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@@ -1,3 +1,17 @@
|
||||
# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
#
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
|
||||
# Misc
|
||||
.git
|
||||
tmp
|
||||
@@ -59,7 +73,7 @@ pip-log.txt
|
||||
pip-delete-this-directory.txt
|
||||
|
||||
# Unit test / coverage reports
|
||||
!tests/data
|
||||
!tests/artifacts
|
||||
htmlcov/
|
||||
.tox/
|
||||
.nox/
|
||||
|
||||
14
.gitattributes
vendored
@@ -1,3 +1,17 @@
|
||||
# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
#
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
|
||||
*.memmap filter=lfs diff=lfs merge=lfs -text
|
||||
*.stl filter=lfs diff=lfs merge=lfs -text
|
||||
*.safetensors filter=lfs diff=lfs merge=lfs -text
|
||||
|
||||
14
.github/ISSUE_TEMPLATE/bug-report.yml
vendored
@@ -1,3 +1,17 @@
|
||||
# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
#
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
|
||||
name: "\U0001F41B Bug Report"
|
||||
description: Submit a bug report to help us improve LeRobot
|
||||
body:
|
||||
|
||||
14
.github/workflows/build-docker-images.yml
vendored
@@ -1,3 +1,17 @@
|
||||
# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
#
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
|
||||
# Inspired by
|
||||
# https://github.com/huggingface/peft/blob/main/.github/workflows/build_docker_images.yml
|
||||
name: Builds
|
||||
|
||||
14
.github/workflows/nightly-tests.yml
vendored
@@ -1,3 +1,17 @@
|
||||
# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
#
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
|
||||
# Inspired by
|
||||
# https://github.com/huggingface/peft/blob/main/.github/workflows/nightly.yml
|
||||
name: Nightly
|
||||
|
||||
125
.github/workflows/pr_style_bot.yml
vendored
@@ -1,125 +0,0 @@
|
||||
# Adapted from https://github.com/huggingface/diffusers/blob/main/.github/workflows/pr_style_bot.yml
|
||||
name: PR Style Bot
|
||||
|
||||
on:
|
||||
issue_comment:
|
||||
types: [created]
|
||||
|
||||
permissions:
|
||||
contents: write
|
||||
pull-requests: write
|
||||
|
||||
jobs:
|
||||
run-style-bot:
|
||||
if: >
|
||||
contains(github.event.comment.body, '@bot /style') &&
|
||||
github.event.issue.pull_request != null
|
||||
runs-on: ubuntu-latest
|
||||
|
||||
steps:
|
||||
- name: Extract PR details
|
||||
id: pr_info
|
||||
uses: actions/github-script@v6
|
||||
with:
|
||||
script: |
|
||||
const prNumber = context.payload.issue.number;
|
||||
const { data: pr } = await github.rest.pulls.get({
|
||||
owner: context.repo.owner,
|
||||
repo: context.repo.repo,
|
||||
pull_number: prNumber
|
||||
});
|
||||
|
||||
// We capture both the branch ref and the "full_name" of the head repo
|
||||
// so that we can check out the correct repository & branch (including forks).
|
||||
core.setOutput("prNumber", prNumber);
|
||||
core.setOutput("headRef", pr.head.ref);
|
||||
core.setOutput("headRepoFullName", pr.head.repo.full_name);
|
||||
|
||||
- name: Check out PR branch
|
||||
uses: actions/checkout@v4
|
||||
env:
|
||||
HEADREPOFULLNAME: ${{ steps.pr_info.outputs.headRepoFullName }}
|
||||
HEADREF: ${{ steps.pr_info.outputs.headRef }}
|
||||
with:
|
||||
persist-credentials: true
|
||||
# Instead of checking out the base repo, use the contributor's repo name
|
||||
repository: ${{ env.HEADREPOFULLNAME }}
|
||||
ref: ${{ env.HEADREF }}
|
||||
# You may need fetch-depth: 0 for being able to push
|
||||
fetch-depth: 0
|
||||
token: ${{ secrets.GITHUB_TOKEN }}
|
||||
|
||||
- name: Debug
|
||||
env:
|
||||
HEADREPOFULLNAME: ${{ steps.pr_info.outputs.headRepoFullName }}
|
||||
HEADREF: ${{ steps.pr_info.outputs.headRef }}
|
||||
PRNUMBER: ${{ steps.pr_info.outputs.prNumber }}
|
||||
run: |
|
||||
echo "PR number: ${PRNUMBER}"
|
||||
echo "Head Ref: ${HEADREF}"
|
||||
echo "Head Repo Full Name: ${HEADREPOFULLNAME}"
|
||||
|
||||
- name: Set up Python
|
||||
uses: actions/setup-python@v4
|
||||
|
||||
- name: Get Ruff Version from pre-commit-config.yaml
|
||||
id: get-ruff-version
|
||||
run: |
|
||||
RUFF_VERSION=$(awk '/repo: https:\/\/github.com\/astral-sh\/ruff-pre-commit/{flag=1;next}/rev:/{if(flag){print $2;exit}}' .pre-commit-config.yaml)
|
||||
echo "ruff_version=${RUFF_VERSION}" >> $GITHUB_OUTPUT
|
||||
|
||||
- name: Install Ruff
|
||||
env:
|
||||
RUFF_VERSION: ${{ steps.get-ruff-version.outputs.ruff_version }}
|
||||
run: python -m pip install "ruff==${RUFF_VERSION}"
|
||||
|
||||
- name: Ruff check
|
||||
run: ruff check --fix
|
||||
|
||||
- name: Ruff format
|
||||
run: ruff format
|
||||
|
||||
- name: Commit and push changes
|
||||
id: commit_and_push
|
||||
env:
|
||||
HEADREPOFULLNAME: ${{ steps.pr_info.outputs.headRepoFullName }}
|
||||
HEADREF: ${{ steps.pr_info.outputs.headRef }}
|
||||
PRNUMBER: ${{ steps.pr_info.outputs.prNumber }}
|
||||
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
|
||||
run: |
|
||||
echo "HEADREPOFULLNAME: ${HEADREPOFULLNAME}, HEADREF: ${HEADREF}"
|
||||
# Configure git with the Actions bot user
|
||||
git config user.name "github-actions[bot]"
|
||||
git config user.email "github-actions[bot]@users.noreply.github.com"
|
||||
|
||||
# Make sure your 'origin' remote is set to the contributor's fork
|
||||
git remote set-url origin "https://x-access-token:${GITHUB_TOKEN}@github.com/${HEADREPOFULLNAME}.git"
|
||||
|
||||
# If there are changes after running style/quality, commit them
|
||||
if [ -n "$(git status --porcelain)" ]; then
|
||||
git add .
|
||||
git commit -m "Apply style fixes"
|
||||
# Push to the original contributor's forked branch
|
||||
git push origin HEAD:${HEADREF}
|
||||
echo "changes_pushed=true" >> $GITHUB_OUTPUT
|
||||
else
|
||||
echo "No changes to commit."
|
||||
echo "changes_pushed=false" >> $GITHUB_OUTPUT
|
||||
fi
|
||||
|
||||
- name: Comment on PR with workflow run link
|
||||
if: steps.commit_and_push.outputs.changes_pushed == 'true'
|
||||
uses: actions/github-script@v6
|
||||
with:
|
||||
script: |
|
||||
const prNumber = parseInt(process.env.prNumber, 10);
|
||||
const runUrl = `${process.env.GITHUB_SERVER_URL}/${process.env.GITHUB_REPOSITORY}/actions/runs/${process.env.GITHUB_RUN_ID}`
|
||||
|
||||
await github.rest.issues.createComment({
|
||||
owner: context.repo.owner,
|
||||
repo: context.repo.repo,
|
||||
issue_number: prNumber,
|
||||
body: `Style fixes have been applied. [View the workflow run here](${runUrl}).`
|
||||
});
|
||||
env:
|
||||
prNumber: ${{ steps.pr_info.outputs.prNumber }}
|
||||
14
.github/workflows/quality.yml
vendored
@@ -1,3 +1,17 @@
|
||||
# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
#
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
|
||||
name: Quality
|
||||
|
||||
on:
|
||||
|
||||
14
.github/workflows/test-docker-build.yml
vendored
@@ -1,3 +1,17 @@
|
||||
# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
#
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
|
||||
# Inspired by
|
||||
# https://github.com/huggingface/peft/blob/main/.github/workflows/test-docker-build.yml
|
||||
name: Test Dockerfiles
|
||||
|
||||
14
.github/workflows/test.yml
vendored
@@ -1,3 +1,17 @@
|
||||
# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
#
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
|
||||
name: Tests
|
||||
|
||||
on:
|
||||
|
||||
14
.github/workflows/trufflehog.yml
vendored
@@ -1,3 +1,17 @@
|
||||
# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
#
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
|
||||
on:
|
||||
push:
|
||||
|
||||
|
||||
16
.gitignore
vendored
@@ -1,3 +1,17 @@
|
||||
# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
#
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
|
||||
# Logging
|
||||
logs
|
||||
tmp
|
||||
@@ -64,7 +78,7 @@ pip-log.txt
|
||||
pip-delete-this-directory.txt
|
||||
|
||||
# Unit test / coverage reports
|
||||
!tests/data
|
||||
!tests/artifacts
|
||||
htmlcov/
|
||||
.tox/
|
||||
.nox/
|
||||
|
||||
@@ -1,7 +1,29 @@
|
||||
exclude: ^(tests/data)
|
||||
# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
#
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
|
||||
exclude: "tests/artifacts/.*\\.safetensors$"
|
||||
default_language_version:
|
||||
python: python3.10
|
||||
repos:
|
||||
##### Meta #####
|
||||
- repo: meta
|
||||
hooks:
|
||||
- id: check-useless-excludes
|
||||
- id: check-hooks-apply
|
||||
|
||||
|
||||
##### Style / Misc. #####
|
||||
- repo: https://github.com/pre-commit/pre-commit-hooks
|
||||
rev: v5.0.0
|
||||
hooks:
|
||||
@@ -13,26 +35,40 @@ repos:
|
||||
- id: check-toml
|
||||
- id: end-of-file-fixer
|
||||
- id: trailing-whitespace
|
||||
|
||||
- repo: https://github.com/crate-ci/typos
|
||||
rev: v1.29.10
|
||||
rev: v1.30.2
|
||||
hooks:
|
||||
- id: typos
|
||||
args: [--force-exclude]
|
||||
|
||||
- repo: https://github.com/asottile/pyupgrade
|
||||
rev: v3.19.1
|
||||
hooks:
|
||||
- id: pyupgrade
|
||||
|
||||
- repo: https://github.com/astral-sh/ruff-pre-commit
|
||||
rev: v0.9.6
|
||||
rev: v0.9.10
|
||||
hooks:
|
||||
- id: ruff
|
||||
args: [--fix]
|
||||
- id: ruff-format
|
||||
|
||||
|
||||
##### Security #####
|
||||
- repo: https://github.com/gitleaks/gitleaks
|
||||
rev: v8.23.3
|
||||
rev: v8.24.0
|
||||
hooks:
|
||||
- id: gitleaks
|
||||
|
||||
- repo: https://github.com/woodruffw/zizmor-pre-commit
|
||||
rev: v1.3.1
|
||||
rev: v1.4.1
|
||||
hooks:
|
||||
- id: zizmor
|
||||
|
||||
- repo: https://github.com/PyCQA/bandit
|
||||
rev: 1.8.3
|
||||
hooks:
|
||||
- id: bandit
|
||||
args: ["-c", "pyproject.toml"]
|
||||
additional_dependencies: ["bandit[toml]"]
|
||||
|
||||
@@ -291,7 +291,7 @@ sudo apt-get install git-lfs
|
||||
git lfs install
|
||||
```
|
||||
|
||||
Pull artifacts if they're not in [tests/data](tests/data)
|
||||
Pull artifacts if they're not in [tests/artifacts](tests/artifacts)
|
||||
```bash
|
||||
git lfs pull
|
||||
```
|
||||
|
||||
32
Makefile
@@ -1,3 +1,17 @@
|
||||
# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
#
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
|
||||
.PHONY: tests
|
||||
|
||||
PYTHON_PATH := $(shell which python)
|
||||
@@ -33,6 +47,7 @@ test-act-ete-train:
|
||||
--policy.dim_model=64 \
|
||||
--policy.n_action_steps=20 \
|
||||
--policy.chunk_size=20 \
|
||||
--policy.device=$(DEVICE) \
|
||||
--env.type=aloha \
|
||||
--env.episode_length=5 \
|
||||
--dataset.repo_id=lerobot/aloha_sim_transfer_cube_human \
|
||||
@@ -47,7 +62,6 @@ test-act-ete-train:
|
||||
--save_checkpoint=true \
|
||||
--log_freq=1 \
|
||||
--wandb.enable=false \
|
||||
--device=$(DEVICE) \
|
||||
--output_dir=tests/outputs/act/
|
||||
|
||||
test-act-ete-train-resume:
|
||||
@@ -58,11 +72,11 @@ test-act-ete-train-resume:
|
||||
test-act-ete-eval:
|
||||
python lerobot/scripts/eval.py \
|
||||
--policy.path=tests/outputs/act/checkpoints/000004/pretrained_model \
|
||||
--policy.device=$(DEVICE) \
|
||||
--env.type=aloha \
|
||||
--env.episode_length=5 \
|
||||
--eval.n_episodes=1 \
|
||||
--eval.batch_size=1 \
|
||||
--device=$(DEVICE)
|
||||
--eval.batch_size=1
|
||||
|
||||
test-diffusion-ete-train:
|
||||
python lerobot/scripts/train.py \
|
||||
@@ -70,6 +84,7 @@ test-diffusion-ete-train:
|
||||
--policy.down_dims='[64,128,256]' \
|
||||
--policy.diffusion_step_embed_dim=32 \
|
||||
--policy.num_inference_steps=10 \
|
||||
--policy.device=$(DEVICE) \
|
||||
--env.type=pusht \
|
||||
--env.episode_length=5 \
|
||||
--dataset.repo_id=lerobot/pusht \
|
||||
@@ -84,21 +99,21 @@ test-diffusion-ete-train:
|
||||
--save_freq=2 \
|
||||
--log_freq=1 \
|
||||
--wandb.enable=false \
|
||||
--device=$(DEVICE) \
|
||||
--output_dir=tests/outputs/diffusion/
|
||||
|
||||
test-diffusion-ete-eval:
|
||||
python lerobot/scripts/eval.py \
|
||||
--policy.path=tests/outputs/diffusion/checkpoints/000002/pretrained_model \
|
||||
--policy.device=$(DEVICE) \
|
||||
--env.type=pusht \
|
||||
--env.episode_length=5 \
|
||||
--eval.n_episodes=1 \
|
||||
--eval.batch_size=1 \
|
||||
--device=$(DEVICE)
|
||||
--eval.batch_size=1
|
||||
|
||||
test-tdmpc-ete-train:
|
||||
python lerobot/scripts/train.py \
|
||||
--policy.type=tdmpc \
|
||||
--policy.device=$(DEVICE) \
|
||||
--env.type=xarm \
|
||||
--env.task=XarmLift-v0 \
|
||||
--env.episode_length=5 \
|
||||
@@ -114,15 +129,14 @@ test-tdmpc-ete-train:
|
||||
--save_freq=2 \
|
||||
--log_freq=1 \
|
||||
--wandb.enable=false \
|
||||
--device=$(DEVICE) \
|
||||
--output_dir=tests/outputs/tdmpc/
|
||||
|
||||
test-tdmpc-ete-eval:
|
||||
python lerobot/scripts/eval.py \
|
||||
--policy.path=tests/outputs/tdmpc/checkpoints/000002/pretrained_model \
|
||||
--policy.device=$(DEVICE) \
|
||||
--env.type=xarm \
|
||||
--env.episode_length=5 \
|
||||
--env.task=XarmLift-v0 \
|
||||
--eval.n_episodes=1 \
|
||||
--eval.batch_size=1 \
|
||||
--device=$(DEVICE)
|
||||
--eval.batch_size=1
|
||||
|
||||
28
README.md
@@ -23,15 +23,24 @@
|
||||
</div>
|
||||
|
||||
<h2 align="center">
|
||||
<p><a href="https://github.com/huggingface/lerobot/blob/main/examples/10_use_so100.md">New robot in town: SO-100</a></p>
|
||||
<p><a href="https://github.com/huggingface/lerobot/blob/main/examples/10_use_so100.md">
|
||||
Build Your Own SO-100 Robot!</a></p>
|
||||
</h2>
|
||||
|
||||
<div align="center">
|
||||
<img src="media/so100/leader_follower.webp?raw=true" alt="SO-100 leader and follower arms" title="SO-100 leader and follower arms" width="50%">
|
||||
<p>We just added a new tutorial on how to build a more affordable robot, at the price of $110 per arm!</p>
|
||||
<p>Teach it new skills by showing it a few moves with just a laptop.</p>
|
||||
<p>Then watch your homemade robot act autonomously 🤯</p>
|
||||
<p>Follow the link to the <a href="https://github.com/huggingface/lerobot/blob/main/examples/10_use_so100.md">full tutorial for SO-100</a>.</p>
|
||||
<img src="media/so100/leader_follower.webp?raw=true" alt="SO-100 leader and follower arms" title="SO-100 leader and follower arms" width="50%">
|
||||
|
||||
<p><strong>Meet the SO-100 – Just $110 per arm!</strong></p>
|
||||
<p>Train it in minutes with a few simple moves on your laptop.</p>
|
||||
<p>Then sit back and watch your creation act autonomously! 🤯</p>
|
||||
|
||||
<p><a href="https://github.com/huggingface/lerobot/blob/main/examples/10_use_so100.md">
|
||||
Get the full SO-100 tutorial here.</a></p>
|
||||
|
||||
<p>Want to take it to the next level? Make your SO-100 mobile by building LeKiwi!</p>
|
||||
<p>Check out the <a href="https://github.com/huggingface/lerobot/blob/main/examples/11_use_lekiwi.md">LeKiwi tutorial</a> and bring your robot to life on wheels.</p>
|
||||
|
||||
<img src="media/lekiwi/kiwi.webp?raw=true" alt="LeKiwi mobile robot" title="LeKiwi mobile robot" width="50%">
|
||||
</div>
|
||||
|
||||
<br/>
|
||||
@@ -223,8 +232,8 @@ python lerobot/scripts/eval.py \
|
||||
--env.type=pusht \
|
||||
--eval.batch_size=10 \
|
||||
--eval.n_episodes=10 \
|
||||
--use_amp=false \
|
||||
--device=cuda
|
||||
--policy.use_amp=false \
|
||||
--policy.device=cuda
|
||||
```
|
||||
|
||||
Note: After training your own policy, you can re-evaluate the checkpoints with:
|
||||
@@ -375,3 +384,6 @@ Additionally, if you are using any of the particular policy architecture, pretra
|
||||
year={2024}
|
||||
}
|
||||
```
|
||||
## Star History
|
||||
|
||||
[](https://star-history.com/#huggingface/lerobot&Timeline)
|
||||
|
||||
@@ -4,8 +4,8 @@
|
||||
|
||||
- [A. Source the parts](#a-source-the-parts)
|
||||
- [B. Install LeRobot](#b-install-lerobot)
|
||||
- [C. Configure the motors](#c-configure-the-motors)
|
||||
- [D. Assemble the arms](#d-assemble-the-arms)
|
||||
- [C. Configure the Motors](#c-configure-the-motors)
|
||||
- [D. Step-by-Step Assembly Instructions](#d-step-by-step-assembly-instructions)
|
||||
- [E. Calibrate](#e-calibrate)
|
||||
- [F. Teleoperate](#f-teleoperate)
|
||||
- [G. Record a dataset](#g-record-a-dataset)
|
||||
@@ -70,6 +70,7 @@ conda install -y -c conda-forge "opencv>=4.10.0"
|
||||
```
|
||||
Great :hugs:! You are now done installing LeRobot and we can begin assembling the SO100 arms :robot:.
|
||||
Every time you now want to use LeRobot you can go to the `~/lerobot` folder where we installed LeRobot and run one of the commands.
|
||||
|
||||
## C. Configure the motors
|
||||
|
||||
> [!NOTE]
|
||||
@@ -98,22 +99,22 @@ Example output when identifying the leader arm's port (e.g., `/dev/tty.usbmodem5
|
||||
```
|
||||
Finding all available ports for the MotorBus.
|
||||
['/dev/tty.usbmodem575E0032081', '/dev/tty.usbmodem575E0031751']
|
||||
Remove the usb cable from your DynamixelMotorsBus and press Enter when done.
|
||||
Remove the usb cable from your MotorsBus and press Enter when done.
|
||||
|
||||
[...Disconnect leader arm and press Enter...]
|
||||
|
||||
The port of this DynamixelMotorsBus is /dev/tty.usbmodem575E0031751
|
||||
The port of this MotorsBus is /dev/tty.usbmodem575E0031751
|
||||
Reconnect the usb cable.
|
||||
```
|
||||
Example output when identifying the follower arm's port (e.g., `/dev/tty.usbmodem575E0032081`, or possibly `/dev/ttyACM1` on Linux):
|
||||
```
|
||||
Finding all available ports for the MotorBus.
|
||||
['/dev/tty.usbmodem575E0032081', '/dev/tty.usbmodem575E0031751']
|
||||
Remove the usb cable from your DynamixelMotorsBus and press Enter when done.
|
||||
Remove the usb cable from your MotorsBus and press Enter when done.
|
||||
|
||||
[...Disconnect follower arm and press Enter...]
|
||||
|
||||
The port of this DynamixelMotorsBus is /dev/tty.usbmodem575E0032081
|
||||
The port of this MotorsBus is /dev/tty.usbmodem575E0032081
|
||||
Reconnect the usb cable.
|
||||
```
|
||||
|
||||
@@ -221,19 +222,13 @@ Redo the process for all your motors until ID 6. Do the same for the 6 motors of
|
||||
|
||||
Follow the video for removing gears. You need to remove the gear for the motors of the leader arm. As a result, you will only use the position encoding of the motor and reduce friction to more easily operate the leader arm.
|
||||
|
||||
#### c. Add motor horn to all 12 motors
|
||||
## D. Step-by-Step Assembly Instructions
|
||||
|
||||
<details>
|
||||
<summary><strong>Video adding motor horn</strong></summary>
|
||||
**Step 1: Clean Parts**
|
||||
- Remove all support material from the 3D-printed parts.
|
||||
---
|
||||
|
||||
<video src="https://github.com/user-attachments/assets/ef3391a4-ad05-4100-b2bd-1699bf86c969"></video>
|
||||
|
||||
</details>
|
||||
|
||||
Follow the video for adding the motor horn. For SO-100, you need to align the holes on the motor horn to the motor spline to be approximately 1:30, 4:30, 7:30 and 10:30.
|
||||
Try to avoid rotating the motor while doing so to keep position 2048 set during configuration. It is especially tricky for the leader motors as it is more sensible without the gears, but it's ok if it's a bit rotated.
|
||||
|
||||
## D. Assemble the arms
|
||||
### Additional Guidance
|
||||
|
||||
<details>
|
||||
<summary><strong>Video assembling arms</strong></summary>
|
||||
@@ -242,7 +237,211 @@ Try to avoid rotating the motor while doing so to keep position 2048 set during
|
||||
|
||||
</details>
|
||||
|
||||
Follow the video for assembling the arms. It is important to insert the cables into the motor that is being assembled before you assemble the motor into the arm! Inserting the cables beforehand is much easier than doing this afterward. The first arm should take a bit more than 1 hour to assemble, but once you get used to it, you can do it under 1 hour for the second arm.
|
||||
**Note:**
|
||||
This video provides visual guidance for assembling the arms, but it doesn't specify when or how to do the wiring. Inserting the cables beforehand is much easier than doing it afterward. The first arm may take a bit more than 1 hour to assemble, but once you get used to it, you can assemble the second arm in under 1 hour.
|
||||
|
||||
---
|
||||
|
||||
### First Motor
|
||||
|
||||
**Step 2: Insert Wires**
|
||||
- Insert two wires into the first motor.
|
||||
|
||||
<img src="../media/tutorial/img1.jpg" style="height:300px;">
|
||||
|
||||
**Step 3: Install in Base**
|
||||
- Place the first motor into the base.
|
||||
|
||||
<img src="../media/tutorial/img2.jpg" style="height:300px;">
|
||||
|
||||
**Step 4: Secure Motor**
|
||||
- Fasten the motor with 4 screws. Two from the bottom and two from top.
|
||||
|
||||
**Step 5: Attach Motor Holder**
|
||||
- Slide over the first motor holder and fasten it using two screws (one on each side).
|
||||
|
||||
<img src="../media/tutorial/img4.jpg" style="height:300px;">
|
||||
|
||||
**Step 6: Attach Motor Horns**
|
||||
- Install both motor horns, securing the top horn with a screw. Try not to move the motor position when attaching the motor horn, especially for the leader arms, where we removed the gears.
|
||||
|
||||
<img src="../media/tutorial/img5.jpg" style="height:300px;">
|
||||
<details>
|
||||
<summary><strong>Video adding motor horn</strong></summary>
|
||||
<video src="https://github.com/user-attachments/assets/ef3391a4-ad05-4100-b2bd-1699bf86c969"></video>
|
||||
</details>
|
||||
|
||||
**Step 7: Attach Shoulder Part**
|
||||
- Route one wire to the back of the robot and the other to the left or in photo towards you (see photo).
|
||||
- Attach the shoulder part.
|
||||
|
||||
<img src="../media/tutorial/img6.jpg" style="height:300px;">
|
||||
|
||||
**Step 8: Secure Shoulder**
|
||||
- Tighten the shoulder part with 4 screws on top and 4 on the bottom
|
||||
*(access bottom holes by turning the shoulder).*
|
||||
|
||||
---
|
||||
|
||||
### Second Motor Assembly
|
||||
|
||||
**Step 9: Install Motor 2**
|
||||
- Slide the second motor in from the top and link the wire from motor 1 to motor 2.
|
||||
|
||||
<img src="../media/tutorial/img8.jpg" style="height:300px;">
|
||||
|
||||
**Step 10: Attach Shoulder Holder**
|
||||
- Add the shoulder motor holder.
|
||||
- Ensure the wire from motor 1 to motor 2 goes behind the holder while the other wire is routed upward (see photo).
|
||||
- This part can be tight to assemble, you can use a workbench like the image or a similar setup to push the part around the motor.
|
||||
|
||||
<div style="display: flex;">
|
||||
<img src="../media/tutorial/img9.jpg" style="height:250px;">
|
||||
<img src="../media/tutorial/img10.jpg" style="height:250px;">
|
||||
<img src="../media/tutorial/img12.jpg" style="height:250px;">
|
||||
</div>
|
||||
|
||||
**Step 11: Secure Motor 2**
|
||||
- Fasten the second motor with 4 screws.
|
||||
|
||||
**Step 12: Attach Motor Horn**
|
||||
- Attach both motor horns to motor 2, again use the horn screw.
|
||||
|
||||
**Step 13: Attach Base**
|
||||
- Install the base attachment using 2 screws.
|
||||
|
||||
<img src="../media/tutorial/img11.jpg" style="height:300px;">
|
||||
|
||||
**Step 14: Attach Upper Arm**
|
||||
- Attach the upper arm with 4 screws on each side.
|
||||
|
||||
<img src="../media/tutorial/img13.jpg" style="height:300px;">
|
||||
|
||||
---
|
||||
|
||||
### Third Motor Assembly
|
||||
|
||||
**Step 15: Install Motor 3**
|
||||
- Route the motor cable from motor 2 through the cable holder to motor 3, then secure motor 3 with 4 screws.
|
||||
|
||||
**Step 16: Attach Motor Horn**
|
||||
- Attach both motor horns to motor 3 and secure one again with a horn screw.
|
||||
|
||||
<img src="../media/tutorial/img14.jpg" style="height:300px;">
|
||||
|
||||
**Step 17: Attach Forearm**
|
||||
- Connect the forearm to motor 3 using 4 screws on each side.
|
||||
|
||||
<img src="../media/tutorial/img15.jpg" style="height:300px;">
|
||||
|
||||
---
|
||||
|
||||
### Fourth Motor Assembly
|
||||
|
||||
**Step 18: Install Motor 4**
|
||||
- Slide in motor 4, attach the cable from motor 3, and secure the cable in its holder with a screw.
|
||||
|
||||
<div style="display: flex;">
|
||||
<img src="../media/tutorial/img16.jpg" style="height:300px;">
|
||||
<img src="../media/tutorial/img19.jpg" style="height:300px;">
|
||||
</div>
|
||||
|
||||
**Step 19: Attach Motor Holder 4**
|
||||
- Install the fourth motor holder (a tight fit). Ensure one wire is routed upward and the wire from motor 3 is routed downward (see photo).
|
||||
|
||||
<img src="../media/tutorial/img17.jpg" style="height:300px;">
|
||||
|
||||
**Step 20: Secure Motor 4 & Attach Horn**
|
||||
- Fasten motor 4 with 4 screws and attach its motor horns, use for one a horn screw.
|
||||
|
||||
<img src="../media/tutorial/img18.jpg" style="height:300px;">
|
||||
|
||||
---
|
||||
|
||||
### Wrist Assembly
|
||||
|
||||
**Step 21: Install Motor 5**
|
||||
- Insert motor 5 into the wrist holder and secure it with 2 front screws.
|
||||
|
||||
<img src="../media/tutorial/img20.jpg" style="height:300px;">
|
||||
|
||||
**Step 22: Attach Wrist**
|
||||
- Connect the wire from motor 4 to motor 5. And already insert the other wire for the gripper.
|
||||
- Secure the wrist to motor 4 using 4 screws on both sides.
|
||||
|
||||
<img src="../media/tutorial/img22.jpg" style="height:300px;">
|
||||
|
||||
**Step 23: Attach Wrist Horn**
|
||||
- Install only one motor horn on the wrist motor and secure it with a horn screw.
|
||||
|
||||
<img src="../media/tutorial/img23.jpg" style="height:300px;">
|
||||
|
||||
---
|
||||
|
||||
### Follower Configuration
|
||||
|
||||
**Step 24: Attach Gripper**
|
||||
- Attach the gripper to motor 5.
|
||||
|
||||
<img src="../media/tutorial/img24.jpg" style="height:300px;">
|
||||
|
||||
**Step 25: Install Gripper Motor**
|
||||
- Insert the gripper motor, connect the motor wire from motor 5 to motor 6, and secure it with 3 screws on each side.
|
||||
|
||||
<img src="../media/tutorial/img25.jpg" style="height:300px;">
|
||||
|
||||
**Step 26: Attach Gripper Horn & Claw**
|
||||
- Attach the motor horns and again use a horn screw.
|
||||
- Install the gripper claw and secure it with 4 screws on both sides.
|
||||
|
||||
<img src="../media/tutorial/img26.jpg" style="height:300px;">
|
||||
|
||||
**Step 27: Mount Controller**
|
||||
- Attach the motor controller on the back.
|
||||
|
||||
<div style="display: flex;">
|
||||
<img src="../media/tutorial/img27.jpg" style="height:300px;">
|
||||
<img src="../media/tutorial/img28.jpg" style="height:300px;">
|
||||
</div>
|
||||
|
||||
*Assembly complete – proceed to Leader arm assembly.*
|
||||
|
||||
---
|
||||
|
||||
### Leader Configuration
|
||||
|
||||
For the leader configuration, perform **Steps 1–23**. Make sure that you removed the motor gears from the motors.
|
||||
|
||||
**Step 24: Attach Leader Holder**
|
||||
- Mount the leader holder onto the wrist and secure it with a screw.
|
||||
|
||||
<img src="../media/tutorial/img29.jpg" style="height:300px;">
|
||||
|
||||
**Step 25: Attach Handle**
|
||||
- Attach the handle to motor 5 using 4 screws.
|
||||
|
||||
<img src="../media/tutorial/img30.jpg" style="height:300px;">
|
||||
|
||||
**Step 26: Install Gripper Motor**
|
||||
- Insert the gripper motor, secure it with 3 screws on each side, attach a motor horn using a horn screw, and connect the motor wire.
|
||||
|
||||
<img src="../media/tutorial/img31.jpg" style="height:300px;">
|
||||
|
||||
**Step 27: Attach Trigger**
|
||||
- Attach the follower trigger with 4 screws.
|
||||
|
||||
<img src="../media/tutorial/img32.jpg" style="height:300px;">
|
||||
|
||||
**Step 28: Mount Controller**
|
||||
- Attach the motor controller on the back.
|
||||
|
||||
<div style="display: flex;">
|
||||
<img src="../media/tutorial/img27.jpg" style="height:300px;">
|
||||
<img src="../media/tutorial/img28.jpg" style="height:300px;">
|
||||
</div>
|
||||
|
||||
*Assembly complete – proceed to calibration.*
|
||||
|
||||
|
||||
## E. Calibrate
|
||||
|
||||
@@ -255,8 +454,8 @@ Next, you'll need to calibrate your SO-100 robot to ensure that the leader and f
|
||||
|
||||
You will need to move the follower arm to these positions sequentially:
|
||||
|
||||
| 1. Zero position | 2. Rotated position | 3. Rest position |
|
||||
|---|---|---|
|
||||
| 1. Zero position | 2. Rotated position | 3. Rest position |
|
||||
| ------------------------------------------------------------------------------------------------------------------------------------------------------------ | --------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------ |
|
||||
| <img src="../media/so100/follower_zero.webp?raw=true" alt="SO-100 follower arm zero position" title="SO-100 follower arm zero position" style="width:100%;"> | <img src="../media/so100/follower_rotated.webp?raw=true" alt="SO-100 follower arm rotated position" title="SO-100 follower arm rotated position" style="width:100%;"> | <img src="../media/so100/follower_rest.webp?raw=true" alt="SO-100 follower arm rest position" title="SO-100 follower arm rest position" style="width:100%;"> |
|
||||
|
||||
Make sure both arms are connected and run this script to launch manual calibration:
|
||||
@@ -271,8 +470,8 @@ python lerobot/scripts/control_robot.py \
|
||||
#### b. Manual calibration of leader arm
|
||||
Follow step 6 of the [assembly video](https://youtu.be/FioA2oeFZ5I?t=724) which illustrates the manual calibration. You will need to move the leader arm to these positions sequentially:
|
||||
|
||||
| 1. Zero position | 2. Rotated position | 3. Rest position |
|
||||
|---|---|---|
|
||||
| 1. Zero position | 2. Rotated position | 3. Rest position |
|
||||
| ------------------------------------------------------------------------------------------------------------------------------------------------------ | --------------------------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------ |
|
||||
| <img src="../media/so100/leader_zero.webp?raw=true" alt="SO-100 leader arm zero position" title="SO-100 leader arm zero position" style="width:100%;"> | <img src="../media/so100/leader_rotated.webp?raw=true" alt="SO-100 leader arm rotated position" title="SO-100 leader arm rotated position" style="width:100%;"> | <img src="../media/so100/leader_rest.webp?raw=true" alt="SO-100 leader arm rest position" title="SO-100 leader arm rest position" style="width:100%;"> |
|
||||
|
||||
Run this script to launch manual calibration:
|
||||
@@ -372,14 +571,14 @@ python lerobot/scripts/train.py \
|
||||
--policy.type=act \
|
||||
--output_dir=outputs/train/act_so100_test \
|
||||
--job_name=act_so100_test \
|
||||
--device=cuda \
|
||||
--policy.device=cuda \
|
||||
--wandb.enable=true
|
||||
```
|
||||
|
||||
Let's explain it:
|
||||
1. We provided the dataset as argument with `--dataset.repo_id=${HF_USER}/so100_test`.
|
||||
2. We provided the policy with `policy.type=act`. This loads configurations from [`configuration_act.py`](../lerobot/common/policies/act/configuration_act.py). Importantly, this policy will automatically adapt to the number of motor sates, motor actions and cameras of your robot (e.g. `laptop` and `phone`) which have been saved in your dataset.
|
||||
4. We provided `device=cuda` since we are training on a Nvidia GPU, but you could use `device=mps` to train on Apple silicon.
|
||||
4. We provided `policy.device=cuda` since we are training on a Nvidia GPU, but you could use `policy.device=mps` to train on Apple silicon.
|
||||
5. We provided `wandb.enable=true` to use [Weights and Biases](https://docs.wandb.ai/quickstart) for visualizing training plots. This is optional but if you use it, make sure you are logged in by running `wandb login`.
|
||||
|
||||
Training should take several hours. You will find checkpoints in `outputs/train/act_so100_test/checkpoints`.
|
||||
|
||||
@@ -23,6 +23,9 @@ Follow this [README](https://github.com/SIGRobotics-UIUC/LeKiwi). It contains th
|
||||
|
||||
Before assembling, you will first need to configure your motors. To this end, we provide a nice script, so let's first install LeRobot. After configuration, we will also guide you through assembly.
|
||||
|
||||
### Wired version
|
||||
If you have the **wired** LeKiwi version you can skip the installation of the Raspberry Pi and setting up SSH. You can also run all commands directly on your PC for both the LeKiwi scripts and the leader arm scripts for teleoperating.
|
||||
|
||||
## B. Install software on Pi
|
||||
Now we have to setup the remote PC that will run on the LeKiwi Robot. This is normally a Raspberry Pi, but can be any PC that can run on 5V and has enough usb ports (2 or more) for the cameras and motor control board.
|
||||
|
||||
@@ -246,6 +249,110 @@ class LeKiwiRobotConfig(RobotConfig):
|
||||
}
|
||||
)
|
||||
|
||||
teleop_keys: dict[str, str] = field(
|
||||
default_factory=lambda: {
|
||||
# Movement
|
||||
"forward": "w",
|
||||
"backward": "s",
|
||||
"left": "a",
|
||||
"right": "d",
|
||||
"rotate_left": "z",
|
||||
"rotate_right": "x",
|
||||
# Speed control
|
||||
"speed_up": "r",
|
||||
"speed_down": "f",
|
||||
# quit teleop
|
||||
"quit": "q",
|
||||
}
|
||||
)
|
||||
|
||||
mock: bool = False
|
||||
```
|
||||
|
||||
## Wired version
|
||||
|
||||
For the wired LeKiwi version your configured IP address should refer to your own laptop (127.0.0.1), because leader arm and LeKiwi are in this case connected to own laptop. Below and example configuration for this wired setup:
|
||||
```python
|
||||
@RobotConfig.register_subclass("lekiwi")
|
||||
@dataclass
|
||||
class LeKiwiRobotConfig(RobotConfig):
|
||||
# `max_relative_target` limits the magnitude of the relative positional target vector for safety purposes.
|
||||
# Set this to a positive scalar to have the same value for all motors, or a list that is the same length as
|
||||
# the number of motors in your follower arms.
|
||||
max_relative_target: int | None = None
|
||||
|
||||
# Network Configuration
|
||||
ip: str = "127.0.0.1"
|
||||
port: int = 5555
|
||||
video_port: int = 5556
|
||||
|
||||
cameras: dict[str, CameraConfig] = field(
|
||||
default_factory=lambda: {
|
||||
"front": OpenCVCameraConfig(
|
||||
camera_index=0, fps=30, width=640, height=480, rotation=90
|
||||
),
|
||||
"wrist": OpenCVCameraConfig(
|
||||
camera_index=1, fps=30, width=640, height=480, rotation=180
|
||||
),
|
||||
}
|
||||
)
|
||||
|
||||
calibration_dir: str = ".cache/calibration/lekiwi"
|
||||
|
||||
leader_arms: dict[str, MotorsBusConfig] = field(
|
||||
default_factory=lambda: {
|
||||
"main": FeetechMotorsBusConfig(
|
||||
port="/dev/tty.usbmodem585A0077581",
|
||||
motors={
|
||||
# name: (index, model)
|
||||
"shoulder_pan": [1, "sts3215"],
|
||||
"shoulder_lift": [2, "sts3215"],
|
||||
"elbow_flex": [3, "sts3215"],
|
||||
"wrist_flex": [4, "sts3215"],
|
||||
"wrist_roll": [5, "sts3215"],
|
||||
"gripper": [6, "sts3215"],
|
||||
},
|
||||
),
|
||||
}
|
||||
)
|
||||
|
||||
follower_arms: dict[str, MotorsBusConfig] = field(
|
||||
default_factory=lambda: {
|
||||
"main": FeetechMotorsBusConfig(
|
||||
port="/dev/tty.usbmodem58760431061",
|
||||
motors={
|
||||
# name: (index, model)
|
||||
"shoulder_pan": [1, "sts3215"],
|
||||
"shoulder_lift": [2, "sts3215"],
|
||||
"elbow_flex": [3, "sts3215"],
|
||||
"wrist_flex": [4, "sts3215"],
|
||||
"wrist_roll": [5, "sts3215"],
|
||||
"gripper": [6, "sts3215"],
|
||||
"left_wheel": (7, "sts3215"),
|
||||
"back_wheel": (8, "sts3215"),
|
||||
"right_wheel": (9, "sts3215"),
|
||||
},
|
||||
),
|
||||
}
|
||||
)
|
||||
|
||||
teleop_keys: dict[str, str] = field(
|
||||
default_factory=lambda: {
|
||||
# Movement
|
||||
"forward": "w",
|
||||
"backward": "s",
|
||||
"left": "a",
|
||||
"right": "d",
|
||||
"rotate_left": "z",
|
||||
"rotate_right": "x",
|
||||
# Speed control
|
||||
"speed_up": "r",
|
||||
"speed_down": "f",
|
||||
# quit teleop
|
||||
"quit": "q",
|
||||
}
|
||||
)
|
||||
|
||||
mock: bool = False
|
||||
```
|
||||
|
||||
@@ -259,8 +366,8 @@ Now we have to calibrate the leader arm and the follower arm. The wheel motors d
|
||||
|
||||
You will need to move the follower arm to these positions sequentially:
|
||||
|
||||
| 1. Zero position | 2. Rotated position | 3. Rest position |
|
||||
|---|---|---|
|
||||
| 1. Zero position | 2. Rotated position | 3. Rest position |
|
||||
| ----------------------------------------------------------------------------------------------------------------------------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------- |
|
||||
| <img src="../media/lekiwi/mobile_calib_zero.webp?raw=true" alt="SO-100 follower arm zero position" title="SO-100 follower arm zero position" style="width:100%;"> | <img src="../media/lekiwi/mobile_calib_rotated.webp?raw=true" alt="SO-100 follower arm rotated position" title="SO-100 follower arm rotated position" style="width:100%;"> | <img src="../media/lekiwi/mobile_calib_rest.webp?raw=true" alt="SO-100 follower arm rest position" title="SO-100 follower arm rest position" style="width:100%;"> |
|
||||
|
||||
Make sure the arm is connected to the Raspberry Pi and run this script (on the Raspberry Pi) to launch manual calibration:
|
||||
@@ -272,11 +379,14 @@ python lerobot/scripts/control_robot.py \
|
||||
--control.arms='["main_follower"]'
|
||||
```
|
||||
|
||||
### Wired version
|
||||
If you have the **wired** LeKiwi version please run all commands including this calibration command on your laptop.
|
||||
|
||||
### Calibrate leader arm
|
||||
Then to calibrate the leader arm (which is attached to the laptop/pc). You will need to move the leader arm to these positions sequentially:
|
||||
|
||||
| 1. Zero position | 2. Rotated position | 3. Rest position |
|
||||
|---|---|---|
|
||||
| 1. Zero position | 2. Rotated position | 3. Rest position |
|
||||
| ------------------------------------------------------------------------------------------------------------------------------------------------------ | --------------------------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------ |
|
||||
| <img src="../media/so100/leader_zero.webp?raw=true" alt="SO-100 leader arm zero position" title="SO-100 leader arm zero position" style="width:100%;"> | <img src="../media/so100/leader_rotated.webp?raw=true" alt="SO-100 leader arm rotated position" title="SO-100 leader arm rotated position" style="width:100%;"> | <img src="../media/so100/leader_rest.webp?raw=true" alt="SO-100 leader arm rest position" title="SO-100 leader arm rest position" style="width:100%;"> |
|
||||
|
||||
Run this script (on your laptop/pc) to launch manual calibration:
|
||||
@@ -306,26 +416,29 @@ python lerobot/scripts/control_robot.py \
|
||||
|
||||
You should see on your laptop something like this: ```[INFO] Connected to remote robot at tcp://172.17.133.91:5555 and video stream at tcp://172.17.133.91:5556.``` Now you can move the leader arm and use the keyboard (w,a,s,d) to drive forward, left, backwards, right. And use (z,x) to turn left or turn right. You can use (r,f) to increase and decrease the speed of the mobile robot. There are three speed modes, see the table below:
|
||||
| Speed Mode | Linear Speed (m/s) | Rotation Speed (deg/s) |
|
||||
|------------|-------------------|-----------------------|
|
||||
| Fast | 0.4 | 90 |
|
||||
| Medium | 0.25 | 60 |
|
||||
| Slow | 0.1 | 30 |
|
||||
| ---------- | ------------------ | ---------------------- |
|
||||
| Fast | 0.4 | 90 |
|
||||
| Medium | 0.25 | 60 |
|
||||
| Slow | 0.1 | 30 |
|
||||
|
||||
|
||||
| Key | Action |
|
||||
|------|--------------------------------|
|
||||
| W | Move forward |
|
||||
| A | Move left |
|
||||
| S | Move backward |
|
||||
| D | Move right |
|
||||
| Z | Turn left |
|
||||
| X | Turn right |
|
||||
| R | Increase speed |
|
||||
| F | Decrease speed |
|
||||
| Key | Action |
|
||||
| --- | -------------- |
|
||||
| W | Move forward |
|
||||
| A | Move left |
|
||||
| S | Move backward |
|
||||
| D | Move right |
|
||||
| Z | Turn left |
|
||||
| X | Turn right |
|
||||
| R | Increase speed |
|
||||
| F | Decrease speed |
|
||||
|
||||
> [!TIP]
|
||||
> If you use a different keyboard you can change the keys for each command in the [`LeKiwiRobotConfig`](../lerobot/common/robot_devices/robots/configs.py).
|
||||
|
||||
### Wired version
|
||||
If you have the **wired** LeKiwi version please run all commands including both these teleoperation commands on your laptop.
|
||||
|
||||
## Troubleshoot communication
|
||||
|
||||
If you are having trouble connecting to the Mobile SO100, follow these steps to diagnose and resolve the issue.
|
||||
@@ -364,6 +477,13 @@ Make sure the configuration file on both your laptop/pc and the Raspberry Pi is
|
||||
# G. Record a dataset
|
||||
Once you're familiar with teleoperation, you can record your first dataset with LeKiwi.
|
||||
|
||||
To start the program on LeKiwi, SSH into your Raspberry Pi, and run `conda activate lerobot` and this script:
|
||||
```bash
|
||||
python lerobot/scripts/control_robot.py \
|
||||
--robot.type=lekiwi \
|
||||
--control.type=remote_robot
|
||||
```
|
||||
|
||||
If you want to use the Hugging Face hub features for uploading your dataset and you haven't previously done it, make sure you've logged in using a write-access token, which can be generated from the [Hugging Face settings](https://huggingface.co/settings/tokens):
|
||||
```bash
|
||||
huggingface-cli login --token ${HUGGINGFACE_TOKEN} --add-to-git-credential
|
||||
@@ -374,8 +494,7 @@ Store your Hugging Face repository name in a variable to run these commands:
|
||||
HF_USER=$(huggingface-cli whoami | head -n 1)
|
||||
echo $HF_USER
|
||||
```
|
||||
|
||||
Record 2 episodes and upload your dataset to the hub:
|
||||
On your laptop then run this command to record 2 episodes and upload your dataset to the hub:
|
||||
```bash
|
||||
python lerobot/scripts/control_robot.py \
|
||||
--robot.type=lekiwi \
|
||||
@@ -393,6 +512,9 @@ python lerobot/scripts/control_robot.py \
|
||||
|
||||
Note: You can resume recording by adding `--control.resume=true`.
|
||||
|
||||
### Wired version
|
||||
If you have the **wired** LeKiwi version please run all commands including both these record dataset commands on your laptop.
|
||||
|
||||
# H. Visualize a dataset
|
||||
|
||||
If you uploaded your dataset to the hub with `--control.push_to_hub=true`, you can [visualize your dataset online](https://huggingface.co/spaces/lerobot/visualize_dataset) by copy pasting your repo id given by:
|
||||
@@ -427,14 +549,14 @@ python lerobot/scripts/train.py \
|
||||
--policy.type=act \
|
||||
--output_dir=outputs/train/act_lekiwi_test \
|
||||
--job_name=act_lekiwi_test \
|
||||
--device=cuda \
|
||||
--policy.device=cuda \
|
||||
--wandb.enable=true
|
||||
```
|
||||
|
||||
Let's explain it:
|
||||
1. We provided the dataset as argument with `--dataset.repo_id=${HF_USER}/lekiwi_test`.
|
||||
2. We provided the policy with `policy.type=act`. This loads configurations from [`configuration_act.py`](../lerobot/common/policies/act/configuration_act.py). Importantly, this policy will automatically adapt to the number of motor sates, motor actions and cameras of your robot (e.g. `laptop` and `phone`) which have been saved in your dataset.
|
||||
4. We provided `device=cuda` since we are training on a Nvidia GPU, but you could use `device=mps` to train on Apple silicon.
|
||||
4. We provided `policy.device=cuda` since we are training on a Nvidia GPU, but you could use `policy.device=mps` to train on Apple silicon.
|
||||
5. We provided `wandb.enable=true` to use [Weights and Biases](https://docs.wandb.ai/quickstart) for visualizing training plots. This is optional but if you use it, make sure you are logged in by running `wandb login`.
|
||||
|
||||
Training should take several hours. You will find checkpoints in `outputs/train/act_lekiwi_test/checkpoints`.
|
||||
|
||||
@@ -176,8 +176,8 @@ Next, you'll need to calibrate your Moss v1 robot to ensure that the leader and
|
||||
|
||||
You will need to move the follower arm to these positions sequentially:
|
||||
|
||||
| 1. Zero position | 2. Rotated position | 3. Rest position |
|
||||
|---|---|---|
|
||||
| 1. Zero position | 2. Rotated position | 3. Rest position |
|
||||
| ------------------------------------------------------------------------------------------------------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------- |
|
||||
| <img src="../media/moss/follower_zero.webp?raw=true" alt="Moss v1 follower arm zero position" title="Moss v1 follower arm zero position" style="width:100%;"> | <img src="../media/moss/follower_rotated.webp?raw=true" alt="Moss v1 follower arm rotated position" title="Moss v1 follower arm rotated position" style="width:100%;"> | <img src="../media/moss/follower_rest.webp?raw=true" alt="Moss v1 follower arm rest position" title="Moss v1 follower arm rest position" style="width:100%;"> |
|
||||
|
||||
Make sure both arms are connected and run this script to launch manual calibration:
|
||||
@@ -192,8 +192,8 @@ python lerobot/scripts/control_robot.py \
|
||||
**Manual calibration of leader arm**
|
||||
Follow step 6 of the [assembly video](https://www.youtube.com/watch?v=DA91NJOtMic) which illustrates the manual calibration. You will need to move the leader arm to these positions sequentially:
|
||||
|
||||
| 1. Zero position | 2. Rotated position | 3. Rest position |
|
||||
|---|---|---|
|
||||
| 1. Zero position | 2. Rotated position | 3. Rest position |
|
||||
| ------------------------------------------------------------------------------------------------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------- |
|
||||
| <img src="../media/moss/leader_zero.webp?raw=true" alt="Moss v1 leader arm zero position" title="Moss v1 leader arm zero position" style="width:100%;"> | <img src="../media/moss/leader_rotated.webp?raw=true" alt="Moss v1 leader arm rotated position" title="Moss v1 leader arm rotated position" style="width:100%;"> | <img src="../media/moss/leader_rest.webp?raw=true" alt="Moss v1 leader arm rest position" title="Moss v1 leader arm rest position" style="width:100%;"> |
|
||||
|
||||
Run this script to launch manual calibration:
|
||||
@@ -293,14 +293,14 @@ python lerobot/scripts/train.py \
|
||||
--policy.type=act \
|
||||
--output_dir=outputs/train/act_moss_test \
|
||||
--job_name=act_moss_test \
|
||||
--device=cuda \
|
||||
--policy.device=cuda \
|
||||
--wandb.enable=true
|
||||
```
|
||||
|
||||
Let's explain it:
|
||||
1. We provided the dataset as argument with `--dataset.repo_id=${HF_USER}/moss_test`.
|
||||
2. We provided the policy with `policy.type=act`. This loads configurations from [`configuration_act.py`](../lerobot/common/policies/act/configuration_act.py). Importantly, this policy will automatically adapt to the number of motor sates, motor actions and cameras of your robot (e.g. `laptop` and `phone`) which have been saved in your dataset.
|
||||
4. We provided `device=cuda` since we are training on a Nvidia GPU, but you could use `device=mps` to train on Apple silicon.
|
||||
4. We provided `policy.device=cuda` since we are training on a Nvidia GPU, but you could use `policy.device=mps` to train on Apple silicon.
|
||||
5. We provided `wandb.enable=true` to use [Weights and Biases](https://docs.wandb.ai/quickstart) for visualizing training plots. This is optional but if you use it, make sure you are logged in by running `wandb login`.
|
||||
|
||||
Training should take several hours. You will find checkpoints in `outputs/train/act_moss_test/checkpoints`.
|
||||
|
||||
@@ -1,3 +1,17 @@
|
||||
# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
#
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
|
||||
"""
|
||||
This script demonstrates the use of `LeRobotDataset` class for handling and processing robotic datasets from Hugging Face.
|
||||
It illustrates how to load datasets, manipulate them, and apply transformations suitable for machine learning tasks in PyTorch.
|
||||
|
||||
@@ -1,3 +1,17 @@
|
||||
# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
#
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
|
||||
"""
|
||||
This scripts demonstrates how to evaluate a pretrained policy from the HuggingFace Hub or from your local
|
||||
training outputs directory. In the latter case, you might want to run examples/3_train_policy.py first.
|
||||
@@ -30,7 +44,7 @@ pretrained_policy_path = "lerobot/diffusion_pusht"
|
||||
# OR a path to a local outputs/train folder.
|
||||
# pretrained_policy_path = Path("outputs/train/example_pusht_diffusion")
|
||||
|
||||
policy = DiffusionPolicy.from_pretrained(pretrained_policy_path, map_location=device)
|
||||
policy = DiffusionPolicy.from_pretrained(pretrained_policy_path)
|
||||
|
||||
# Initialize evaluation environment to render two observation types:
|
||||
# an image of the scene and state/position of the agent. The environment
|
||||
|
||||
@@ -1,3 +1,17 @@
|
||||
# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
#
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
|
||||
"""This scripts demonstrates how to train Diffusion Policy on the PushT environment.
|
||||
|
||||
Once you have trained a model with this script, you can try to evaluate it on
|
||||
@@ -85,7 +99,7 @@ def main():
|
||||
done = False
|
||||
while not done:
|
||||
for batch in dataloader:
|
||||
batch = {k: v.to(device, non_blocking=True) for k, v in batch.items()}
|
||||
batch = {k: (v.to(device) if isinstance(v, torch.Tensor) else v) for k, v in batch.items()}
|
||||
loss, _ = policy.forward(batch)
|
||||
loss.backward()
|
||||
optimizer.step()
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
This tutorial will explain the training script, how to use it, and particularly how to configure everything needed for the training run.
|
||||
> **Note:** The following assume you're running these commands on a machine equipped with a cuda GPU. If you don't have one (or if you're using a Mac), you can add `--device=cpu` (`--device=mps` respectively). However, be advised that the code executes much slower on cpu.
|
||||
> **Note:** The following assume you're running these commands on a machine equipped with a cuda GPU. If you don't have one (or if you're using a Mac), you can add `--policy.device=cpu` (`--policy.device=mps` respectively). However, be advised that the code executes much slower on cpu.
|
||||
|
||||
|
||||
## The training script
|
||||
|
||||
@@ -386,14 +386,14 @@ When you connect your robot for the first time, the [`ManipulatorRobot`](../lero
|
||||
|
||||
Here are the positions you'll move the follower arm to:
|
||||
|
||||
| 1. Zero position | 2. Rotated position | 3. Rest position |
|
||||
|---|---|---|
|
||||
| 1. Zero position | 2. Rotated position | 3. Rest position |
|
||||
| ----------------------------------------------------------------------------------------------------------------------------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------- |
|
||||
| <img src="../media/koch/follower_zero.webp?raw=true" alt="Koch v1.1 follower arm zero position" title="Koch v1.1 follower arm zero position" style="width:100%;"> | <img src="../media/koch/follower_rotated.webp?raw=true" alt="Koch v1.1 follower arm rotated position" title="Koch v1.1 follower arm rotated position" style="width:100%;"> | <img src="../media/koch/follower_rest.webp?raw=true" alt="Koch v1.1 follower arm rest position" title="Koch v1.1 follower arm rest position" style="width:100%;"> |
|
||||
|
||||
And here are the corresponding positions for the leader arm:
|
||||
|
||||
| 1. Zero position | 2. Rotated position | 3. Rest position |
|
||||
|---|---|---|
|
||||
| 1. Zero position | 2. Rotated position | 3. Rest position |
|
||||
| ----------------------------------------------------------------------------------------------------------------------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------- |
|
||||
| <img src="../media/koch/leader_zero.webp?raw=true" alt="Koch v1.1 leader arm zero position" title="Koch v1.1 leader arm zero position" style="width:100%;"> | <img src="../media/koch/leader_rotated.webp?raw=true" alt="Koch v1.1 leader arm rotated position" title="Koch v1.1 leader arm rotated position" style="width:100%;"> | <img src="../media/koch/leader_rest.webp?raw=true" alt="Koch v1.1 leader arm rest position" title="Koch v1.1 leader arm rest position" style="width:100%;"> |
|
||||
|
||||
You can watch a [video tutorial of the calibration procedure](https://youtu.be/8drnU9uRY24) for more details.
|
||||
@@ -898,14 +898,14 @@ python lerobot/scripts/train.py \
|
||||
--policy.type=act \
|
||||
--output_dir=outputs/train/act_koch_test \
|
||||
--job_name=act_koch_test \
|
||||
--device=cuda \
|
||||
--policy.device=cuda \
|
||||
--wandb.enable=true
|
||||
```
|
||||
|
||||
Let's explain it:
|
||||
1. We provided the dataset as argument with `--dataset.repo_id=${HF_USER}/koch_test`.
|
||||
2. We provided the policy with `policy.type=act`. This loads configurations from [`configuration_act.py`](../lerobot/common/policies/act/configuration_act.py). Importantly, this policy will automatically adapt to the number of motor sates, motor actions and cameras of your robot (e.g. `laptop` and `phone`) which have been saved in your dataset.
|
||||
4. We provided `device=cuda` since we are training on a Nvidia GPU, but you could use `device=mps` to train on Apple silicon.
|
||||
4. We provided `policy.device=cuda` since we are training on a Nvidia GPU, but you could use `policy.device=mps` to train on Apple silicon.
|
||||
5. We provided `wandb.enable=true` to use [Weights and Biases](https://docs.wandb.ai/quickstart) for visualizing training plots. This is optional but if you use it, make sure you are logged in by running `wandb login`.
|
||||
|
||||
For more information on the `train` script see the previous tutorial: [`examples/4_train_policy_with_script.md`](../examples/4_train_policy_with_script.md)
|
||||
|
||||
@@ -135,14 +135,14 @@ python lerobot/scripts/train.py \
|
||||
--policy.type=act \
|
||||
--output_dir=outputs/train/act_aloha_test \
|
||||
--job_name=act_aloha_test \
|
||||
--device=cuda \
|
||||
--policy.device=cuda \
|
||||
--wandb.enable=true
|
||||
```
|
||||
|
||||
Let's explain it:
|
||||
1. We provided the dataset as argument with `--dataset.repo_id=${HF_USER}/aloha_test`.
|
||||
2. We provided the policy with `policy.type=act`. This loads configurations from [`configuration_act.py`](../lerobot/common/policies/act/configuration_act.py). Importantly, this policy will automatically adapt to the number of motor sates, motor actions and cameras of your robot (e.g. `laptop` and `phone`) which have been saved in your dataset.
|
||||
4. We provided `device=cuda` since we are training on a Nvidia GPU, but you could use `device=mps` to train on Apple silicon.
|
||||
4. We provided `policy.device=cuda` since we are training on a Nvidia GPU, but you could use `policy.device=mps` to train on Apple silicon.
|
||||
5. We provided `wandb.enable=true` to use [Weights and Biases](https://docs.wandb.ai/quickstart) for visualizing training plots. This is optional but if you use it, make sure you are logged in by running `wandb login`.
|
||||
|
||||
For more information on the `train` script see the previous tutorial: [`examples/4_train_policy_with_script.md`](../examples/4_train_policy_with_script.md)
|
||||
|
||||
@@ -1,3 +1,17 @@
|
||||
# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
#
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
|
||||
"""
|
||||
This script demonstrates how to use torchvision's image transformation with LeRobotDataset for data
|
||||
augmentation purposes. The transformations are passed to the dataset as an argument upon creation, and
|
||||
|
||||
@@ -1,3 +1,17 @@
|
||||
# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
#
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
|
||||
"""This script demonstrates how to slice a dataset and calculate the loss on a subset of the data.
|
||||
|
||||
This technique can be useful for debugging and testing purposes, as well as identifying whether a policy
|
||||
|
||||
@@ -1,3 +1,17 @@
|
||||
# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
#
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
|
||||
import shutil
|
||||
from pathlib import Path
|
||||
|
||||
|
||||
@@ -1,3 +1,16 @@
|
||||
# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
#
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
# keys
|
||||
import os
|
||||
from pathlib import Path
|
||||
|
||||
@@ -1,3 +1,17 @@
|
||||
# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
#
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
|
||||
import packaging.version
|
||||
|
||||
V2_MESSAGE = """
|
||||
|
||||
@@ -13,6 +13,7 @@
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
import contextlib
|
||||
import logging
|
||||
import shutil
|
||||
from pathlib import Path
|
||||
@@ -27,6 +28,7 @@ import torch.utils
|
||||
from datasets import concatenate_datasets, load_dataset
|
||||
from huggingface_hub import HfApi, snapshot_download
|
||||
from huggingface_hub.constants import REPOCARD_NAME
|
||||
from huggingface_hub.errors import RevisionNotFoundError
|
||||
|
||||
from lerobot.common.constants import HF_LEROBOT_HOME
|
||||
from lerobot.common.datasets.compute_stats import aggregate_stats, compute_episode_stats
|
||||
@@ -517,6 +519,7 @@ class LeRobotDataset(torch.utils.data.Dataset):
|
||||
branch: str | None = None,
|
||||
tags: list | None = None,
|
||||
license: str | None = "apache-2.0",
|
||||
tag_version: bool = True,
|
||||
push_videos: bool = True,
|
||||
private: bool = False,
|
||||
allow_patterns: list[str] | str | None = None,
|
||||
@@ -562,6 +565,11 @@ class LeRobotDataset(torch.utils.data.Dataset):
|
||||
)
|
||||
card.push_to_hub(repo_id=self.repo_id, repo_type="dataset", revision=branch)
|
||||
|
||||
if tag_version:
|
||||
with contextlib.suppress(RevisionNotFoundError):
|
||||
hub_api.delete_tag(self.repo_id, tag=CODEBASE_VERSION, repo_type="dataset")
|
||||
hub_api.create_tag(self.repo_id, tag=CODEBASE_VERSION, revision=branch, repo_type="dataset")
|
||||
|
||||
def pull_from_repo(
|
||||
self,
|
||||
allow_patterns: list[str] | str | None = None,
|
||||
|
||||
@@ -31,6 +31,7 @@ import packaging.version
|
||||
import torch
|
||||
from datasets.table import embed_table_storage
|
||||
from huggingface_hub import DatasetCard, DatasetCardData, HfApi
|
||||
from huggingface_hub.errors import RevisionNotFoundError
|
||||
from PIL import Image as PILImage
|
||||
from torchvision import transforms
|
||||
|
||||
@@ -325,6 +326,19 @@ def get_safe_version(repo_id: str, version: str | packaging.version.Version) ->
|
||||
)
|
||||
hub_versions = get_repo_versions(repo_id)
|
||||
|
||||
if not hub_versions:
|
||||
raise RevisionNotFoundError(
|
||||
f"""Your dataset must be tagged with a codebase version.
|
||||
Assuming _version_ is the codebase_version value in the info.json, you can run this:
|
||||
```python
|
||||
from huggingface_hub import HfApi
|
||||
|
||||
hub_api = HfApi()
|
||||
hub_api.create_tag("{repo_id}", tag="_version_", repo_type="dataset")
|
||||
```
|
||||
"""
|
||||
)
|
||||
|
||||
if target_version in hub_versions:
|
||||
return f"v{target_version}"
|
||||
|
||||
|
||||
@@ -1,3 +1,17 @@
|
||||
# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
#
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
|
||||
import logging
|
||||
import traceback
|
||||
from pathlib import Path
|
||||
|
||||
@@ -1,3 +1,17 @@
|
||||
# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
#
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
|
||||
"""
|
||||
This script will help you convert any LeRobot dataset already pushed to the hub from codebase version 2.0 to
|
||||
2.1. It will:
|
||||
@@ -57,7 +71,7 @@ def convert_dataset(
|
||||
dataset.meta.info["codebase_version"] = CODEBASE_VERSION
|
||||
write_info(dataset.meta.info, dataset.root)
|
||||
|
||||
dataset.push_to_hub(branch=branch, allow_patterns="meta/")
|
||||
dataset.push_to_hub(branch=branch, tag_version=False, allow_patterns="meta/")
|
||||
|
||||
# delete old stats.json file
|
||||
if (dataset.root / STATS_PATH).is_file:
|
||||
|
||||
@@ -1,3 +1,17 @@
|
||||
# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
#
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
|
||||
from concurrent.futures import ThreadPoolExecutor, as_completed
|
||||
|
||||
import numpy as np
|
||||
|
||||
@@ -1 +1,15 @@
|
||||
# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
#
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
|
||||
from .configs import AlohaEnv, EnvConfig, PushtEnv, XarmEnv # noqa: F401
|
||||
|
||||
@@ -1,3 +1,17 @@
|
||||
# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
#
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
|
||||
import abc
|
||||
from dataclasses import dataclass, field
|
||||
|
||||
|
||||
@@ -1 +1,15 @@
|
||||
# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
#
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
|
||||
from .optimizers import OptimizerConfig as OptimizerConfig
|
||||
|
||||
@@ -1,3 +1,17 @@
|
||||
# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
#
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
|
||||
from .act.configuration_act import ACTConfig as ACTConfig
|
||||
from .diffusion.configuration_diffusion import DiffusionConfig as DiffusionConfig
|
||||
from .pi0.configuration_pi0 import PI0Config as PI0Config
|
||||
|
||||
@@ -16,7 +16,6 @@
|
||||
|
||||
import logging
|
||||
|
||||
import torch
|
||||
from torch import nn
|
||||
|
||||
from lerobot.common.datasets.lerobot_dataset import LeRobotDatasetMetadata
|
||||
@@ -76,7 +75,6 @@ def make_policy_config(policy_type: str, **kwargs) -> PreTrainedConfig:
|
||||
|
||||
def make_policy(
|
||||
cfg: PreTrainedConfig,
|
||||
device: str | torch.device,
|
||||
ds_meta: LeRobotDatasetMetadata | None = None,
|
||||
env_cfg: EnvConfig | None = None,
|
||||
) -> PreTrainedPolicy:
|
||||
@@ -88,7 +86,6 @@ def make_policy(
|
||||
Args:
|
||||
cfg (PreTrainedConfig): The config of the policy to make. If `pretrained_path` is set, the policy will
|
||||
be loaded with the weights from that path.
|
||||
device (str): the device to load the policy onto.
|
||||
ds_meta (LeRobotDatasetMetadata | None, optional): Dataset metadata to take input/output shapes and
|
||||
statistics to use for (un)normalization of inputs/outputs in the policy. Defaults to None.
|
||||
env_cfg (EnvConfig | None, optional): The config of a gym environment to parse features from. Must be
|
||||
@@ -96,7 +93,7 @@ def make_policy(
|
||||
|
||||
Raises:
|
||||
ValueError: Either ds_meta or env and env_cfg must be provided.
|
||||
NotImplementedError: if the policy.type is 'vqbet' and the device 'mps' (due to an incompatibility)
|
||||
NotImplementedError: if the policy.type is 'vqbet' and the policy device 'mps' (due to an incompatibility)
|
||||
|
||||
Returns:
|
||||
PreTrainedPolicy: _description_
|
||||
@@ -111,7 +108,7 @@ def make_policy(
|
||||
# https://github.com/pytorch/pytorch/issues/77764. As a temporary fix, you can set the environment
|
||||
# variable `PYTORCH_ENABLE_MPS_FALLBACK=1` to use the CPU as a fallback for this op. WARNING: this will be
|
||||
# slower than running natively on MPS.
|
||||
if cfg.type == "vqbet" and str(device) == "mps":
|
||||
if cfg.type == "vqbet" and cfg.device == "mps":
|
||||
raise NotImplementedError(
|
||||
"Current implementation of VQBeT does not support `mps` backend. "
|
||||
"Please use `cpu` or `cuda` backend."
|
||||
@@ -145,7 +142,7 @@ def make_policy(
|
||||
# Make a fresh policy.
|
||||
policy = policy_cls(**kwargs)
|
||||
|
||||
policy.to(device)
|
||||
policy.to(cfg.device)
|
||||
assert isinstance(policy, nn.Module)
|
||||
|
||||
# policy = torch.compile(policy, mode="reduce-overhead")
|
||||
|
||||
@@ -1,3 +1,17 @@
|
||||
# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
#
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
|
||||
from dataclasses import dataclass, field
|
||||
|
||||
from lerobot.common.optim.optimizers import AdamWConfig
|
||||
@@ -76,6 +90,7 @@ class PI0Config(PreTrainedConfig):
|
||||
def __post_init__(self):
|
||||
super().__post_init__()
|
||||
|
||||
# TODO(Steven): Validate device and amp? in all policy configs?
|
||||
"""Input validation (not exhaustive)."""
|
||||
if self.n_action_steps > self.chunk_size:
|
||||
raise ValueError(
|
||||
|
||||
@@ -1,3 +1,17 @@
|
||||
# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
#
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
|
||||
import torch
|
||||
|
||||
from lerobot.common.datasets.lerobot_dataset import LeRobotDataset
|
||||
@@ -31,7 +45,7 @@ def main():
|
||||
|
||||
cfg = PreTrainedConfig.from_pretrained(ckpt_torch_dir)
|
||||
cfg.pretrained_path = ckpt_torch_dir
|
||||
policy = make_policy(cfg, device, ds_meta=dataset.meta)
|
||||
policy = make_policy(cfg, ds_meta=dataset.meta)
|
||||
|
||||
# policy = torch.compile(policy, mode="reduce-overhead")
|
||||
|
||||
|
||||
@@ -1,3 +1,17 @@
|
||||
# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
#
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
|
||||
import json
|
||||
import pickle
|
||||
from pathlib import Path
|
||||
@@ -87,7 +101,7 @@ def main():
|
||||
|
||||
cfg = PreTrainedConfig.from_pretrained(ckpt_torch_dir)
|
||||
cfg.pretrained_path = ckpt_torch_dir
|
||||
policy = make_policy(cfg, device, dataset_meta)
|
||||
policy = make_policy(cfg, dataset_meta)
|
||||
|
||||
# loss_dict = policy.forward(batch, noise=noise, time=time_beta)
|
||||
# loss_dict["loss"].backward()
|
||||
|
||||
@@ -1,3 +1,17 @@
|
||||
# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
#
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
|
||||
from transformers import GemmaConfig, PaliGemmaConfig
|
||||
|
||||
|
||||
|
||||
@@ -1,3 +1,17 @@
|
||||
# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
#
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
|
||||
"""
|
||||
Convert pi0 parameters from Jax to Pytorch
|
||||
|
||||
|
||||
@@ -1,3 +1,17 @@
|
||||
# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
#
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
|
||||
import torch
|
||||
import torch.nn.functional as F # noqa: N812
|
||||
from packaging.version import Version
|
||||
|
||||
@@ -313,7 +313,7 @@ class PI0Policy(PreTrainedPolicy):
|
||||
state = self.prepare_state(batch)
|
||||
lang_tokens, lang_masks = self.prepare_language(batch)
|
||||
actions = self.prepare_action(batch)
|
||||
actions_is_pad = batch.get("actions_id_pad")
|
||||
actions_is_pad = batch.get("actions_is_pad")
|
||||
|
||||
loss_dict = {}
|
||||
losses = self.model.forward(images, img_masks, lang_tokens, lang_masks, state, actions, noise, time)
|
||||
|
||||
@@ -1,3 +1,17 @@
|
||||
# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
#
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
|
||||
from typing import List, Optional, Union
|
||||
|
||||
import torch
|
||||
|
||||
@@ -1,3 +1,16 @@
|
||||
# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
#
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
import abc
|
||||
import logging
|
||||
import os
|
||||
@@ -73,7 +86,6 @@ class PreTrainedPolicy(nn.Module, HubMixin, abc.ABC):
|
||||
cache_dir: str | Path | None = None,
|
||||
local_files_only: bool = False,
|
||||
revision: str | None = None,
|
||||
map_location: str = "cpu",
|
||||
strict: bool = False,
|
||||
**kwargs,
|
||||
) -> T:
|
||||
@@ -98,7 +110,7 @@ class PreTrainedPolicy(nn.Module, HubMixin, abc.ABC):
|
||||
if os.path.isdir(model_id):
|
||||
print("Loading weights from local directory")
|
||||
model_file = os.path.join(model_id, SAFETENSORS_SINGLE_FILE)
|
||||
policy = cls._load_as_safetensor(instance, model_file, map_location, strict)
|
||||
policy = cls._load_as_safetensor(instance, model_file, config.device, strict)
|
||||
else:
|
||||
try:
|
||||
model_file = hf_hub_download(
|
||||
@@ -112,13 +124,13 @@ class PreTrainedPolicy(nn.Module, HubMixin, abc.ABC):
|
||||
token=token,
|
||||
local_files_only=local_files_only,
|
||||
)
|
||||
policy = cls._load_as_safetensor(instance, model_file, map_location, strict)
|
||||
policy = cls._load_as_safetensor(instance, model_file, config.device, strict)
|
||||
except HfHubHTTPError as e:
|
||||
raise FileNotFoundError(
|
||||
f"{SAFETENSORS_SINGLE_FILE} not found on the HuggingFace Hub in {model_id}"
|
||||
) from e
|
||||
|
||||
policy.to(map_location)
|
||||
policy.to(config.device)
|
||||
policy.eval()
|
||||
return policy
|
||||
|
||||
|
||||
@@ -1,3 +1,17 @@
|
||||
# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
#
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
|
||||
import abc
|
||||
from dataclasses import dataclass
|
||||
|
||||
|
||||
@@ -1,3 +1,17 @@
|
||||
# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
#
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
|
||||
"""
|
||||
This file contains utilities for recording frames from Intel Realsense cameras.
|
||||
"""
|
||||
@@ -34,7 +48,7 @@ def find_cameras(raise_when_empty=True, mock=False) -> list[dict]:
|
||||
connected to the computer.
|
||||
"""
|
||||
if mock:
|
||||
import tests.mock_pyrealsense2 as rs
|
||||
import tests.cameras.mock_pyrealsense2 as rs
|
||||
else:
|
||||
import pyrealsense2 as rs
|
||||
|
||||
@@ -86,7 +100,7 @@ def save_images_from_cameras(
|
||||
serial_numbers = [cam["serial_number"] for cam in camera_infos]
|
||||
|
||||
if mock:
|
||||
import tests.mock_cv2 as cv2
|
||||
import tests.cameras.mock_cv2 as cv2
|
||||
else:
|
||||
import cv2
|
||||
|
||||
@@ -100,7 +114,7 @@ def save_images_from_cameras(
|
||||
camera = IntelRealSenseCamera(config)
|
||||
camera.connect()
|
||||
print(
|
||||
f"IntelRealSenseCamera({camera.serial_number}, fps={camera.fps}, width={camera.width}, height={camera.height}, color_mode={camera.color_mode})"
|
||||
f"IntelRealSenseCamera({camera.serial_number}, fps={camera.fps}, width={camera.capture_width}, height={camera.capture_height}, color_mode={camera.color_mode})"
|
||||
)
|
||||
cameras.append(camera)
|
||||
|
||||
@@ -210,9 +224,20 @@ class IntelRealSenseCamera:
|
||||
self.serial_number = self.find_serial_number_from_name(config.name)
|
||||
else:
|
||||
self.serial_number = config.serial_number
|
||||
|
||||
# Store the raw (capture) resolution from the config.
|
||||
self.capture_width = config.width
|
||||
self.capture_height = config.height
|
||||
|
||||
# If rotated by ±90, swap width and height.
|
||||
if config.rotation in [-90, 90]:
|
||||
self.width = config.height
|
||||
self.height = config.width
|
||||
else:
|
||||
self.width = config.width
|
||||
self.height = config.height
|
||||
|
||||
self.fps = config.fps
|
||||
self.width = config.width
|
||||
self.height = config.height
|
||||
self.channels = config.channels
|
||||
self.color_mode = config.color_mode
|
||||
self.use_depth = config.use_depth
|
||||
@@ -228,11 +253,10 @@ class IntelRealSenseCamera:
|
||||
self.logs = {}
|
||||
|
||||
if self.mock:
|
||||
import tests.mock_cv2 as cv2
|
||||
import tests.cameras.mock_cv2 as cv2
|
||||
else:
|
||||
import cv2
|
||||
|
||||
# TODO(alibets): Do we keep original width/height or do we define them after rotation?
|
||||
self.rotation = None
|
||||
if config.rotation == -90:
|
||||
self.rotation = cv2.ROTATE_90_COUNTERCLOCKWISE
|
||||
@@ -263,22 +287,26 @@ class IntelRealSenseCamera:
|
||||
)
|
||||
|
||||
if self.mock:
|
||||
import tests.mock_pyrealsense2 as rs
|
||||
import tests.cameras.mock_pyrealsense2 as rs
|
||||
else:
|
||||
import pyrealsense2 as rs
|
||||
|
||||
config = rs.config()
|
||||
config.enable_device(str(self.serial_number))
|
||||
|
||||
if self.fps and self.width and self.height:
|
||||
if self.fps and self.capture_width and self.capture_height:
|
||||
# TODO(rcadene): can we set rgb8 directly?
|
||||
config.enable_stream(rs.stream.color, self.width, self.height, rs.format.rgb8, self.fps)
|
||||
config.enable_stream(
|
||||
rs.stream.color, self.capture_width, self.capture_height, rs.format.rgb8, self.fps
|
||||
)
|
||||
else:
|
||||
config.enable_stream(rs.stream.color)
|
||||
|
||||
if self.use_depth:
|
||||
if self.fps and self.width and self.height:
|
||||
config.enable_stream(rs.stream.depth, self.width, self.height, rs.format.z16, self.fps)
|
||||
if self.fps and self.capture_width and self.capture_height:
|
||||
config.enable_stream(
|
||||
rs.stream.depth, self.capture_width, self.capture_height, rs.format.z16, self.fps
|
||||
)
|
||||
else:
|
||||
config.enable_stream(rs.stream.depth)
|
||||
|
||||
@@ -316,18 +344,18 @@ class IntelRealSenseCamera:
|
||||
raise OSError(
|
||||
f"Can't set {self.fps=} for IntelRealSenseCamera({self.serial_number}). Actual value is {actual_fps}."
|
||||
)
|
||||
if self.width is not None and self.width != actual_width:
|
||||
if self.capture_width is not None and self.capture_width != actual_width:
|
||||
raise OSError(
|
||||
f"Can't set {self.width=} for IntelRealSenseCamera({self.serial_number}). Actual value is {actual_width}."
|
||||
f"Can't set {self.capture_width=} for IntelRealSenseCamera({self.serial_number}). Actual value is {actual_width}."
|
||||
)
|
||||
if self.height is not None and self.height != actual_height:
|
||||
if self.capture_height is not None and self.capture_height != actual_height:
|
||||
raise OSError(
|
||||
f"Can't set {self.height=} for IntelRealSenseCamera({self.serial_number}). Actual value is {actual_height}."
|
||||
f"Can't set {self.capture_height=} for IntelRealSenseCamera({self.serial_number}). Actual value is {actual_height}."
|
||||
)
|
||||
|
||||
self.fps = round(actual_fps)
|
||||
self.width = round(actual_width)
|
||||
self.height = round(actual_height)
|
||||
self.capture_width = round(actual_width)
|
||||
self.capture_height = round(actual_height)
|
||||
|
||||
self.is_connected = True
|
||||
|
||||
@@ -347,7 +375,7 @@ class IntelRealSenseCamera:
|
||||
)
|
||||
|
||||
if self.mock:
|
||||
import tests.mock_cv2 as cv2
|
||||
import tests.cameras.mock_cv2 as cv2
|
||||
else:
|
||||
import cv2
|
||||
|
||||
@@ -373,7 +401,7 @@ class IntelRealSenseCamera:
|
||||
color_image = cv2.cvtColor(color_image, cv2.COLOR_RGB2BGR)
|
||||
|
||||
h, w, _ = color_image.shape
|
||||
if h != self.height or w != self.width:
|
||||
if h != self.capture_height or w != self.capture_width:
|
||||
raise OSError(
|
||||
f"Can't capture color image with expected height and width ({self.height} x {self.width}). ({h} x {w}) returned instead."
|
||||
)
|
||||
@@ -395,7 +423,7 @@ class IntelRealSenseCamera:
|
||||
depth_map = np.asanyarray(depth_frame.get_data())
|
||||
|
||||
h, w = depth_map.shape
|
||||
if h != self.height or w != self.width:
|
||||
if h != self.capture_height or w != self.capture_width:
|
||||
raise OSError(
|
||||
f"Can't capture depth map with expected height and width ({self.height} x {self.width}). ({h} x {w}) returned instead."
|
||||
)
|
||||
|
||||
@@ -1,3 +1,17 @@
|
||||
# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
#
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
|
||||
"""
|
||||
This file contains utilities for recording frames from cameras. For more info look at `OpenCVCamera` docstring.
|
||||
"""
|
||||
@@ -66,7 +80,7 @@ def _find_cameras(
|
||||
possible_camera_ids: list[int | str], raise_when_empty=False, mock=False
|
||||
) -> list[int | str]:
|
||||
if mock:
|
||||
import tests.mock_cv2 as cv2
|
||||
import tests.cameras.mock_cv2 as cv2
|
||||
else:
|
||||
import cv2
|
||||
|
||||
@@ -130,8 +144,8 @@ def save_images_from_cameras(
|
||||
camera = OpenCVCamera(config)
|
||||
camera.connect()
|
||||
print(
|
||||
f"OpenCVCamera({camera.camera_index}, fps={camera.fps}, width={camera.width}, "
|
||||
f"height={camera.height}, color_mode={camera.color_mode})"
|
||||
f"OpenCVCamera({camera.camera_index}, fps={camera.fps}, width={camera.capture_width}, "
|
||||
f"height={camera.capture_height}, color_mode={camera.color_mode})"
|
||||
)
|
||||
cameras.append(camera)
|
||||
|
||||
@@ -230,9 +244,19 @@ class OpenCVCamera:
|
||||
else:
|
||||
raise ValueError(f"Please check the provided camera_index: {self.camera_index}")
|
||||
|
||||
# Store the raw (capture) resolution from the config.
|
||||
self.capture_width = config.width
|
||||
self.capture_height = config.height
|
||||
|
||||
# If rotated by ±90, swap width and height.
|
||||
if config.rotation in [-90, 90]:
|
||||
self.width = config.height
|
||||
self.height = config.width
|
||||
else:
|
||||
self.width = config.width
|
||||
self.height = config.height
|
||||
|
||||
self.fps = config.fps
|
||||
self.width = config.width
|
||||
self.height = config.height
|
||||
self.channels = config.channels
|
||||
self.color_mode = config.color_mode
|
||||
self.mock = config.mock
|
||||
@@ -245,11 +269,10 @@ class OpenCVCamera:
|
||||
self.logs = {}
|
||||
|
||||
if self.mock:
|
||||
import tests.mock_cv2 as cv2
|
||||
import tests.cameras.mock_cv2 as cv2
|
||||
else:
|
||||
import cv2
|
||||
|
||||
# TODO(aliberts): Do we keep original width/height or do we define them after rotation?
|
||||
self.rotation = None
|
||||
if config.rotation == -90:
|
||||
self.rotation = cv2.ROTATE_90_COUNTERCLOCKWISE
|
||||
@@ -263,7 +286,7 @@ class OpenCVCamera:
|
||||
raise RobotDeviceAlreadyConnectedError(f"OpenCVCamera({self.camera_index}) is already connected.")
|
||||
|
||||
if self.mock:
|
||||
import tests.mock_cv2 as cv2
|
||||
import tests.cameras.mock_cv2 as cv2
|
||||
else:
|
||||
import cv2
|
||||
|
||||
@@ -271,10 +294,20 @@ class OpenCVCamera:
|
||||
# when other threads are used to save the images.
|
||||
cv2.setNumThreads(1)
|
||||
|
||||
backend = (
|
||||
cv2.CAP_V4L2
|
||||
if platform.system() == "Linux"
|
||||
else cv2.CAP_DSHOW
|
||||
if platform.system() == "Windows"
|
||||
else cv2.CAP_AVFOUNDATION
|
||||
if platform.system() == "Darwin"
|
||||
else cv2.CAP_ANY
|
||||
)
|
||||
|
||||
camera_idx = f"/dev/video{self.camera_index}" if platform.system() == "Linux" else self.camera_index
|
||||
# First create a temporary camera trying to access `camera_index`,
|
||||
# and verify it is a valid camera by calling `isOpened`.
|
||||
tmp_camera = cv2.VideoCapture(camera_idx)
|
||||
tmp_camera = cv2.VideoCapture(camera_idx, backend)
|
||||
is_camera_open = tmp_camera.isOpened()
|
||||
# Release camera to make it accessible for `find_camera_indices`
|
||||
tmp_camera.release()
|
||||
@@ -297,14 +330,14 @@ class OpenCVCamera:
|
||||
# Secondly, create the camera that will be used downstream.
|
||||
# Note: For some unknown reason, calling `isOpened` blocks the camera which then
|
||||
# needs to be re-created.
|
||||
self.camera = cv2.VideoCapture(camera_idx)
|
||||
self.camera = cv2.VideoCapture(camera_idx, backend)
|
||||
|
||||
if self.fps is not None:
|
||||
self.camera.set(cv2.CAP_PROP_FPS, self.fps)
|
||||
if self.width is not None:
|
||||
self.camera.set(cv2.CAP_PROP_FRAME_WIDTH, self.width)
|
||||
if self.height is not None:
|
||||
self.camera.set(cv2.CAP_PROP_FRAME_HEIGHT, self.height)
|
||||
if self.capture_width is not None:
|
||||
self.camera.set(cv2.CAP_PROP_FRAME_WIDTH, self.capture_width)
|
||||
if self.capture_height is not None:
|
||||
self.camera.set(cv2.CAP_PROP_FRAME_HEIGHT, self.capture_height)
|
||||
|
||||
actual_fps = self.camera.get(cv2.CAP_PROP_FPS)
|
||||
actual_width = self.camera.get(cv2.CAP_PROP_FRAME_WIDTH)
|
||||
@@ -316,19 +349,22 @@ class OpenCVCamera:
|
||||
raise OSError(
|
||||
f"Can't set {self.fps=} for OpenCVCamera({self.camera_index}). Actual value is {actual_fps}."
|
||||
)
|
||||
if self.width is not None and not math.isclose(self.width, actual_width, rel_tol=1e-3):
|
||||
if self.capture_width is not None and not math.isclose(
|
||||
self.capture_width, actual_width, rel_tol=1e-3
|
||||
):
|
||||
raise OSError(
|
||||
f"Can't set {self.width=} for OpenCVCamera({self.camera_index}). Actual value is {actual_width}."
|
||||
f"Can't set {self.capture_width=} for OpenCVCamera({self.camera_index}). Actual value is {actual_width}."
|
||||
)
|
||||
if self.height is not None and not math.isclose(self.height, actual_height, rel_tol=1e-3):
|
||||
if self.capture_height is not None and not math.isclose(
|
||||
self.capture_height, actual_height, rel_tol=1e-3
|
||||
):
|
||||
raise OSError(
|
||||
f"Can't set {self.height=} for OpenCVCamera({self.camera_index}). Actual value is {actual_height}."
|
||||
f"Can't set {self.capture_height=} for OpenCVCamera({self.camera_index}). Actual value is {actual_height}."
|
||||
)
|
||||
|
||||
self.fps = round(actual_fps)
|
||||
self.width = round(actual_width)
|
||||
self.height = round(actual_height)
|
||||
|
||||
self.capture_width = round(actual_width)
|
||||
self.capture_height = round(actual_height)
|
||||
self.is_connected = True
|
||||
|
||||
def read(self, temporary_color_mode: str | None = None) -> np.ndarray:
|
||||
@@ -362,14 +398,14 @@ class OpenCVCamera:
|
||||
# so we convert the image color from BGR to RGB.
|
||||
if requested_color_mode == "rgb":
|
||||
if self.mock:
|
||||
import tests.mock_cv2 as cv2
|
||||
import tests.cameras.mock_cv2 as cv2
|
||||
else:
|
||||
import cv2
|
||||
|
||||
color_image = cv2.cvtColor(color_image, cv2.COLOR_BGR2RGB)
|
||||
|
||||
h, w, _ = color_image.shape
|
||||
if h != self.height or w != self.width:
|
||||
if h != self.capture_height or w != self.capture_width:
|
||||
raise OSError(
|
||||
f"Can't capture color image with expected height and width ({self.height} x {self.width}). ({h} x {w}) returned instead."
|
||||
)
|
||||
|
||||
@@ -1,3 +1,17 @@
|
||||
# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
#
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
|
||||
from typing import Protocol
|
||||
|
||||
import numpy as np
|
||||
@@ -31,7 +45,7 @@ def make_cameras_from_configs(camera_configs: dict[str, CameraConfig]) -> list[C
|
||||
|
||||
cameras[key] = IntelRealSenseCamera(cfg)
|
||||
else:
|
||||
raise ValueError(f"The motor type '{cfg.type}' is not valid.")
|
||||
raise ValueError(f"The camera type '{cfg.type}' is not valid.")
|
||||
|
||||
return cameras
|
||||
|
||||
|
||||
@@ -1,14 +1,25 @@
|
||||
import logging
|
||||
# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
#
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
|
||||
from dataclasses import dataclass
|
||||
from pathlib import Path
|
||||
|
||||
import draccus
|
||||
|
||||
from lerobot.common.robot_devices.robots.configs import RobotConfig
|
||||
from lerobot.common.utils.utils import auto_select_torch_device, is_amp_available, is_torch_device_available
|
||||
from lerobot.configs import parser
|
||||
from lerobot.configs.policies import PreTrainedConfig
|
||||
from lerobot.configs.train import TrainPipelineConfig
|
||||
|
||||
|
||||
@dataclass
|
||||
@@ -43,11 +54,6 @@ class RecordControlConfig(ControlConfig):
|
||||
# Root directory where the dataset will be stored (e.g. 'dataset/path').
|
||||
root: str | Path | None = None
|
||||
policy: PreTrainedConfig | None = None
|
||||
# TODO(rcadene, aliberts): By default, use device and use_amp values from policy checkpoint.
|
||||
device: str | None = None # cuda | cpu | mps
|
||||
# `use_amp` determines whether to use Automatic Mixed Precision (AMP) for training and evaluation. With AMP,
|
||||
# automatic gradient scaling is used.
|
||||
use_amp: bool | None = None
|
||||
# Limit the frames per second. By default, uses the policy fps.
|
||||
fps: int | None = None
|
||||
# Number of seconds before starting data collection. It allows the robot devices to warmup and synchronize.
|
||||
@@ -90,27 +96,6 @@ class RecordControlConfig(ControlConfig):
|
||||
self.policy = PreTrainedConfig.from_pretrained(policy_path, cli_overrides=cli_overrides)
|
||||
self.policy.pretrained_path = policy_path
|
||||
|
||||
# When no device or use_amp are given, use the one from training config.
|
||||
if self.device is None or self.use_amp is None:
|
||||
train_cfg = TrainPipelineConfig.from_pretrained(policy_path)
|
||||
if self.device is None:
|
||||
self.device = train_cfg.device
|
||||
if self.use_amp is None:
|
||||
self.use_amp = train_cfg.use_amp
|
||||
|
||||
# Automatically switch to available device if necessary
|
||||
if not is_torch_device_available(self.device):
|
||||
auto_device = auto_select_torch_device()
|
||||
logging.warning(f"Device '{self.device}' is not available. Switching to '{auto_device}'.")
|
||||
self.device = auto_device
|
||||
|
||||
# Automatically deactivate AMP if necessary
|
||||
if self.use_amp and not is_amp_available(self.device):
|
||||
logging.warning(
|
||||
f"Automatic Mixed Precision (amp) is not available on device '{self.device}'. Deactivating AMP."
|
||||
)
|
||||
self.use_amp = False
|
||||
|
||||
|
||||
@ControlConfig.register_subclass("replay")
|
||||
@dataclass
|
||||
|
||||
@@ -1,3 +1,17 @@
|
||||
# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
#
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
|
||||
########################################################################################
|
||||
# Utilities
|
||||
########################################################################################
|
||||
@@ -18,6 +32,7 @@ from termcolor import colored
|
||||
from lerobot.common.datasets.image_writer import safe_stop_image_writer
|
||||
from lerobot.common.datasets.lerobot_dataset import LeRobotDataset
|
||||
from lerobot.common.datasets.utils import get_features_from_robot
|
||||
from lerobot.common.policies.pretrained import PreTrainedPolicy
|
||||
from lerobot.common.robot_devices.robots.utils import Robot
|
||||
from lerobot.common.robot_devices.utils import busy_wait
|
||||
from lerobot.common.utils.utils import get_safe_torch_device, has_method
|
||||
@@ -179,8 +194,6 @@ def record_episode(
|
||||
episode_time_s,
|
||||
display_cameras,
|
||||
policy,
|
||||
device,
|
||||
use_amp,
|
||||
fps,
|
||||
single_task,
|
||||
):
|
||||
@@ -191,8 +204,6 @@ def record_episode(
|
||||
dataset=dataset,
|
||||
events=events,
|
||||
policy=policy,
|
||||
device=device,
|
||||
use_amp=use_amp,
|
||||
fps=fps,
|
||||
teleoperate=policy is None,
|
||||
single_task=single_task,
|
||||
@@ -207,9 +218,7 @@ def control_loop(
|
||||
display_cameras=False,
|
||||
dataset: LeRobotDataset | None = None,
|
||||
events=None,
|
||||
policy=None,
|
||||
device: torch.device | str | None = None,
|
||||
use_amp: bool | None = None,
|
||||
policy: PreTrainedPolicy = None,
|
||||
fps: int | None = None,
|
||||
single_task: str | None = None,
|
||||
):
|
||||
@@ -232,9 +241,6 @@ def control_loop(
|
||||
if dataset is not None and fps is not None and dataset.fps != fps:
|
||||
raise ValueError(f"The dataset fps should be equal to requested fps ({dataset['fps']} != {fps}).")
|
||||
|
||||
if isinstance(device, str):
|
||||
device = get_safe_torch_device(device)
|
||||
|
||||
timestamp = 0
|
||||
start_episode_t = time.perf_counter()
|
||||
while timestamp < control_time_s:
|
||||
@@ -246,7 +252,9 @@ def control_loop(
|
||||
observation = robot.capture_observation()
|
||||
|
||||
if policy is not None:
|
||||
pred_action = predict_action(observation, policy, device, use_amp)
|
||||
pred_action = predict_action(
|
||||
observation, policy, get_safe_torch_device(policy.config.device), policy.config.use_amp
|
||||
)
|
||||
# Action can eventually be clipped using `max_relative_target`,
|
||||
# so action actually sent is saved in the dataset.
|
||||
action = robot.send_action(pred_action)
|
||||
|
||||
@@ -1,3 +1,17 @@
|
||||
# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
#
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
|
||||
import abc
|
||||
from dataclasses import dataclass
|
||||
|
||||
|
||||
@@ -1,3 +1,17 @@
|
||||
# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
#
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
|
||||
import enum
|
||||
import logging
|
||||
import math
|
||||
@@ -318,7 +332,7 @@ class DynamixelMotorsBus:
|
||||
)
|
||||
|
||||
if self.mock:
|
||||
import tests.mock_dynamixel_sdk as dxl
|
||||
import tests.motors.mock_dynamixel_sdk as dxl
|
||||
else:
|
||||
import dynamixel_sdk as dxl
|
||||
|
||||
@@ -342,7 +356,7 @@ class DynamixelMotorsBus:
|
||||
|
||||
def reconnect(self):
|
||||
if self.mock:
|
||||
import tests.mock_dynamixel_sdk as dxl
|
||||
import tests.motors.mock_dynamixel_sdk as dxl
|
||||
else:
|
||||
import dynamixel_sdk as dxl
|
||||
|
||||
@@ -632,7 +646,7 @@ class DynamixelMotorsBus:
|
||||
|
||||
def read_with_motor_ids(self, motor_models, motor_ids, data_name, num_retry=NUM_READ_RETRY):
|
||||
if self.mock:
|
||||
import tests.mock_dynamixel_sdk as dxl
|
||||
import tests.motors.mock_dynamixel_sdk as dxl
|
||||
else:
|
||||
import dynamixel_sdk as dxl
|
||||
|
||||
@@ -677,7 +691,7 @@ class DynamixelMotorsBus:
|
||||
start_time = time.perf_counter()
|
||||
|
||||
if self.mock:
|
||||
import tests.mock_dynamixel_sdk as dxl
|
||||
import tests.motors.mock_dynamixel_sdk as dxl
|
||||
else:
|
||||
import dynamixel_sdk as dxl
|
||||
|
||||
@@ -743,7 +757,7 @@ class DynamixelMotorsBus:
|
||||
|
||||
def write_with_motor_ids(self, motor_models, motor_ids, data_name, values, num_retry=NUM_WRITE_RETRY):
|
||||
if self.mock:
|
||||
import tests.mock_dynamixel_sdk as dxl
|
||||
import tests.motors.mock_dynamixel_sdk as dxl
|
||||
else:
|
||||
import dynamixel_sdk as dxl
|
||||
|
||||
@@ -779,7 +793,7 @@ class DynamixelMotorsBus:
|
||||
start_time = time.perf_counter()
|
||||
|
||||
if self.mock:
|
||||
import tests.mock_dynamixel_sdk as dxl
|
||||
import tests.motors.mock_dynamixel_sdk as dxl
|
||||
else:
|
||||
import dynamixel_sdk as dxl
|
||||
|
||||
|
||||
@@ -1,6 +1,18 @@
|
||||
# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
#
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
|
||||
import enum
|
||||
import logging
|
||||
import math
|
||||
import time
|
||||
import traceback
|
||||
from copy import deepcopy
|
||||
@@ -18,13 +30,6 @@ TIMEOUT_MS = 1000
|
||||
|
||||
MAX_ID_RANGE = 252
|
||||
|
||||
# The following bounds define the lower and upper joints range (after calibration).
|
||||
# For joints in degree (i.e. revolute joints), their nominal range is [-180, 180] degrees
|
||||
# which corresponds to a half rotation on the left and half rotation on the right.
|
||||
# Some joints might require higher range, so we allow up to [-270, 270] degrees until
|
||||
# an error is raised.
|
||||
LOWER_BOUND_DEGREE = -270
|
||||
UPPER_BOUND_DEGREE = 270
|
||||
# For joints in percentage (i.e. joints that move linearly like the prismatic joint of a gripper),
|
||||
# their nominal range is [0, 100] %. For instance, for Aloha gripper, 0% is fully
|
||||
# closed, and 100% is fully open. To account for slight calibration issue, we allow up to
|
||||
@@ -34,7 +39,6 @@ UPPER_BOUND_LINEAR = 110
|
||||
|
||||
HALF_TURN_DEGREE = 180
|
||||
|
||||
|
||||
# See this link for STS3215 Memory Table:
|
||||
# https://docs.google.com/spreadsheets/d/1GVs7W1VS1PqdhA1nW-abeyAHhTUxKUdR/edit?usp=sharing&ouid=116566590112741600240&rtpof=true&sd=true
|
||||
# data_name: (address, size_byte)
|
||||
@@ -100,8 +104,6 @@ SCS_SERIES_BAUDRATE_TABLE = {
|
||||
}
|
||||
|
||||
CALIBRATION_REQUIRED = ["Goal_Position", "Present_Position"]
|
||||
CONVERT_UINT32_TO_INT32_REQUIRED = ["Goal_Position", "Present_Position"]
|
||||
|
||||
|
||||
MODEL_CONTROL_TABLE = {
|
||||
"scs_series": SCS_SERIES_CONTROL_TABLE,
|
||||
@@ -123,15 +125,63 @@ NUM_READ_RETRY = 20
|
||||
NUM_WRITE_RETRY = 20
|
||||
|
||||
|
||||
def convert_degrees_to_steps(degrees: float | np.ndarray, models: str | list[str]) -> np.ndarray:
|
||||
"""This function converts the degree range to the step range for indicating motors rotation.
|
||||
It assumes a motor achieves a full rotation by going from -180 degree position to +180.
|
||||
The motor resolution (e.g. 4096) corresponds to the number of steps needed to achieve a full rotation.
|
||||
def convert_ticks_to_degrees(ticks, model):
|
||||
resolutions = MODEL_RESOLUTION[model]
|
||||
# Convert the ticks to degrees
|
||||
return ticks * (360.0 / resolutions)
|
||||
|
||||
|
||||
def convert_degrees_to_ticks(degrees, model):
|
||||
resolutions = MODEL_RESOLUTION[model]
|
||||
# Convert degrees to motor ticks
|
||||
return int(degrees * (resolutions / 360.0))
|
||||
|
||||
|
||||
def adjusted_to_homing_ticks(raw_motor_ticks: int, model: str, motorbus, motor_id: int) -> int:
|
||||
"""
|
||||
resolutions = [MODEL_RESOLUTION[model] for model in models]
|
||||
steps = degrees / 180 * np.array(resolutions) / 2
|
||||
steps = steps.astype(int)
|
||||
return steps
|
||||
Takes a raw reading [0..(res-1)] (e.g. 0..4095) and shifts it so that '2048'
|
||||
becomes 0 in the homed coordinate system ([-2048..+2047] for 4096 resolution).
|
||||
"""
|
||||
resolutions = MODEL_RESOLUTION[model]
|
||||
|
||||
# Shift raw ticks by half-resolution so 2048 -> 0, then wrap [0..res-1].
|
||||
ticks = (raw_motor_ticks - (resolutions // 2)) % resolutions
|
||||
|
||||
# If above halfway, fold it into negative territory => [-2048..+2047].
|
||||
if ticks > (resolutions // 2):
|
||||
ticks -= resolutions
|
||||
|
||||
# Flip sign if drive_mode is set.
|
||||
drive_mode = 0
|
||||
if motorbus.calibration is not None:
|
||||
drive_mode = motorbus.calibration["drive_mode"][motor_id - 1]
|
||||
|
||||
if drive_mode:
|
||||
ticks *= -1
|
||||
|
||||
return ticks
|
||||
|
||||
|
||||
def adjusted_to_motor_ticks(adjusted_pos: int, model: str, motorbus, motor_id: int) -> int:
|
||||
"""
|
||||
Inverse of adjusted_to_homing_ticks(). Takes a 'homed' position in [-2048..+2047]
|
||||
and recovers the raw [0..(res-1)] ticks with 2048 as midpoint.
|
||||
"""
|
||||
# Flip sign if drive_mode was set.
|
||||
drive_mode = 0
|
||||
if motorbus.calibration is not None:
|
||||
drive_mode = motorbus.calibration["drive_mode"][motor_id - 1]
|
||||
|
||||
if drive_mode:
|
||||
adjusted_pos *= -1
|
||||
|
||||
resolutions = MODEL_RESOLUTION[model]
|
||||
|
||||
# Shift by +half-resolution and wrap into [0..res-1].
|
||||
# This undoes the earlier shift by -half-resolution.
|
||||
ticks = (adjusted_pos + (resolutions // 2)) % resolutions
|
||||
|
||||
return ticks
|
||||
|
||||
|
||||
def convert_to_bytes(value, bytes, mock=False):
|
||||
@@ -290,8 +340,6 @@ class FeetechMotorsBus:
|
||||
self.group_writers = {}
|
||||
self.logs = {}
|
||||
|
||||
self.track_positions = {}
|
||||
|
||||
def connect(self):
|
||||
if self.is_connected:
|
||||
raise RobotDeviceAlreadyConnectedError(
|
||||
@@ -299,7 +347,7 @@ class FeetechMotorsBus:
|
||||
)
|
||||
|
||||
if self.mock:
|
||||
import tests.mock_scservo_sdk as scs
|
||||
import tests.motors.mock_scservo_sdk as scs
|
||||
else:
|
||||
import scservo_sdk as scs
|
||||
|
||||
@@ -323,7 +371,7 @@ class FeetechMotorsBus:
|
||||
|
||||
def reconnect(self):
|
||||
if self.mock:
|
||||
import tests.mock_scservo_sdk as scs
|
||||
import tests.motors.mock_scservo_sdk as scs
|
||||
else:
|
||||
import scservo_sdk as scs
|
||||
|
||||
@@ -388,33 +436,7 @@ class FeetechMotorsBus:
|
||||
def set_calibration(self, calibration: dict[str, list]):
|
||||
self.calibration = calibration
|
||||
|
||||
def apply_calibration_autocorrect(self, values: np.ndarray | list, motor_names: list[str] | None):
|
||||
"""This function apply the calibration, automatically detects out of range errors for motors values and attempt to correct.
|
||||
|
||||
For more info, see docstring of `apply_calibration` and `autocorrect_calibration`.
|
||||
"""
|
||||
try:
|
||||
values = self.apply_calibration(values, motor_names)
|
||||
except JointOutOfRangeError as e:
|
||||
print(e)
|
||||
self.autocorrect_calibration(values, motor_names)
|
||||
values = self.apply_calibration(values, motor_names)
|
||||
return values
|
||||
|
||||
def apply_calibration(self, values: np.ndarray | list, motor_names: list[str] | None):
|
||||
"""Convert from unsigned int32 joint position range [0, 2**32[ to the universal float32 nominal degree range ]-180.0, 180.0[ with
|
||||
a "zero position" at 0 degree.
|
||||
|
||||
Note: We say "nominal degree range" since the motors can take values outside this range. For instance, 190 degrees, if the motor
|
||||
rotate more than a half a turn from the zero position. However, most motors can't rotate more than 180 degrees and will stay in this range.
|
||||
|
||||
Joints values are original in [0, 2**32[ (unsigned int32). Each motor are expected to complete a full rotation
|
||||
when given a goal position that is + or - their resolution. For instance, feetech xl330-m077 have a resolution of 4096, and
|
||||
at any position in their original range, let's say the position 56734, they complete a full rotation clockwise by moving to 60830,
|
||||
or anticlockwise by moving to 52638. The position in the original range is arbitrary and might change a lot between each motor.
|
||||
To harmonize between motors of the same model, different robots, or even models of different brands, we propose to work
|
||||
in the centered nominal degree range ]-180, 180[.
|
||||
"""
|
||||
if motor_names is None:
|
||||
motor_names = self.motor_names
|
||||
|
||||
@@ -426,34 +448,11 @@ class FeetechMotorsBus:
|
||||
calib_mode = self.calibration["calib_mode"][calib_idx]
|
||||
|
||||
if CalibrationMode[calib_mode] == CalibrationMode.DEGREE:
|
||||
drive_mode = self.calibration["drive_mode"][calib_idx]
|
||||
homing_offset = self.calibration["homing_offset"][calib_idx]
|
||||
_, model = self.motors[name]
|
||||
resolution = self.model_resolution[model]
|
||||
motor_idx, model = self.motors[name]
|
||||
|
||||
# Update direction of rotation of the motor to match between leader and follower.
|
||||
# In fact, the motor of the leader for a given joint can be assembled in an
|
||||
# opposite direction in term of rotation than the motor of the follower on the same joint.
|
||||
if drive_mode:
|
||||
values[i] *= -1
|
||||
|
||||
# Convert from range [-2**31, 2**31[ to
|
||||
# nominal range ]-resolution, resolution[ (e.g. ]-2048, 2048[)
|
||||
values[i] += homing_offset
|
||||
|
||||
# Convert from range ]-resolution, resolution[ to
|
||||
# universal float32 centered degree range ]-180, 180[
|
||||
values[i] = values[i] / (resolution // 2) * HALF_TURN_DEGREE
|
||||
|
||||
if (values[i] < LOWER_BOUND_DEGREE) or (values[i] > UPPER_BOUND_DEGREE):
|
||||
raise JointOutOfRangeError(
|
||||
f"Wrong motor position range detected for {name}. "
|
||||
f"Expected to be in nominal range of [-{HALF_TURN_DEGREE}, {HALF_TURN_DEGREE}] degrees (a full rotation), "
|
||||
f"with a maximum range of [{LOWER_BOUND_DEGREE}, {UPPER_BOUND_DEGREE}] degrees to account for joints that can rotate a bit more, "
|
||||
f"but present value is {values[i]} degree. "
|
||||
"This might be due to a cable connection issue creating an artificial 360 degrees jump in motor values. "
|
||||
"You need to recalibrate by running: `python lerobot/scripts/control_robot.py calibrate`"
|
||||
)
|
||||
# Convert raw motor ticks to homed ticks, then convert the homed ticks to degrees
|
||||
values[i] = adjusted_to_homing_ticks(values[i], model, self, motor_idx)
|
||||
values[i] = convert_ticks_to_degrees(values[i], model)
|
||||
|
||||
elif CalibrationMode[calib_mode] == CalibrationMode.LINEAR:
|
||||
start_pos = self.calibration["start_pos"][calib_idx]
|
||||
@@ -475,103 +474,6 @@ class FeetechMotorsBus:
|
||||
|
||||
return values
|
||||
|
||||
def autocorrect_calibration(self, values: np.ndarray | list, motor_names: list[str] | None):
|
||||
"""This function automatically detects issues with values of motors after calibration, and correct for these issues.
|
||||
|
||||
Some motors might have values outside of expected maximum bounds after calibration.
|
||||
For instance, for a joint in degree, its value can be outside [-270, 270] degrees, which is totally unexpected given
|
||||
a nominal range of [-180, 180] degrees, which represents half a turn to the left or right starting from zero position.
|
||||
|
||||
Known issues:
|
||||
#1: Motor value randomly shifts of a full turn, caused by hardware/connection errors.
|
||||
#2: Motor internal homing offset is shifted of a full turn, caused by using default calibration (e.g Aloha).
|
||||
#3: motor internal homing offset is shifted of less or more than a full turn, caused by using default calibration
|
||||
or by human error during manual calibration.
|
||||
|
||||
Issues #1 and #2 can be solved by shifting the calibration homing offset by a full turn.
|
||||
Issue #3 will be visually detected by user and potentially captured by the safety feature `max_relative_target`,
|
||||
that will slow down the motor, raise an error asking to recalibrate. Manual recalibrating will solve the issue.
|
||||
|
||||
Note: A full turn corresponds to 360 degrees but also to 4096 steps for a motor resolution of 4096.
|
||||
"""
|
||||
if motor_names is None:
|
||||
motor_names = self.motor_names
|
||||
|
||||
# Convert from unsigned int32 original range [0, 2**32] to signed float32 range
|
||||
values = values.astype(np.float32)
|
||||
|
||||
for i, name in enumerate(motor_names):
|
||||
calib_idx = self.calibration["motor_names"].index(name)
|
||||
calib_mode = self.calibration["calib_mode"][calib_idx]
|
||||
|
||||
if CalibrationMode[calib_mode] == CalibrationMode.DEGREE:
|
||||
drive_mode = self.calibration["drive_mode"][calib_idx]
|
||||
homing_offset = self.calibration["homing_offset"][calib_idx]
|
||||
_, model = self.motors[name]
|
||||
resolution = self.model_resolution[model]
|
||||
|
||||
if drive_mode:
|
||||
values[i] *= -1
|
||||
|
||||
# Convert from initial range to range [-180, 180] degrees
|
||||
calib_val = (values[i] + homing_offset) / (resolution // 2) * HALF_TURN_DEGREE
|
||||
in_range = (calib_val > LOWER_BOUND_DEGREE) and (calib_val < UPPER_BOUND_DEGREE)
|
||||
|
||||
# Solve this inequality to find the factor to shift the range into [-180, 180] degrees
|
||||
# values[i] = (values[i] + homing_offset + resolution * factor) / (resolution // 2) * HALF_TURN_DEGREE
|
||||
# - HALF_TURN_DEGREE <= (values[i] + homing_offset + resolution * factor) / (resolution // 2) * HALF_TURN_DEGREE <= HALF_TURN_DEGREE
|
||||
# (- HALF_TURN_DEGREE / HALF_TURN_DEGREE * (resolution // 2) - values[i] - homing_offset) / resolution <= factor <= (HALF_TURN_DEGREE / 180 * (resolution // 2) - values[i] - homing_offset) / resolution
|
||||
low_factor = (
|
||||
-HALF_TURN_DEGREE / HALF_TURN_DEGREE * (resolution // 2) - values[i] - homing_offset
|
||||
) / resolution
|
||||
upp_factor = (
|
||||
HALF_TURN_DEGREE / HALF_TURN_DEGREE * (resolution // 2) - values[i] - homing_offset
|
||||
) / resolution
|
||||
|
||||
elif CalibrationMode[calib_mode] == CalibrationMode.LINEAR:
|
||||
start_pos = self.calibration["start_pos"][calib_idx]
|
||||
end_pos = self.calibration["end_pos"][calib_idx]
|
||||
|
||||
# Convert from initial range to range [0, 100] in %
|
||||
calib_val = (values[i] - start_pos) / (end_pos - start_pos) * 100
|
||||
in_range = (calib_val > LOWER_BOUND_LINEAR) and (calib_val < UPPER_BOUND_LINEAR)
|
||||
|
||||
# Solve this inequality to find the factor to shift the range into [0, 100] %
|
||||
# values[i] = (values[i] - start_pos + resolution * factor) / (end_pos + resolution * factor - start_pos - resolution * factor) * 100
|
||||
# values[i] = (values[i] - start_pos + resolution * factor) / (end_pos - start_pos) * 100
|
||||
# 0 <= (values[i] - start_pos + resolution * factor) / (end_pos - start_pos) * 100 <= 100
|
||||
# (start_pos - values[i]) / resolution <= factor <= (end_pos - values[i]) / resolution
|
||||
low_factor = (start_pos - values[i]) / resolution
|
||||
upp_factor = (end_pos - values[i]) / resolution
|
||||
|
||||
if not in_range:
|
||||
# Get first integer between the two bounds
|
||||
if low_factor < upp_factor:
|
||||
factor = math.ceil(low_factor)
|
||||
|
||||
if factor > upp_factor:
|
||||
raise ValueError(f"No integer found between bounds [{low_factor=}, {upp_factor=}]")
|
||||
else:
|
||||
factor = math.ceil(upp_factor)
|
||||
|
||||
if factor > low_factor:
|
||||
raise ValueError(f"No integer found between bounds [{low_factor=}, {upp_factor=}]")
|
||||
|
||||
if CalibrationMode[calib_mode] == CalibrationMode.DEGREE:
|
||||
out_of_range_str = f"{LOWER_BOUND_DEGREE} < {calib_val} < {UPPER_BOUND_DEGREE} degrees"
|
||||
in_range_str = f"{LOWER_BOUND_DEGREE} < {calib_val} < {UPPER_BOUND_DEGREE} degrees"
|
||||
elif CalibrationMode[calib_mode] == CalibrationMode.LINEAR:
|
||||
out_of_range_str = f"{LOWER_BOUND_LINEAR} < {calib_val} < {UPPER_BOUND_LINEAR} %"
|
||||
in_range_str = f"{LOWER_BOUND_LINEAR} < {calib_val} < {UPPER_BOUND_LINEAR} %"
|
||||
|
||||
logging.warning(
|
||||
f"Auto-correct calibration of motor '{name}' by shifting value by {abs(factor)} full turns, "
|
||||
f"from '{out_of_range_str}' to '{in_range_str}'."
|
||||
)
|
||||
|
||||
# A full turn corresponds to 360 degrees but also to 4096 steps for a motor resolution of 4096.
|
||||
self.calibration["homing_offset"][calib_idx] += resolution * factor
|
||||
|
||||
def revert_calibration(self, values: np.ndarray | list, motor_names: list[str] | None):
|
||||
"""Inverse of `apply_calibration`."""
|
||||
if motor_names is None:
|
||||
@@ -582,23 +484,11 @@ class FeetechMotorsBus:
|
||||
calib_mode = self.calibration["calib_mode"][calib_idx]
|
||||
|
||||
if CalibrationMode[calib_mode] == CalibrationMode.DEGREE:
|
||||
drive_mode = self.calibration["drive_mode"][calib_idx]
|
||||
homing_offset = self.calibration["homing_offset"][calib_idx]
|
||||
_, model = self.motors[name]
|
||||
resolution = self.model_resolution[model]
|
||||
motor_idx, model = self.motors[name]
|
||||
|
||||
# Convert from nominal 0-centered degree range [-180, 180] to
|
||||
# 0-centered resolution range (e.g. [-2048, 2048] for resolution=4096)
|
||||
values[i] = values[i] / HALF_TURN_DEGREE * (resolution // 2)
|
||||
|
||||
# Subtract the homing offsets to come back to actual motor range of values
|
||||
# which can be arbitrary.
|
||||
values[i] -= homing_offset
|
||||
|
||||
# Remove drive mode, which is the rotation direction of the motor, to come back to
|
||||
# actual motor rotation direction which can be arbitrary.
|
||||
if drive_mode:
|
||||
values[i] *= -1
|
||||
# Convert degrees to homed ticks, then convert the homed ticks to raw ticks
|
||||
values[i] = convert_degrees_to_ticks(values[i], model)
|
||||
values[i] = adjusted_to_motor_ticks(values[i], model, self, motor_idx)
|
||||
|
||||
elif CalibrationMode[calib_mode] == CalibrationMode.LINEAR:
|
||||
start_pos = self.calibration["start_pos"][calib_idx]
|
||||
@@ -611,46 +501,9 @@ class FeetechMotorsBus:
|
||||
values = np.round(values).astype(np.int32)
|
||||
return values
|
||||
|
||||
def avoid_rotation_reset(self, values, motor_names, data_name):
|
||||
if data_name not in self.track_positions:
|
||||
self.track_positions[data_name] = {
|
||||
"prev": [None] * len(self.motor_names),
|
||||
# Assume False at initialization
|
||||
"below_zero": [False] * len(self.motor_names),
|
||||
"above_max": [False] * len(self.motor_names),
|
||||
}
|
||||
|
||||
track = self.track_positions[data_name]
|
||||
|
||||
if motor_names is None:
|
||||
motor_names = self.motor_names
|
||||
|
||||
for i, name in enumerate(motor_names):
|
||||
idx = self.motor_names.index(name)
|
||||
|
||||
if track["prev"][idx] is None:
|
||||
track["prev"][idx] = values[i]
|
||||
continue
|
||||
|
||||
# Detect a full rotation occurred
|
||||
if abs(track["prev"][idx] - values[i]) > 2048:
|
||||
# Position went below 0 and got reset to 4095
|
||||
if track["prev"][idx] < values[i]:
|
||||
# So we set negative value by adding a full rotation
|
||||
values[i] -= 4096
|
||||
|
||||
# Position went above 4095 and got reset to 0
|
||||
elif track["prev"][idx] > values[i]:
|
||||
# So we add a full rotation
|
||||
values[i] += 4096
|
||||
|
||||
track["prev"][idx] = values[i]
|
||||
|
||||
return values
|
||||
|
||||
def read_with_motor_ids(self, motor_models, motor_ids, data_name, num_retry=NUM_READ_RETRY):
|
||||
if self.mock:
|
||||
import tests.mock_scservo_sdk as scs
|
||||
import tests.motors.mock_scservo_sdk as scs
|
||||
else:
|
||||
import scservo_sdk as scs
|
||||
|
||||
@@ -688,7 +541,7 @@ class FeetechMotorsBus:
|
||||
|
||||
def read(self, data_name, motor_names: str | list[str] | None = None):
|
||||
if self.mock:
|
||||
import tests.mock_scservo_sdk as scs
|
||||
import tests.motors.mock_scservo_sdk as scs
|
||||
else:
|
||||
import scservo_sdk as scs
|
||||
|
||||
@@ -721,7 +574,7 @@ class FeetechMotorsBus:
|
||||
self.port_handler.ser.reset_output_buffer()
|
||||
self.port_handler.ser.reset_input_buffer()
|
||||
|
||||
# create new group reader
|
||||
# Create new group reader
|
||||
self.group_readers[group_key] = scs.GroupSyncRead(
|
||||
self.port_handler, self.packet_handler, addr, bytes
|
||||
)
|
||||
@@ -746,15 +599,8 @@ class FeetechMotorsBus:
|
||||
|
||||
values = np.array(values)
|
||||
|
||||
# Convert to signed int to use range [-2048, 2048] for our motor positions.
|
||||
if data_name in CONVERT_UINT32_TO_INT32_REQUIRED:
|
||||
values = values.astype(np.int32)
|
||||
|
||||
if data_name in CALIBRATION_REQUIRED:
|
||||
values = self.avoid_rotation_reset(values, motor_names, data_name)
|
||||
|
||||
if data_name in CALIBRATION_REQUIRED and self.calibration is not None:
|
||||
values = self.apply_calibration_autocorrect(values, motor_names)
|
||||
values = self.apply_calibration(values, motor_names)
|
||||
|
||||
# log the number of seconds it took to read the data from the motors
|
||||
delta_ts_name = get_log_name("delta_timestamp_s", "read", data_name, motor_names)
|
||||
@@ -768,7 +614,7 @@ class FeetechMotorsBus:
|
||||
|
||||
def write_with_motor_ids(self, motor_models, motor_ids, data_name, values, num_retry=NUM_WRITE_RETRY):
|
||||
if self.mock:
|
||||
import tests.mock_scservo_sdk as scs
|
||||
import tests.motors.mock_scservo_sdk as scs
|
||||
else:
|
||||
import scservo_sdk as scs
|
||||
|
||||
@@ -804,7 +650,7 @@ class FeetechMotorsBus:
|
||||
start_time = time.perf_counter()
|
||||
|
||||
if self.mock:
|
||||
import tests.mock_scservo_sdk as scs
|
||||
import tests.motors.mock_scservo_sdk as scs
|
||||
else:
|
||||
import scservo_sdk as scs
|
||||
|
||||
|
||||
@@ -1,3 +1,17 @@
|
||||
# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
#
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
|
||||
from typing import Protocol
|
||||
|
||||
from lerobot.common.robot_devices.motors.configs import (
|
||||
|
||||
@@ -1,3 +1,17 @@
|
||||
# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
#
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
|
||||
import abc
|
||||
from dataclasses import dataclass, field
|
||||
from typing import Sequence
|
||||
|
||||
@@ -1,3 +1,17 @@
|
||||
# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
#
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
|
||||
"""Logic to calibrate a robot arm built with dynamixel motors"""
|
||||
# TODO(rcadene, aliberts): move this logic into the robot code when refactoring
|
||||
|
||||
|
||||
@@ -1,14 +1,21 @@
|
||||
"""Logic to calibrate a robot arm built with feetech motors"""
|
||||
# TODO(rcadene, aliberts): move this logic into the robot code when refactoring
|
||||
|
||||
import time
|
||||
|
||||
# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
#
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
import numpy as np
|
||||
|
||||
from lerobot.common.robot_devices.motors.feetech import (
|
||||
CalibrationMode,
|
||||
TorqueMode,
|
||||
convert_degrees_to_steps,
|
||||
)
|
||||
from lerobot.common.robot_devices.motors.utils import MotorsBus
|
||||
|
||||
@@ -16,469 +23,164 @@ URL_TEMPLATE = (
|
||||
"https://raw.githubusercontent.com/huggingface/lerobot/main/media/{robot}/{arm}_{position}.webp"
|
||||
)
|
||||
|
||||
# The following positions are provided in nominal degree range ]-180, +180[
|
||||
# For more info on these constants, see comments in the code where they get used.
|
||||
ZERO_POSITION_DEGREE = 0
|
||||
ROTATED_POSITION_DEGREE = 90
|
||||
|
||||
|
||||
def assert_drive_mode(drive_mode):
|
||||
# `drive_mode` is in [0,1] with 0 means original rotation direction for the motor, and 1 means inverted.
|
||||
if not np.all(np.isin(drive_mode, [0, 1])):
|
||||
raise ValueError(f"`drive_mode` contains values other than 0 or 1: ({drive_mode})")
|
||||
|
||||
|
||||
def apply_drive_mode(position, drive_mode):
|
||||
assert_drive_mode(drive_mode)
|
||||
# Convert `drive_mode` from [0, 1] with 0 indicates original rotation direction and 1 inverted,
|
||||
# to [-1, 1] with 1 indicates original rotation direction and -1 inverted.
|
||||
signed_drive_mode = -(drive_mode * 2 - 1)
|
||||
position *= signed_drive_mode
|
||||
return position
|
||||
|
||||
|
||||
def move_until_block(arm, motor_name, positive_direction=True, while_move_hook=None):
|
||||
count = 0
|
||||
while True:
|
||||
present_pos = arm.read("Present_Position", motor_name)
|
||||
if positive_direction:
|
||||
# Move +100 steps every time. Lower the steps to lower the speed at which the arm moves.
|
||||
arm.write("Goal_Position", present_pos + 100, motor_name)
|
||||
else:
|
||||
arm.write("Goal_Position", present_pos - 100, motor_name)
|
||||
|
||||
if while_move_hook is not None:
|
||||
while_move_hook()
|
||||
|
||||
present_pos = arm.read("Present_Position", motor_name).item()
|
||||
present_speed = arm.read("Present_Speed", motor_name).item()
|
||||
present_current = arm.read("Present_Current", motor_name).item()
|
||||
# present_load = arm.read("Present_Load", motor_name).item()
|
||||
# present_voltage = arm.read("Present_Voltage", motor_name).item()
|
||||
# present_temperature = arm.read("Present_Temperature", motor_name).item()
|
||||
|
||||
# print(f"{present_pos=}")
|
||||
# print(f"{present_speed=}")
|
||||
# print(f"{present_current=}")
|
||||
# print(f"{present_load=}")
|
||||
# print(f"{present_voltage=}")
|
||||
# print(f"{present_temperature=}")
|
||||
|
||||
if present_speed == 0 and present_current > 40:
|
||||
count += 1
|
||||
if count > 100 or present_current > 300:
|
||||
return present_pos
|
||||
else:
|
||||
count = 0
|
||||
|
||||
|
||||
def move_to_calibrate(
|
||||
arm,
|
||||
motor_name,
|
||||
invert_drive_mode=False,
|
||||
positive_first=True,
|
||||
in_between_move_hook=None,
|
||||
while_move_hook=None,
|
||||
):
|
||||
initial_pos = arm.read("Present_Position", motor_name)
|
||||
|
||||
if positive_first:
|
||||
p_present_pos = move_until_block(
|
||||
arm, motor_name, positive_direction=True, while_move_hook=while_move_hook
|
||||
)
|
||||
else:
|
||||
n_present_pos = move_until_block(
|
||||
arm, motor_name, positive_direction=False, while_move_hook=while_move_hook
|
||||
)
|
||||
|
||||
if in_between_move_hook is not None:
|
||||
in_between_move_hook()
|
||||
|
||||
if positive_first:
|
||||
n_present_pos = move_until_block(
|
||||
arm, motor_name, positive_direction=False, while_move_hook=while_move_hook
|
||||
)
|
||||
else:
|
||||
p_present_pos = move_until_block(
|
||||
arm, motor_name, positive_direction=True, while_move_hook=while_move_hook
|
||||
)
|
||||
|
||||
zero_pos = (n_present_pos + p_present_pos) / 2
|
||||
|
||||
calib_data = {
|
||||
"initial_pos": initial_pos,
|
||||
"homing_offset": zero_pos if invert_drive_mode else -zero_pos,
|
||||
"invert_drive_mode": invert_drive_mode,
|
||||
"drive_mode": -1 if invert_drive_mode else 0,
|
||||
"zero_pos": zero_pos,
|
||||
"start_pos": n_present_pos if invert_drive_mode else p_present_pos,
|
||||
"end_pos": p_present_pos if invert_drive_mode else n_present_pos,
|
||||
}
|
||||
return calib_data
|
||||
|
||||
|
||||
def apply_offset(calib, offset):
|
||||
calib["zero_pos"] += offset
|
||||
if calib["drive_mode"]:
|
||||
calib["homing_offset"] += offset
|
||||
else:
|
||||
calib["homing_offset"] -= offset
|
||||
return calib
|
||||
|
||||
|
||||
def run_arm_auto_calibration(arm: MotorsBus, robot_type: str, arm_name: str, arm_type: str):
|
||||
if robot_type == "so100":
|
||||
return run_arm_auto_calibration_so100(arm, robot_type, arm_name, arm_type)
|
||||
elif robot_type == "moss":
|
||||
return run_arm_auto_calibration_moss(arm, robot_type, arm_name, arm_type)
|
||||
else:
|
||||
raise ValueError(robot_type)
|
||||
|
||||
|
||||
def run_arm_auto_calibration_so100(arm: MotorsBus, robot_type: str, arm_name: str, arm_type: str):
|
||||
"""All the offsets and magic numbers are hand tuned, and are unique to SO-100 follower arms"""
|
||||
def disable_torque(arm: MotorsBus):
|
||||
if (arm.read("Torque_Enable") != TorqueMode.DISABLED.value).any():
|
||||
raise ValueError("To run calibration, the torque must be disabled on all motors.")
|
||||
|
||||
if not (robot_type == "so100" and arm_type == "follower"):
|
||||
raise NotImplementedError("Auto calibration only supports the follower of so100 arms for now.")
|
||||
|
||||
print(f"\nRunning calibration of {robot_type} {arm_name} {arm_type}...")
|
||||
def get_calibration_modes(arm: MotorsBus):
|
||||
"""Returns calibration modes for each motor (DEGREE for rotational, LINEAR for gripper)."""
|
||||
return [
|
||||
CalibrationMode.LINEAR.name if name == "gripper" else CalibrationMode.DEGREE.name
|
||||
for name in arm.motor_names
|
||||
]
|
||||
|
||||
print("\nMove arm to initial position")
|
||||
print("See: " + URL_TEMPLATE.format(robot=robot_type, arm=arm_type, position="initial"))
|
||||
input("Press Enter to continue...")
|
||||
|
||||
# Lower the acceleration of the motors (in [0,254])
|
||||
initial_acceleration = arm.read("Acceleration")
|
||||
arm.write("Lock", 0)
|
||||
arm.write("Acceleration", 10)
|
||||
time.sleep(1)
|
||||
def reset_offset(motor_id, motor_bus):
|
||||
# Open the write lock, changes to EEPROM do NOT persist yet
|
||||
motor_bus.write("Lock", 1)
|
||||
|
||||
arm.write("Torque_Enable", TorqueMode.ENABLED.value)
|
||||
# Set offset to 0
|
||||
motor_name = motor_bus.motor_names[motor_id - 1]
|
||||
motor_bus.write("Offset", 0, motor_names=[motor_name])
|
||||
|
||||
print(f'{arm.read("Present_Position", "elbow_flex")=}')
|
||||
# Close the write lock, changes to EEPROM do persist
|
||||
motor_bus.write("Lock", 0)
|
||||
|
||||
calib = {}
|
||||
# Confirm that the offset is zero by reading it back
|
||||
confirmed_offset = motor_bus.read("Offset")[motor_id - 1]
|
||||
print(f"Offset for motor {motor_id} reset to: {confirmed_offset}")
|
||||
return confirmed_offset
|
||||
|
||||
init_wf_pos = arm.read("Present_Position", "wrist_flex")
|
||||
init_sl_pos = arm.read("Present_Position", "shoulder_lift")
|
||||
init_ef_pos = arm.read("Present_Position", "elbow_flex")
|
||||
arm.write("Goal_Position", init_wf_pos - 800, "wrist_flex")
|
||||
arm.write("Goal_Position", init_sl_pos + 150 + 1024, "shoulder_lift")
|
||||
arm.write("Goal_Position", init_ef_pos - 2048, "elbow_flex")
|
||||
time.sleep(2)
|
||||
|
||||
print("Calibrate shoulder_pan")
|
||||
calib["shoulder_pan"] = move_to_calibrate(arm, "shoulder_pan")
|
||||
arm.write("Goal_Position", calib["shoulder_pan"]["zero_pos"], "shoulder_pan")
|
||||
time.sleep(1)
|
||||
def calibrate_homing_motor(motor_id, motor_bus):
|
||||
reset_offset(motor_id, motor_bus)
|
||||
|
||||
print("Calibrate gripper")
|
||||
calib["gripper"] = move_to_calibrate(arm, "gripper", invert_drive_mode=True)
|
||||
time.sleep(1)
|
||||
home_ticks = motor_bus.read("Present_Position")[motor_id - 1] # Read index starts at 0
|
||||
print(f"Encoder offset (present position in homing position): {home_ticks}")
|
||||
|
||||
print("Calibrate wrist_flex")
|
||||
calib["wrist_flex"] = move_to_calibrate(arm, "wrist_flex")
|
||||
calib["wrist_flex"] = apply_offset(calib["wrist_flex"], offset=80)
|
||||
return home_ticks
|
||||
|
||||
def in_between_move_hook():
|
||||
nonlocal arm, calib
|
||||
time.sleep(2)
|
||||
ef_pos = arm.read("Present_Position", "elbow_flex")
|
||||
sl_pos = arm.read("Present_Position", "shoulder_lift")
|
||||
arm.write("Goal_Position", ef_pos + 1024, "elbow_flex")
|
||||
arm.write("Goal_Position", sl_pos - 1024, "shoulder_lift")
|
||||
time.sleep(2)
|
||||
|
||||
print("Calibrate elbow_flex")
|
||||
calib["elbow_flex"] = move_to_calibrate(
|
||||
arm, "elbow_flex", positive_first=False, in_between_move_hook=in_between_move_hook
|
||||
)
|
||||
calib["elbow_flex"] = apply_offset(calib["elbow_flex"], offset=80 - 1024)
|
||||
def calibrate_linear_motor(motor_id, motor_bus):
|
||||
motor_names = motor_bus.motor_names
|
||||
motor_name = motor_names[motor_id - 1]
|
||||
|
||||
arm.write("Goal_Position", calib["elbow_flex"]["zero_pos"] + 1024 + 512, "elbow_flex")
|
||||
time.sleep(1)
|
||||
reset_offset(motor_id, motor_bus)
|
||||
|
||||
def in_between_move_hook():
|
||||
nonlocal arm, calib
|
||||
arm.write("Goal_Position", calib["elbow_flex"]["zero_pos"], "elbow_flex")
|
||||
input(f"Close the {motor_name}, then press Enter...")
|
||||
start_pos = motor_bus.read("Present_Position")[motor_id - 1] # Read index starts ar 0
|
||||
print(f" [Motor {motor_id}] start position recorded: {start_pos}")
|
||||
|
||||
print("Calibrate shoulder_lift")
|
||||
calib["shoulder_lift"] = move_to_calibrate(
|
||||
arm,
|
||||
"shoulder_lift",
|
||||
invert_drive_mode=True,
|
||||
positive_first=False,
|
||||
in_between_move_hook=in_between_move_hook,
|
||||
)
|
||||
# add an 30 steps as offset to align with body
|
||||
calib["shoulder_lift"] = apply_offset(calib["shoulder_lift"], offset=1024 - 50)
|
||||
input(f"Open the {motor_name} fully, then press Enter...")
|
||||
end_pos = motor_bus.read("Present_Position")[motor_id - 1] # Read index starts ar 0
|
||||
print(f" [Motor {motor_id}] end position recorded: {end_pos}")
|
||||
|
||||
def while_move_hook():
|
||||
nonlocal arm, calib
|
||||
positions = {
|
||||
"shoulder_lift": round(calib["shoulder_lift"]["zero_pos"] - 1600),
|
||||
"elbow_flex": round(calib["elbow_flex"]["zero_pos"] + 1700),
|
||||
"wrist_flex": round(calib["wrist_flex"]["zero_pos"] + 800),
|
||||
"gripper": round(calib["gripper"]["end_pos"]),
|
||||
}
|
||||
arm.write("Goal_Position", list(positions.values()), list(positions.keys()))
|
||||
return start_pos, end_pos
|
||||
|
||||
arm.write("Goal_Position", round(calib["shoulder_lift"]["zero_pos"] - 1600), "shoulder_lift")
|
||||
time.sleep(2)
|
||||
arm.write("Goal_Position", round(calib["elbow_flex"]["zero_pos"] + 1700), "elbow_flex")
|
||||
time.sleep(2)
|
||||
arm.write("Goal_Position", round(calib["wrist_flex"]["zero_pos"] + 800), "wrist_flex")
|
||||
time.sleep(2)
|
||||
arm.write("Goal_Position", round(calib["gripper"]["end_pos"]), "gripper")
|
||||
time.sleep(2)
|
||||
|
||||
print("Calibrate wrist_roll")
|
||||
calib["wrist_roll"] = move_to_calibrate(
|
||||
arm, "wrist_roll", invert_drive_mode=True, positive_first=False, while_move_hook=while_move_hook
|
||||
)
|
||||
def single_motor_calibration(arm: MotorsBus, motor_id: int):
|
||||
"""Calibrates a single motor and returns its calibration data for updating the calibration file."""
|
||||
|
||||
arm.write("Goal_Position", calib["wrist_roll"]["zero_pos"], "wrist_roll")
|
||||
time.sleep(1)
|
||||
arm.write("Goal_Position", calib["gripper"]["start_pos"], "gripper")
|
||||
time.sleep(1)
|
||||
arm.write("Goal_Position", calib["wrist_flex"]["zero_pos"], "wrist_flex")
|
||||
time.sleep(1)
|
||||
arm.write("Goal_Position", calib["elbow_flex"]["zero_pos"] + 2048, "elbow_flex")
|
||||
arm.write("Goal_Position", calib["shoulder_lift"]["zero_pos"] - 2048, "shoulder_lift")
|
||||
time.sleep(1)
|
||||
arm.write("Goal_Position", calib["shoulder_pan"]["zero_pos"], "shoulder_pan")
|
||||
time.sleep(1)
|
||||
disable_torque(arm)
|
||||
print(f"\n--- Calibrating Motor {motor_id} ---")
|
||||
|
||||
calib_modes = []
|
||||
for name in arm.motor_names:
|
||||
if name == "gripper":
|
||||
calib_modes.append(CalibrationMode.LINEAR.name)
|
||||
else:
|
||||
calib_modes.append(CalibrationMode.DEGREE.name)
|
||||
start_pos = 0
|
||||
end_pos = 0
|
||||
encoder_offset = 0
|
||||
|
||||
if motor_id == 6:
|
||||
start_pos, end_pos = calibrate_linear_motor(motor_id, arm)
|
||||
else:
|
||||
input("Move the motor to (zero) position, then press Enter...")
|
||||
encoder_offset = calibrate_homing_motor(motor_id, arm)
|
||||
|
||||
print(f"Calibration for motor ID:{motor_id} done.")
|
||||
|
||||
# Create a calibration dictionary for the single motor
|
||||
calib_dict = {
|
||||
"homing_offset": [calib[name]["homing_offset"] for name in arm.motor_names],
|
||||
"drive_mode": [calib[name]["drive_mode"] for name in arm.motor_names],
|
||||
"start_pos": [calib[name]["start_pos"] for name in arm.motor_names],
|
||||
"end_pos": [calib[name]["end_pos"] for name in arm.motor_names],
|
||||
"calib_mode": calib_modes,
|
||||
"motor_names": arm.motor_names,
|
||||
"homing_offset": int(encoder_offset),
|
||||
"drive_mode": 0,
|
||||
"start_pos": int(start_pos),
|
||||
"end_pos": int(end_pos),
|
||||
"calib_mode": get_calibration_modes(arm)[motor_id - 1],
|
||||
"motor_name": arm.motor_names[motor_id - 1],
|
||||
}
|
||||
|
||||
# Re-enable original accerlation
|
||||
arm.write("Lock", 0)
|
||||
arm.write("Acceleration", initial_acceleration)
|
||||
time.sleep(1)
|
||||
|
||||
return calib_dict
|
||||
|
||||
|
||||
def run_arm_auto_calibration_moss(arm: MotorsBus, robot_type: str, arm_name: str, arm_type: str):
|
||||
"""All the offsets and magic numbers are hand tuned, and are unique to SO-100 follower arms"""
|
||||
if (arm.read("Torque_Enable") != TorqueMode.DISABLED.value).any():
|
||||
raise ValueError("To run calibration, the torque must be disabled on all motors.")
|
||||
def run_full_arm_calibration(arm: MotorsBus, robot_type: str, arm_name: str, arm_type: str):
|
||||
"""
|
||||
Runs a full calibration process for all motors in a robotic arm.
|
||||
|
||||
if not (robot_type == "moss" and arm_type == "follower"):
|
||||
raise NotImplementedError("Auto calibration only supports the follower of moss arms for now.")
|
||||
This function calibrates each motor in the arm, determining encoder offsets and
|
||||
start/end positions for linear and rotational motors. The calibration data is then
|
||||
stored in a dictionary for later use.
|
||||
|
||||
print(f"\nRunning calibration of {robot_type} {arm_name} {arm_type}...")
|
||||
**Calibration Process:**
|
||||
- The user is prompted to move the arm to its homing position before starting.
|
||||
- Motors with rotational motion are calibrated using a homing method.
|
||||
- Linear actuators (e.g., grippers) are calibrated separately.
|
||||
- Encoder offsets, start positions, and end positions are recorded.
|
||||
|
||||
print("\nMove arm to initial position")
|
||||
print("See: " + URL_TEMPLATE.format(robot=robot_type, arm=arm_type, position="initial"))
|
||||
input("Press Enter to continue...")
|
||||
|
||||
# Lower the acceleration of the motors (in [0,254])
|
||||
initial_acceleration = arm.read("Acceleration")
|
||||
arm.write("Lock", 0)
|
||||
arm.write("Acceleration", 10)
|
||||
time.sleep(1)
|
||||
|
||||
arm.write("Torque_Enable", TorqueMode.ENABLED.value)
|
||||
|
||||
sl_pos = arm.read("Present_Position", "shoulder_lift")
|
||||
arm.write("Goal_Position", sl_pos - 1024 - 450, "shoulder_lift")
|
||||
ef_pos = arm.read("Present_Position", "elbow_flex")
|
||||
arm.write("Goal_Position", ef_pos + 1024 + 450, "elbow_flex")
|
||||
time.sleep(2)
|
||||
|
||||
calib = {}
|
||||
|
||||
print("Calibrate shoulder_pan")
|
||||
calib["shoulder_pan"] = move_to_calibrate(arm, "shoulder_pan")
|
||||
arm.write("Goal_Position", calib["shoulder_pan"]["zero_pos"], "shoulder_pan")
|
||||
time.sleep(1)
|
||||
|
||||
print("Calibrate gripper")
|
||||
calib["gripper"] = move_to_calibrate(arm, "gripper", invert_drive_mode=True)
|
||||
time.sleep(1)
|
||||
|
||||
print("Calibrate wrist_flex")
|
||||
calib["wrist_flex"] = move_to_calibrate(arm, "wrist_flex", invert_drive_mode=True)
|
||||
calib["wrist_flex"] = apply_offset(calib["wrist_flex"], offset=-210 + 1024)
|
||||
|
||||
wr_pos = arm.read("Present_Position", "wrist_roll")
|
||||
arm.write("Goal_Position", calib["wrist_flex"]["zero_pos"] - 1024, "wrist_flex")
|
||||
time.sleep(1)
|
||||
arm.write("Goal_Position", wr_pos - 1024, "wrist_roll")
|
||||
time.sleep(1)
|
||||
arm.write("Goal_Position", calib["wrist_flex"]["zero_pos"] - 2048, "wrist_flex")
|
||||
time.sleep(1)
|
||||
arm.write("Goal_Position", calib["gripper"]["end_pos"], "gripper")
|
||||
time.sleep(1)
|
||||
|
||||
print("Calibrate wrist_roll")
|
||||
calib["wrist_roll"] = move_to_calibrate(arm, "wrist_roll", invert_drive_mode=True)
|
||||
calib["wrist_roll"] = apply_offset(calib["wrist_roll"], offset=790)
|
||||
|
||||
arm.write("Goal_Position", calib["wrist_roll"]["zero_pos"] - 1024, "wrist_roll")
|
||||
arm.write("Goal_Position", calib["gripper"]["start_pos"], "gripper")
|
||||
arm.write("Goal_Position", calib["wrist_flex"]["zero_pos"] - 1024, "wrist_flex")
|
||||
time.sleep(1)
|
||||
arm.write("Goal_Position", calib["wrist_roll"]["zero_pos"], "wrist_roll")
|
||||
arm.write("Goal_Position", calib["wrist_flex"]["zero_pos"] - 2048, "wrist_flex")
|
||||
|
||||
def in_between_move_elbow_flex_hook():
|
||||
nonlocal arm, calib
|
||||
arm.write("Goal_Position", calib["wrist_flex"]["zero_pos"], "wrist_flex")
|
||||
|
||||
print("Calibrate elbow_flex")
|
||||
calib["elbow_flex"] = move_to_calibrate(
|
||||
arm,
|
||||
"elbow_flex",
|
||||
invert_drive_mode=True,
|
||||
in_between_move_hook=in_between_move_elbow_flex_hook,
|
||||
)
|
||||
arm.write("Goal_Position", calib["wrist_flex"]["zero_pos"] - 1024, "wrist_flex")
|
||||
|
||||
def in_between_move_shoulder_lift_hook():
|
||||
nonlocal arm, calib
|
||||
sl = arm.read("Present_Position", "shoulder_lift")
|
||||
arm.write("Goal_Position", sl - 1500, "shoulder_lift")
|
||||
time.sleep(1)
|
||||
arm.write("Goal_Position", calib["elbow_flex"]["zero_pos"] + 1536, "elbow_flex")
|
||||
time.sleep(1)
|
||||
arm.write("Goal_Position", calib["wrist_flex"]["start_pos"], "wrist_flex")
|
||||
time.sleep(1)
|
||||
|
||||
print("Calibrate shoulder_lift")
|
||||
calib["shoulder_lift"] = move_to_calibrate(
|
||||
arm, "shoulder_lift", in_between_move_hook=in_between_move_shoulder_lift_hook
|
||||
)
|
||||
calib["shoulder_lift"] = apply_offset(calib["shoulder_lift"], offset=-1024)
|
||||
|
||||
arm.write("Goal_Position", calib["wrist_flex"]["zero_pos"] - 1024, "wrist_flex")
|
||||
time.sleep(1)
|
||||
arm.write("Goal_Position", calib["shoulder_lift"]["zero_pos"] + 2048, "shoulder_lift")
|
||||
arm.write("Goal_Position", calib["elbow_flex"]["zero_pos"] - 1024 - 400, "elbow_flex")
|
||||
time.sleep(2)
|
||||
|
||||
calib_modes = []
|
||||
for name in arm.motor_names:
|
||||
if name == "gripper":
|
||||
calib_modes.append(CalibrationMode.LINEAR.name)
|
||||
else:
|
||||
calib_modes.append(CalibrationMode.DEGREE.name)
|
||||
|
||||
calib_dict = {
|
||||
"homing_offset": [calib[name]["homing_offset"] for name in arm.motor_names],
|
||||
"drive_mode": [calib[name]["drive_mode"] for name in arm.motor_names],
|
||||
"start_pos": [calib[name]["start_pos"] for name in arm.motor_names],
|
||||
"end_pos": [calib[name]["end_pos"] for name in arm.motor_names],
|
||||
"calib_mode": calib_modes,
|
||||
"motor_names": arm.motor_names,
|
||||
}
|
||||
|
||||
# Re-enable original accerlation
|
||||
arm.write("Lock", 0)
|
||||
arm.write("Acceleration", initial_acceleration)
|
||||
time.sleep(1)
|
||||
|
||||
return calib_dict
|
||||
|
||||
|
||||
def run_arm_manual_calibration(arm: MotorsBus, robot_type: str, arm_name: str, arm_type: str):
|
||||
"""This function ensures that a neural network trained on data collected on a given robot
|
||||
can work on another robot. For instance before calibration, setting a same goal position
|
||||
for each motor of two different robots will get two very different positions. But after calibration,
|
||||
the two robots will move to the same position.To this end, this function computes the homing offset
|
||||
and the drive mode for each motor of a given robot.
|
||||
|
||||
Homing offset is used to shift the motor position to a ]-2048, +2048[ nominal range (when the motor uses 2048 steps
|
||||
to complete a half a turn). This range is set around an arbitrary "zero position" corresponding to all motor positions
|
||||
being 0. During the calibration process, you will need to manually move the robot to this "zero position".
|
||||
|
||||
Drive mode is used to invert the rotation direction of the motor. This is useful when some motors have been assembled
|
||||
in the opposite orientation for some robots. During the calibration process, you will need to manually move the robot
|
||||
to the "rotated position".
|
||||
|
||||
After calibration, the homing offsets and drive modes are stored in a cache.
|
||||
|
||||
Example of usage:
|
||||
**Example Usage:**
|
||||
```python
|
||||
run_arm_calibration(arm, "so100", "left", "follower")
|
||||
run_full_arm_calibration(arm, "so100", "left", "follower")
|
||||
```
|
||||
"""
|
||||
if (arm.read("Torque_Enable") != TorqueMode.DISABLED.value).any():
|
||||
raise ValueError("To run calibration, the torque must be disabled on all motors.")
|
||||
disable_torque(arm)
|
||||
|
||||
print(f"\nRunning calibration of {robot_type} {arm_name} {arm_type}...")
|
||||
|
||||
print("\nMove arm to zero position")
|
||||
print("See: " + URL_TEMPLATE.format(robot=robot_type, arm=arm_type, position="zero"))
|
||||
print("\nMove arm to homing position (middle)")
|
||||
print(
|
||||
"See: " + URL_TEMPLATE.format(robot=robot_type, arm=arm_type, position="zero")
|
||||
) # TODO(pepijn): replace with new instruction homing pos (all motors in middle) in tutorial
|
||||
input("Press Enter to continue...")
|
||||
|
||||
# We arbitrarily chose our zero target position to be a straight horizontal position with gripper upwards and closed.
|
||||
# It is easy to identify and all motors are in a "quarter turn" position. Once calibration is done, this position will
|
||||
# correspond to every motor angle being 0. If you set all 0 as Goal Position, the arm will move in this position.
|
||||
zero_target_pos = convert_degrees_to_steps(ZERO_POSITION_DEGREE, arm.motor_models)
|
||||
start_positions = np.zeros(len(arm.motor_indices))
|
||||
end_positions = np.zeros(len(arm.motor_indices))
|
||||
encoder_offsets = np.zeros(len(arm.motor_indices))
|
||||
|
||||
# Compute homing offset so that `present_position + homing_offset ~= target_position`.
|
||||
zero_pos = arm.read("Present_Position")
|
||||
homing_offset = zero_target_pos - zero_pos
|
||||
modes = get_calibration_modes(arm)
|
||||
|
||||
# The rotated target position corresponds to a rotation of a quarter turn from the zero position.
|
||||
# This allows to identify the rotation direction of each motor.
|
||||
# For instance, if the motor rotates 90 degree, and its value is -90 after applying the homing offset, then we know its rotation direction
|
||||
# is inverted. However, for the calibration being successful, we need everyone to follow the same target position.
|
||||
# Sometimes, there is only one possible rotation direction. For instance, if the gripper is closed, there is only one direction which
|
||||
# corresponds to opening the gripper. When the rotation direction is ambiguous, we arbitrarily rotate clockwise from the point of view
|
||||
# of the previous motor in the kinetic chain.
|
||||
print("\nMove arm to rotated target position")
|
||||
print("See: " + URL_TEMPLATE.format(robot=robot_type, arm=arm_type, position="rotated"))
|
||||
input("Press Enter to continue...")
|
||||
for i, motor_id in enumerate(arm.motor_indices):
|
||||
if modes[i] == CalibrationMode.DEGREE.name:
|
||||
encoder_offsets[i] = calibrate_homing_motor(motor_id, arm)
|
||||
start_positions[i] = 0
|
||||
end_positions[i] = 0
|
||||
|
||||
rotated_target_pos = convert_degrees_to_steps(ROTATED_POSITION_DEGREE, arm.motor_models)
|
||||
|
||||
# Find drive mode by rotating each motor by a quarter of a turn.
|
||||
# Drive mode indicates if the motor rotation direction should be inverted (=1) or not (=0).
|
||||
rotated_pos = arm.read("Present_Position")
|
||||
drive_mode = (rotated_pos < zero_pos).astype(np.int32)
|
||||
|
||||
# Re-compute homing offset to take into account drive mode
|
||||
rotated_drived_pos = apply_drive_mode(rotated_pos, drive_mode)
|
||||
homing_offset = rotated_target_pos - rotated_drived_pos
|
||||
for i, motor_id in enumerate(arm.motor_indices):
|
||||
if modes[i] == CalibrationMode.LINEAR.name:
|
||||
start_positions[i], end_positions[i] = calibrate_linear_motor(motor_id, arm)
|
||||
encoder_offsets[i] = 0
|
||||
|
||||
print("\nMove arm to rest position")
|
||||
print("See: " + URL_TEMPLATE.format(robot=robot_type, arm=arm_type, position="rest"))
|
||||
input("Press Enter to continue...")
|
||||
print()
|
||||
|
||||
# Joints with rotational motions are expressed in degrees in nominal range of [-180, 180]
|
||||
calib_modes = []
|
||||
for name in arm.motor_names:
|
||||
if name == "gripper":
|
||||
calib_modes.append(CalibrationMode.LINEAR.name)
|
||||
else:
|
||||
calib_modes.append(CalibrationMode.DEGREE.name)
|
||||
print(f"\n calibration of {robot_type} {arm_name} {arm_type} done!")
|
||||
|
||||
# Force drive_mode values (can be static)
|
||||
drive_modes = [0, 1, 0, 0, 1, 0]
|
||||
|
||||
calib_dict = {
|
||||
"homing_offset": homing_offset.tolist(),
|
||||
"drive_mode": drive_mode.tolist(),
|
||||
"start_pos": zero_pos.tolist(),
|
||||
"end_pos": rotated_pos.tolist(),
|
||||
"calib_mode": calib_modes,
|
||||
"homing_offset": encoder_offsets.astype(int).tolist(),
|
||||
"drive_mode": drive_modes,
|
||||
"start_pos": start_positions.astype(int).tolist(),
|
||||
"end_pos": end_positions.astype(int).tolist(),
|
||||
"calib_mode": get_calibration_modes(arm),
|
||||
"motor_names": arm.motor_names,
|
||||
}
|
||||
return calib_dict
|
||||
|
||||
|
||||
def run_full_auto_arm_calibration(arm: MotorsBus, robot_type: str, arm_name: str, arm_type: str):
|
||||
"""TODO(pepijn): Add this method later as extra
|
||||
Example of usage:
|
||||
```python
|
||||
run_full_auto_arm_calibration(arm, "so100", "left", "follower")
|
||||
```
|
||||
"""
|
||||
print(f"\nRunning calibration of {robot_type} {arm_name} {arm_type}...")
|
||||
|
||||
@@ -1,3 +1,17 @@
|
||||
# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
#
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
|
||||
import base64
|
||||
import json
|
||||
import threading
|
||||
|
||||
@@ -1,3 +1,17 @@
|
||||
# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
#
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
|
||||
"""Contains logic to instantiate a robot, read information from its motors and cameras,
|
||||
and send orders to its motors.
|
||||
"""
|
||||
@@ -40,6 +54,73 @@ def ensure_safe_goal_position(
|
||||
return safe_goal_pos
|
||||
|
||||
|
||||
def apply_feetech_offsets_from_calibration(motorsbus, calibration_dict: dict):
|
||||
"""
|
||||
Reads 'calibration_dict' containing 'homing_offset' and 'motor_names',
|
||||
then writes each motor's offset to the servo's internal Offset (0x1F) in EPROM.
|
||||
|
||||
This version is modified so each homed position (originally 0) will now read
|
||||
2047, i.e. 180° away from 0 in the 4096-count circle. Offsets are permanently
|
||||
stored in EEPROM, so the servo's Present_Position is hardware-shifted even
|
||||
after power cycling.
|
||||
|
||||
Steps:
|
||||
1) Subtract 2047 from the old offset (so 0 -> 2047).
|
||||
2) Clamp to [-2047..+2047].
|
||||
3) Encode sign bit and magnitude into a 12-bit number.
|
||||
"""
|
||||
|
||||
homing_offsets = calibration_dict["homing_offset"]
|
||||
motor_names = calibration_dict["motor_names"]
|
||||
start_pos = calibration_dict["start_pos"]
|
||||
|
||||
# Open the write lock, changes to EEPROM do NOT persist yet
|
||||
motorsbus.write("Lock", 1)
|
||||
|
||||
# For each motor, set the 'Offset' parameter
|
||||
for m_name, old_offset in zip(motor_names, homing_offsets, strict=False):
|
||||
# If bus doesn’t have a motor named m_name, skip
|
||||
if m_name not in motorsbus.motors:
|
||||
print(f"Warning: '{m_name}' not found in motorsbus.motors; skipping offset.")
|
||||
continue
|
||||
|
||||
if m_name == "gripper":
|
||||
old_offset = start_pos # If gripper set the offset to the start position of the gripper
|
||||
continue
|
||||
|
||||
# Shift the offset so the homed position reads 2047
|
||||
new_offset = old_offset - 2047
|
||||
|
||||
# Clamp to [-2047..+2047]
|
||||
if new_offset > 2047:
|
||||
new_offset = 2047
|
||||
print(
|
||||
f"Warning: '{new_offset}' is getting clamped because its larger then 2047; This should not happen!"
|
||||
)
|
||||
elif new_offset < -2047:
|
||||
new_offset = -2047
|
||||
print(
|
||||
f"Warning: '{new_offset}' is getting clamped because its smaller then -2047; This should not happen!"
|
||||
)
|
||||
|
||||
# Determine the direction (sign) bit and magnitude
|
||||
direction_bit = 1 if new_offset < 0 else 0
|
||||
magnitude = abs(new_offset)
|
||||
|
||||
# Combine sign bit (bit 11) with the magnitude (bits 0..10)
|
||||
servo_offset = (direction_bit << 11) | magnitude
|
||||
|
||||
# Write offset to servo
|
||||
motorsbus.write("Offset", servo_offset, motor_names=m_name)
|
||||
print(
|
||||
f"Set offset for {m_name}: "
|
||||
f"old_offset={old_offset}, new_offset={new_offset}, servo_encoded={magnitude} + direction={direction_bit}"
|
||||
)
|
||||
|
||||
motorsbus.write("Lock", 0)
|
||||
print("Offsets have been saved to EEPROM successfully.")
|
||||
|
||||
|
||||
class ManipulatorRobot:
|
||||
# TODO(rcadene): Implement force feedback
|
||||
"""This class allows to control any manipulator robot of various number of motors.
|
||||
@@ -301,10 +382,10 @@ class ManipulatorRobot:
|
||||
|
||||
elif self.robot_type in ["so100", "moss", "lekiwi"]:
|
||||
from lerobot.common.robot_devices.robots.feetech_calibration import (
|
||||
run_arm_manual_calibration,
|
||||
run_full_arm_calibration,
|
||||
)
|
||||
|
||||
calibration = run_arm_manual_calibration(arm, self.robot_type, name, arm_type)
|
||||
calibration = run_full_arm_calibration(arm, self.robot_type, name, arm_type)
|
||||
|
||||
print(f"Calibration is done! Saving calibration file '{arm_calib_path}'")
|
||||
arm_calib_path.parent.mkdir(parents=True, exist_ok=True)
|
||||
@@ -313,12 +394,24 @@ class ManipulatorRobot:
|
||||
|
||||
return calibration
|
||||
|
||||
for name, arm in self.follower_arms.items():
|
||||
calibration = load_or_run_calibration_(name, arm, "follower")
|
||||
arm.set_calibration(calibration)
|
||||
for name, arm in self.leader_arms.items():
|
||||
calibration = load_or_run_calibration_(name, arm, "leader")
|
||||
arm.set_calibration(calibration)
|
||||
# For each follower arm
|
||||
|
||||
for name, arm_bus in self.follower_arms.items():
|
||||
calibration = load_or_run_calibration_(name, arm_bus, "follower")
|
||||
arm_bus.set_calibration(calibration)
|
||||
|
||||
# If this is a Feetech robot, also set the servo offset into EEPROM
|
||||
if self.robot_type in ["so100", "lekiwi"]:
|
||||
apply_feetech_offsets_from_calibration(arm_bus, calibration)
|
||||
|
||||
# For each leader arm
|
||||
for name, arm_bus in self.leader_arms.items():
|
||||
calibration = load_or_run_calibration_(name, arm_bus, "leader")
|
||||
arm_bus.set_calibration(calibration)
|
||||
|
||||
# Optionally also set offset for leader if you want the servo offsets as well
|
||||
if self.robot_type in ["so100", "lekiwi"]:
|
||||
apply_feetech_offsets_from_calibration(arm_bus, calibration)
|
||||
|
||||
def set_koch_robot_preset(self):
|
||||
def set_operating_mode_(arm):
|
||||
|
||||
@@ -1,3 +1,17 @@
|
||||
# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
#
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
|
||||
import base64
|
||||
import json
|
||||
import os
|
||||
@@ -392,21 +406,19 @@ class MobileManipulator:
|
||||
for name in self.leader_arms:
|
||||
pos = self.leader_arms[name].read("Present_Position")
|
||||
pos_tensor = torch.from_numpy(pos).float()
|
||||
# Instead of pos_tensor.item(), use tolist() to convert the entire tensor to a list
|
||||
arm_positions.extend(pos_tensor.tolist())
|
||||
|
||||
# (The rest of your code for generating wheel commands remains unchanged)
|
||||
x_cmd = 0.0 # m/s forward/backward
|
||||
y_cmd = 0.0 # m/s lateral
|
||||
y_cmd = 0.0 # m/s forward/backward
|
||||
x_cmd = 0.0 # m/s lateral
|
||||
theta_cmd = 0.0 # deg/s rotation
|
||||
if self.pressed_keys["forward"]:
|
||||
x_cmd += xy_speed
|
||||
if self.pressed_keys["backward"]:
|
||||
x_cmd -= xy_speed
|
||||
if self.pressed_keys["left"]:
|
||||
y_cmd += xy_speed
|
||||
if self.pressed_keys["right"]:
|
||||
if self.pressed_keys["backward"]:
|
||||
y_cmd -= xy_speed
|
||||
if self.pressed_keys["left"]:
|
||||
x_cmd += xy_speed
|
||||
if self.pressed_keys["right"]:
|
||||
x_cmd -= xy_speed
|
||||
if self.pressed_keys["rotate_left"]:
|
||||
theta_cmd += theta_speed
|
||||
if self.pressed_keys["rotate_right"]:
|
||||
@@ -584,8 +596,8 @@ class MobileManipulator:
|
||||
# Create the body velocity vector [x, y, theta_rad].
|
||||
velocity_vector = np.array([x_cmd, y_cmd, theta_rad])
|
||||
|
||||
# Define the wheel mounting angles with a -90° offset.
|
||||
angles = np.radians(np.array([240, 120, 0]) - 90)
|
||||
# Define the wheel mounting angles (defined from y axis cw)
|
||||
angles = np.radians(np.array([300, 180, 60]))
|
||||
# Build the kinematic matrix: each row maps body velocities to a wheel’s linear speed.
|
||||
# The third column (base_radius) accounts for the effect of rotation.
|
||||
m = np.array([[np.cos(a), np.sin(a), base_radius] for a in angles])
|
||||
@@ -641,8 +653,8 @@ class MobileManipulator:
|
||||
# Compute each wheel’s linear speed (m/s) from its angular speed.
|
||||
wheel_linear_speeds = wheel_radps * wheel_radius
|
||||
|
||||
# Define the wheel mounting angles with a -90° offset.
|
||||
angles = np.radians(np.array([240, 120, 0]) - 90)
|
||||
# Define the wheel mounting angles (defined from y axis cw)
|
||||
angles = np.radians(np.array([300, 180, 60]))
|
||||
m = np.array([[np.cos(a), np.sin(a), base_radius] for a in angles])
|
||||
|
||||
# Solve the inverse kinematics: body_velocity = M⁻¹ · wheel_linear_speeds.
|
||||
|
||||
@@ -1,3 +1,17 @@
|
||||
# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
#
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
|
||||
from typing import Protocol
|
||||
|
||||
from lerobot.common.robot_devices.robots.configs import (
|
||||
|
||||
@@ -1,3 +1,17 @@
|
||||
# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
#
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
|
||||
import platform
|
||||
import time
|
||||
|
||||
|
||||
@@ -1,3 +1,17 @@
|
||||
# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
#
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
|
||||
from pathlib import Path
|
||||
from tempfile import TemporaryDirectory
|
||||
from typing import Any, Type, TypeVar
|
||||
|
||||
@@ -17,6 +17,7 @@ import logging
|
||||
import os
|
||||
import os.path as osp
|
||||
import platform
|
||||
import subprocess
|
||||
from copy import copy
|
||||
from datetime import datetime, timezone
|
||||
from pathlib import Path
|
||||
@@ -50,8 +51,10 @@ def auto_select_torch_device() -> torch.device:
|
||||
return torch.device("cpu")
|
||||
|
||||
|
||||
# TODO(Steven): Remove log. log shouldn't be an argument, this should be handled by the logger level
|
||||
def get_safe_torch_device(try_device: str, log: bool = False) -> torch.device:
|
||||
"""Given a string, return a torch.device with checks on whether the device is available."""
|
||||
try_device = str(try_device)
|
||||
match try_device:
|
||||
case "cuda":
|
||||
assert torch.cuda.is_available()
|
||||
@@ -84,6 +87,7 @@ def get_safe_dtype(dtype: torch.dtype, device: str | torch.device):
|
||||
|
||||
|
||||
def is_torch_device_available(try_device: str) -> bool:
|
||||
try_device = str(try_device) # Ensure try_device is a string
|
||||
if try_device == "cuda":
|
||||
return torch.cuda.is_available()
|
||||
elif try_device == "mps":
|
||||
@@ -91,7 +95,7 @@ def is_torch_device_available(try_device: str) -> bool:
|
||||
elif try_device == "cpu":
|
||||
return True
|
||||
else:
|
||||
raise ValueError(f"Unknown device '{try_device}.")
|
||||
raise ValueError(f"Unknown device {try_device}. Supported devices are: cuda, mps or cpu.")
|
||||
|
||||
|
||||
def is_amp_available(device: str):
|
||||
@@ -165,23 +169,31 @@ def capture_timestamp_utc():
|
||||
|
||||
|
||||
def say(text, blocking=False):
|
||||
# Check if mac, linux, or windows.
|
||||
if platform.system() == "Darwin":
|
||||
cmd = f'say "{text}"'
|
||||
if not blocking:
|
||||
cmd += " &"
|
||||
elif platform.system() == "Linux":
|
||||
cmd = f'spd-say "{text}"'
|
||||
if blocking:
|
||||
cmd += " --wait"
|
||||
elif platform.system() == "Windows":
|
||||
# TODO(rcadene): Make blocking option work for Windows
|
||||
cmd = (
|
||||
'PowerShell -Command "Add-Type -AssemblyName System.Speech; '
|
||||
f"(New-Object System.Speech.Synthesis.SpeechSynthesizer).Speak('{text}')\""
|
||||
)
|
||||
system = platform.system()
|
||||
|
||||
os.system(cmd)
|
||||
if system == "Darwin":
|
||||
cmd = ["say", text]
|
||||
|
||||
elif system == "Linux":
|
||||
cmd = ["spd-say", text]
|
||||
if blocking:
|
||||
cmd.append("--wait")
|
||||
|
||||
elif system == "Windows":
|
||||
cmd = [
|
||||
"PowerShell",
|
||||
"-Command",
|
||||
"Add-Type -AssemblyName System.Speech; "
|
||||
f"(New-Object System.Speech.Synthesis.SpeechSynthesizer).Speak('{text}')",
|
||||
]
|
||||
|
||||
else:
|
||||
raise RuntimeError("Unsupported operating system for text-to-speech.")
|
||||
|
||||
if blocking:
|
||||
subprocess.run(cmd, check=True)
|
||||
else:
|
||||
subprocess.Popen(cmd, creationflags=subprocess.CREATE_NO_WINDOW if system == "Windows" else 0)
|
||||
|
||||
|
||||
def log_say(text, play_sounds, blocking=False):
|
||||
|
||||
@@ -1,14 +1,26 @@
|
||||
# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
#
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
|
||||
import datetime as dt
|
||||
import logging
|
||||
from dataclasses import dataclass, field
|
||||
from pathlib import Path
|
||||
|
||||
from lerobot.common import envs, policies # noqa: F401
|
||||
from lerobot.common.utils.utils import auto_select_torch_device, is_amp_available, is_torch_device_available
|
||||
from lerobot.configs import parser
|
||||
from lerobot.configs.default import EvalConfig
|
||||
from lerobot.configs.policies import PreTrainedConfig
|
||||
from lerobot.configs.train import TrainPipelineConfig
|
||||
|
||||
|
||||
@dataclass
|
||||
@@ -21,11 +33,6 @@ class EvalPipelineConfig:
|
||||
policy: PreTrainedConfig | None = None
|
||||
output_dir: Path | None = None
|
||||
job_name: str | None = None
|
||||
# TODO(rcadene, aliberts): By default, use device and use_amp values from policy checkpoint.
|
||||
device: str | None = None # cuda | cpu | mps
|
||||
# `use_amp` determines whether to use Automatic Mixed Precision (AMP) for training and evaluation. With AMP,
|
||||
# automatic gradient scaling is used.
|
||||
use_amp: bool = False
|
||||
seed: int | None = 1000
|
||||
|
||||
def __post_init__(self):
|
||||
@@ -36,27 +43,6 @@ class EvalPipelineConfig:
|
||||
self.policy = PreTrainedConfig.from_pretrained(policy_path, cli_overrides=cli_overrides)
|
||||
self.policy.pretrained_path = policy_path
|
||||
|
||||
# When no device or use_amp are given, use the one from training config.
|
||||
if self.device is None or self.use_amp is None:
|
||||
train_cfg = TrainPipelineConfig.from_pretrained(policy_path)
|
||||
if self.device is None:
|
||||
self.device = train_cfg.device
|
||||
if self.use_amp is None:
|
||||
self.use_amp = train_cfg.use_amp
|
||||
|
||||
# Automatically switch to available device if necessary
|
||||
if not is_torch_device_available(self.device):
|
||||
auto_device = auto_select_torch_device()
|
||||
logging.warning(f"Device '{self.device}' is not available. Switching to '{auto_device}'.")
|
||||
self.device = auto_device
|
||||
|
||||
# Automatically deactivate AMP if necessary
|
||||
if self.use_amp and not is_amp_available(self.device):
|
||||
logging.warning(
|
||||
f"Automatic Mixed Precision (amp) is not available on device '{self.device}'. Deactivating AMP."
|
||||
)
|
||||
self.use_amp = False
|
||||
|
||||
else:
|
||||
logging.warning(
|
||||
"No pretrained path was provided, evaluated policy will be built from scratch (random weights)."
|
||||
@@ -73,11 +59,6 @@ class EvalPipelineConfig:
|
||||
eval_dir = f"{now:%Y-%m-%d}/{now:%H-%M-%S}_{self.job_name}"
|
||||
self.output_dir = Path("outputs/eval") / eval_dir
|
||||
|
||||
if self.device is None:
|
||||
raise ValueError("Set one of the following device: cuda, cpu or mps")
|
||||
elif self.device == "cuda" and self.use_amp is None:
|
||||
raise ValueError("Set 'use_amp' to True or False.")
|
||||
|
||||
@classmethod
|
||||
def __get_path_fields__(cls) -> list[str]:
|
||||
"""This enables the parser to load config from the policy using `--policy.path=local/dir`"""
|
||||
|
||||
@@ -1,4 +1,19 @@
|
||||
# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
#
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
import importlib
|
||||
import inspect
|
||||
import pkgutil
|
||||
import sys
|
||||
from argparse import ArgumentError
|
||||
from functools import wraps
|
||||
@@ -10,6 +25,7 @@ import draccus
|
||||
from lerobot.common.utils.utils import has_method
|
||||
|
||||
PATH_KEY = "path"
|
||||
PLUGIN_DISCOVERY_SUFFIX = "discover_packages_path"
|
||||
draccus.set_config_type("json")
|
||||
|
||||
|
||||
@@ -45,6 +61,86 @@ def parse_arg(arg_name: str, args: Sequence[str] | None = None) -> str | None:
|
||||
return None
|
||||
|
||||
|
||||
def parse_plugin_args(plugin_arg_suffix: str, args: Sequence[str]) -> dict:
|
||||
"""Parse plugin-related arguments from command-line arguments.
|
||||
|
||||
This function extracts arguments from command-line arguments that match a specified suffix pattern.
|
||||
It processes arguments in the format '--key=value' and returns them as a dictionary.
|
||||
|
||||
Args:
|
||||
plugin_arg_suffix (str): The suffix to identify plugin-related arguments.
|
||||
cli_args (Sequence[str]): A sequence of command-line arguments to parse.
|
||||
|
||||
Returns:
|
||||
dict: A dictionary containing the parsed plugin arguments where:
|
||||
- Keys are the argument names (with '--' prefix removed if present)
|
||||
- Values are the corresponding argument values
|
||||
|
||||
Example:
|
||||
>>> args = ['--env.discover_packages_path=my_package',
|
||||
... '--other_arg=value']
|
||||
>>> parse_plugin_args('discover_packages_path', args)
|
||||
{'env.discover_packages_path': 'my_package'}
|
||||
"""
|
||||
plugin_args = {}
|
||||
for arg in args:
|
||||
if "=" in arg and plugin_arg_suffix in arg:
|
||||
key, value = arg.split("=", 1)
|
||||
# Remove leading '--' if present
|
||||
if key.startswith("--"):
|
||||
key = key[2:]
|
||||
plugin_args[key] = value
|
||||
return plugin_args
|
||||
|
||||
|
||||
class PluginLoadError(Exception):
|
||||
"""Raised when a plugin fails to load."""
|
||||
|
||||
|
||||
def load_plugin(plugin_path: str) -> None:
|
||||
"""Load and initialize a plugin from a given Python package path.
|
||||
|
||||
This function attempts to load a plugin by importing its package and any submodules.
|
||||
Plugin registration is expected to happen during package initialization, i.e. when
|
||||
the package is imported the gym environment should be registered and the config classes
|
||||
registered with their parents using the `register_subclass` decorator.
|
||||
|
||||
Args:
|
||||
plugin_path (str): The Python package path to the plugin (e.g. "mypackage.plugins.myplugin")
|
||||
|
||||
Raises:
|
||||
PluginLoadError: If the plugin cannot be loaded due to import errors or if the package path is invalid.
|
||||
|
||||
Examples:
|
||||
>>> load_plugin("external_plugin.core") # Loads plugin from external package
|
||||
|
||||
Notes:
|
||||
- The plugin package should handle its own registration during import
|
||||
- All submodules in the plugin package will be imported
|
||||
- Implementation follows the plugin discovery pattern from Python packaging guidelines
|
||||
|
||||
See Also:
|
||||
https://packaging.python.org/en/latest/guides/creating-and-discovering-plugins/
|
||||
"""
|
||||
try:
|
||||
package_module = importlib.import_module(plugin_path, __package__)
|
||||
except (ImportError, ModuleNotFoundError) as e:
|
||||
raise PluginLoadError(
|
||||
f"Failed to load plugin '{plugin_path}'. Verify the path and installation: {str(e)}"
|
||||
) from e
|
||||
|
||||
def iter_namespace(ns_pkg):
|
||||
return pkgutil.iter_modules(ns_pkg.__path__, ns_pkg.__name__ + ".")
|
||||
|
||||
try:
|
||||
for _finder, pkg_name, _ispkg in iter_namespace(package_module):
|
||||
importlib.import_module(pkg_name)
|
||||
except ImportError as e:
|
||||
raise PluginLoadError(
|
||||
f"Failed to load plugin '{plugin_path}'. Verify the path and installation: {str(e)}"
|
||||
) from e
|
||||
|
||||
|
||||
def get_path_arg(field_name: str, args: Sequence[str] | None = None) -> str | None:
|
||||
return parse_arg(f"{field_name}.{PATH_KEY}", args)
|
||||
|
||||
@@ -92,10 +188,13 @@ def filter_path_args(fields_to_filter: str | list[str], args: Sequence[str] | No
|
||||
|
||||
def wrap(config_path: Path | None = None):
|
||||
"""
|
||||
HACK: Similar to draccus.wrap but does two additional things:
|
||||
HACK: Similar to draccus.wrap but does three additional things:
|
||||
- Will remove '.path' arguments from CLI in order to process them later on.
|
||||
- If a 'config_path' is passed and the main config class has a 'from_pretrained' method, will
|
||||
initialize it from there to allow to fetch configs from the hub directly
|
||||
- Will load plugins specified in the CLI arguments. These plugins will typically register
|
||||
their own subclasses of config classes, so that draccus can find the right class to instantiate
|
||||
from the CLI '.type' arguments
|
||||
"""
|
||||
|
||||
def wrapper_outer(fn):
|
||||
@@ -108,6 +207,14 @@ def wrap(config_path: Path | None = None):
|
||||
args = args[1:]
|
||||
else:
|
||||
cli_args = sys.argv[1:]
|
||||
plugin_args = parse_plugin_args(PLUGIN_DISCOVERY_SUFFIX, cli_args)
|
||||
for plugin_cli_arg, plugin_path in plugin_args.items():
|
||||
try:
|
||||
load_plugin(plugin_path)
|
||||
except PluginLoadError as e:
|
||||
# add the relevant CLI arg to the error message
|
||||
raise PluginLoadError(f"{e}\nFailed plugin CLI Arg: {plugin_cli_arg}") from e
|
||||
cli_args = filter_arg(plugin_cli_arg, cli_args)
|
||||
config_path_cli = parse_arg("config_path", cli_args)
|
||||
if has_method(argtype, "__get_path_fields__"):
|
||||
path_fields = argtype.__get_path_fields__()
|
||||
|
||||
@@ -1,4 +1,18 @@
|
||||
# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
#
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
import abc
|
||||
import logging
|
||||
import os
|
||||
from dataclasses import dataclass, field
|
||||
from pathlib import Path
|
||||
@@ -12,6 +26,7 @@ from huggingface_hub.errors import HfHubHTTPError
|
||||
from lerobot.common.optim.optimizers import OptimizerConfig
|
||||
from lerobot.common.optim.schedulers import LRSchedulerConfig
|
||||
from lerobot.common.utils.hub import HubMixin
|
||||
from lerobot.common.utils.utils import auto_select_torch_device, is_amp_available, is_torch_device_available
|
||||
from lerobot.configs.types import FeatureType, NormalizationMode, PolicyFeature
|
||||
|
||||
# Generic variable that is either PreTrainedConfig or a subclass thereof
|
||||
@@ -40,8 +55,24 @@ class PreTrainedConfig(draccus.ChoiceRegistry, HubMixin, abc.ABC):
|
||||
input_features: dict[str, PolicyFeature] = field(default_factory=dict)
|
||||
output_features: dict[str, PolicyFeature] = field(default_factory=dict)
|
||||
|
||||
device: str | None = None # cuda | cpu | mp
|
||||
# `use_amp` determines whether to use Automatic Mixed Precision (AMP) for training and evaluation. With AMP,
|
||||
# automatic gradient scaling is used.
|
||||
use_amp: bool = False
|
||||
|
||||
def __post_init__(self):
|
||||
self.pretrained_path = None
|
||||
if not self.device or not is_torch_device_available(self.device):
|
||||
auto_device = auto_select_torch_device()
|
||||
logging.warning(f"Device '{self.device}' is not available. Switching to '{auto_device}'.")
|
||||
self.device = auto_device.type
|
||||
|
||||
# Automatically deactivate AMP if necessary
|
||||
if self.use_amp and not is_amp_available(self.device):
|
||||
logging.warning(
|
||||
f"Automatic Mixed Precision (amp) is not available on device '{self.device}'. Deactivating AMP."
|
||||
)
|
||||
self.use_amp = False
|
||||
|
||||
@property
|
||||
def type(self) -> str:
|
||||
|
||||
@@ -1,5 +1,17 @@
|
||||
# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
#
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
import datetime as dt
|
||||
import logging
|
||||
import os
|
||||
from dataclasses import dataclass, field
|
||||
from pathlib import Path
|
||||
@@ -13,7 +25,6 @@ from lerobot.common import envs
|
||||
from lerobot.common.optim import OptimizerConfig
|
||||
from lerobot.common.optim.schedulers import LRSchedulerConfig
|
||||
from lerobot.common.utils.hub import HubMixin
|
||||
from lerobot.common.utils.utils import auto_select_torch_device, is_amp_available
|
||||
from lerobot.configs import parser
|
||||
from lerobot.configs.default import DatasetConfig, EvalConfig, WandBConfig
|
||||
from lerobot.configs.policies import PreTrainedConfig
|
||||
@@ -35,10 +46,6 @@ class TrainPipelineConfig(HubMixin):
|
||||
# Note that when resuming a run, the default behavior is to use the configuration from the checkpoint,
|
||||
# regardless of what's provided with the training command at the time of resumption.
|
||||
resume: bool = False
|
||||
device: str | None = None # cuda | cpu | mp
|
||||
# `use_amp` determines whether to use Automatic Mixed Precision (AMP) for training and evaluation. With AMP,
|
||||
# automatic gradient scaling is used.
|
||||
use_amp: bool = False
|
||||
# `seed` is used for training (eg: model initialization, dataset shuffling)
|
||||
# AND for the evaluation environments.
|
||||
seed: int | None = 1000
|
||||
@@ -61,18 +68,6 @@ class TrainPipelineConfig(HubMixin):
|
||||
self.checkpoint_path = None
|
||||
|
||||
def validate(self):
|
||||
if not self.device:
|
||||
logging.warning("No device specified, trying to infer device automatically")
|
||||
device = auto_select_torch_device()
|
||||
self.device = device.type
|
||||
|
||||
# Automatically deactivate AMP if necessary
|
||||
if self.use_amp and not is_amp_available(self.device):
|
||||
logging.warning(
|
||||
f"Automatic Mixed Precision (amp) is not available on device '{self.device}'. Deactivating AMP."
|
||||
)
|
||||
self.use_amp = False
|
||||
|
||||
# HACK: We parse again the cli args here to get the pretrained paths if there was some.
|
||||
policy_path = parser.get_path_arg("policy")
|
||||
if policy_path:
|
||||
|
||||
@@ -1,3 +1,16 @@
|
||||
# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
#
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
# Note: We subclass str so that serialization is straightforward
|
||||
# https://stackoverflow.com/questions/24481852/serialising-an-enum-member-to-json
|
||||
from dataclasses import dataclass
|
||||
|
||||
176
lerobot/scripts/calibration_visualization_so100.py
Normal file
@@ -0,0 +1,176 @@
|
||||
import argparse
|
||||
import json
|
||||
import time
|
||||
from pathlib import Path
|
||||
|
||||
from lerobot.common.robot_devices.motors.feetech import (
|
||||
FeetechMotorsBus,
|
||||
adjusted_to_homing_ticks,
|
||||
adjusted_to_motor_ticks,
|
||||
convert_degrees_to_ticks,
|
||||
convert_ticks_to_degrees,
|
||||
)
|
||||
from lerobot.common.robot_devices.robots.configs import So100RobotConfig
|
||||
from lerobot.common.robot_devices.robots.utils import make_robot_from_config
|
||||
|
||||
|
||||
def apply_feetech_offsets_from_calibration(motorsbus: FeetechMotorsBus, calibration_dict: dict):
|
||||
"""
|
||||
Reads 'calibration_dict' containing 'homing_offset' and 'motor_names',
|
||||
then writes each motor's offset to the servo's internal Offset (0x1F) in EPROM.
|
||||
|
||||
This version is modified so each homed position (originally 0) will now read
|
||||
2047, i.e. 180° away from 0 in the 4096-count circle. Offsets are permanently
|
||||
stored in EEPROM, so the servo's Present_Position is hardware-shifted even
|
||||
after power cycling.
|
||||
|
||||
Steps:
|
||||
1) Subtract 2047 from the old offset (so 0 -> 2047).
|
||||
2) Clamp to [-2047..+2047].
|
||||
3) Encode sign bit and magnitude into a 12-bit number.
|
||||
"""
|
||||
|
||||
homing_offsets = calibration_dict["homing_offset"]
|
||||
motor_names = calibration_dict["motor_names"]
|
||||
start_pos = calibration_dict["start_pos"]
|
||||
|
||||
# Open the write lock, changes to EEPROM do NOT persist yet
|
||||
motorsbus.write("Lock", 1)
|
||||
|
||||
# For each motor, set the 'Offset' parameter
|
||||
for m_name, old_offset in zip(motor_names, homing_offsets, strict=False):
|
||||
# If bus doesn’t have a motor named m_name, skip
|
||||
if m_name not in motorsbus.motors:
|
||||
print(f"Warning: '{m_name}' not found in motorsbus.motors; skipping offset.")
|
||||
continue
|
||||
|
||||
if m_name == "gripper":
|
||||
old_offset = start_pos # If gripper set the offset to the start position of the gripper
|
||||
continue
|
||||
|
||||
# Shift the offset so the homed position reads 2047
|
||||
new_offset = old_offset - 2047
|
||||
|
||||
# Clamp to [-2047..+2047]
|
||||
if new_offset > 2047:
|
||||
new_offset = 2047
|
||||
print(
|
||||
f"Warning: '{new_offset}' is getting clamped because its larger then 2047; This should not happen!"
|
||||
)
|
||||
elif new_offset < -2047:
|
||||
new_offset = -2047
|
||||
print(
|
||||
f"Warning: '{new_offset}' is getting clamped because its smaller then -2047; This should not happen!"
|
||||
)
|
||||
|
||||
# Determine the direction (sign) bit and magnitude
|
||||
direction_bit = 1 if new_offset < 0 else 0
|
||||
magnitude = abs(new_offset)
|
||||
|
||||
# Combine sign bit (bit 11) with the magnitude (bits 0..10)
|
||||
servo_offset = (direction_bit << 11) | magnitude
|
||||
|
||||
# Write offset to servo
|
||||
motorsbus.write("Offset", servo_offset, motor_names=m_name)
|
||||
print(
|
||||
f"Set offset for {m_name}: "
|
||||
f"old_offset={old_offset}, new_offset={new_offset}, servo_encoded={magnitude} + direction={direction_bit}"
|
||||
)
|
||||
|
||||
motorsbus.write("Lock", 0)
|
||||
print("Offsets have been saved to EEPROM successfully.")
|
||||
|
||||
|
||||
def debug_feetech_positions(cfg, arm_arg: str):
|
||||
"""
|
||||
Reads each joint’s (1) raw ticks, (2) homed ticks, (3) degrees, and (4) invert-adjusted ticks.
|
||||
:param arm_arg: One of "main_leader" or "main_follower".
|
||||
"""
|
||||
robot = make_robot_from_config(cfg)
|
||||
|
||||
# Parse which arm we want: 'main_leader' or 'main_follower'
|
||||
if arm_arg not in ("main_leader", "main_follower"):
|
||||
raise ValueError("Please specify --arm=main_leader or --arm=main_follower")
|
||||
|
||||
bus_config = robot.leader_arms["main"] if arm_arg == "main_leader" else robot.follower_arms["main"]
|
||||
bus = FeetechMotorsBus(bus_config)
|
||||
|
||||
# Load calibration if it exists
|
||||
calib_file = Path(robot.calibration_dir) / f"{arm_arg}.json"
|
||||
if calib_file.exists():
|
||||
with open(calib_file) as f:
|
||||
calibration_dict = json.load(f)
|
||||
bus.set_calibration(calibration_dict)
|
||||
print(f"Loaded calibration from {calib_file}")
|
||||
else:
|
||||
print(f"No calibration file found at {calib_file}, skipping calibration set.")
|
||||
|
||||
bus.connect()
|
||||
print(f"Connected to Feetech bus on port: {bus.port}")
|
||||
|
||||
# Apply offset to servo EEPROM so the servo’s Present_Position is hardware-shifted
|
||||
if calibration_dict is not None:
|
||||
print("Applying offsets from calibration object to servo EEPROM. Be careful—this is permanent!")
|
||||
apply_feetech_offsets_from_calibration(bus, calibration_dict)
|
||||
|
||||
# Disable torque on all motors so you can move them freely by hand
|
||||
bus.write("Torque_Enable", 0, motor_names=bus.motor_names)
|
||||
print("Torque disabled on all joints.")
|
||||
|
||||
try:
|
||||
print("\nPress Ctrl+C to quit.\n")
|
||||
while True:
|
||||
# Read *raw* positions (no calibration).
|
||||
raw_positions = bus.read_with_motor_ids(
|
||||
bus.motor_models, bus.motor_indices, data_name="Present_Position"
|
||||
)
|
||||
|
||||
# Read *already-homed* positions
|
||||
homed_positions = bus.read("Present_Position")
|
||||
|
||||
for i, name in enumerate(bus.motor_names):
|
||||
motor_idx, model = bus.motors[name]
|
||||
|
||||
raw_ticks = raw_positions[i] # 0..4095
|
||||
homed_val = homed_positions[i] # degrees or % if linear
|
||||
|
||||
# Manually compute "adjusted ticks" from raw ticks
|
||||
manual_adjusted = adjusted_to_homing_ticks(raw_ticks, model, bus, motor_idx)
|
||||
# Convert to degrees
|
||||
manual_degs = convert_ticks_to_degrees(manual_adjusted, model)
|
||||
|
||||
# Convert that deg back to ticks
|
||||
manual_ticks = convert_degrees_to_ticks(manual_degs, model)
|
||||
# Then invert them using offset & bus drive mode
|
||||
inv_ticks = adjusted_to_motor_ticks(manual_ticks, model, bus, motor_idx)
|
||||
|
||||
print(
|
||||
f"{name:15s} | "
|
||||
f"RAW={raw_ticks:4d} | "
|
||||
f"HOMED_FROM_READ={homed_val:7.2f} | "
|
||||
f"HOMED_TICKS={manual_adjusted:6d} | "
|
||||
f"MANUAL_ADJ_DEG={manual_degs:7.2f} | "
|
||||
f"MANUAL_ADJ_TICKS={manual_ticks:6d} | "
|
||||
f"INV_TICKS={inv_ticks:4d} "
|
||||
)
|
||||
print("----------------------------------------------------")
|
||||
time.sleep(0.25)
|
||||
except KeyboardInterrupt:
|
||||
pass
|
||||
finally:
|
||||
print("\nExiting. Disconnecting bus...")
|
||||
bus.disconnect()
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
parser = argparse.ArgumentParser(description="Debug Feetech positions.")
|
||||
parser.add_argument(
|
||||
"--arm",
|
||||
type=str,
|
||||
choices=["main_leader", "main_follower"],
|
||||
default="main_leader",
|
||||
help="Which arm to debug: 'main_leader' or 'main_follower'.",
|
||||
)
|
||||
args = parser.parse_args()
|
||||
cfg = So100RobotConfig()
|
||||
debug_feetech_positions(cfg, arm_arg=args.arm)
|
||||
@@ -1,3 +1,16 @@
|
||||
# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
#
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
"""
|
||||
This script configure a single motor at a time to a given ID and baudrate.
|
||||
|
||||
@@ -132,13 +145,12 @@ def configure_motor(port, brand, model, motor_idx_des, baudrate_des):
|
||||
# the motors. Note: this configuration is not in the official STS3215 Memory Table
|
||||
motor_bus.write("Lock", 0)
|
||||
motor_bus.write("Maximum_Acceleration", 254)
|
||||
|
||||
motor_bus.write("Goal_Position", 2048)
|
||||
time.sleep(4)
|
||||
print("Present Position", motor_bus.read("Present_Position"))
|
||||
|
||||
motor_bus.write("Max_Angle_Limit", 4095) # default 4095
|
||||
motor_bus.write("Min_Angle_Limit", 0) # default 0
|
||||
motor_bus.write("Offset", 0)
|
||||
time.sleep(4)
|
||||
motor_bus.write("Mode", 0)
|
||||
motor_bus.write("Goal_Position", 2048)
|
||||
motor_bus.write("Lock", 1)
|
||||
print("Offset", motor_bus.read("Offset"))
|
||||
|
||||
except Exception as e:
|
||||
|
||||
@@ -1,3 +1,16 @@
|
||||
# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
#
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
"""
|
||||
Utilities to control a robot.
|
||||
|
||||
@@ -254,7 +267,7 @@ def record(
|
||||
)
|
||||
|
||||
# Load pretrained policy
|
||||
policy = None if cfg.policy is None else make_policy(cfg.policy, cfg.device, ds_meta=dataset.meta)
|
||||
policy = None if cfg.policy is None else make_policy(cfg.policy, ds_meta=dataset.meta)
|
||||
|
||||
if not robot.is_connected:
|
||||
robot.connect()
|
||||
@@ -285,8 +298,6 @@ def record(
|
||||
episode_time_s=cfg.episode_time_s,
|
||||
display_cameras=cfg.display_cameras,
|
||||
policy=policy,
|
||||
device=cfg.device,
|
||||
use_amp=cfg.use_amp,
|
||||
fps=cfg.fps,
|
||||
single_task=cfg.single_task,
|
||||
)
|
||||
|
||||
@@ -1,3 +1,16 @@
|
||||
# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
#
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
"""
|
||||
Utilities to control a robot in simulation.
|
||||
|
||||
|
||||
@@ -454,11 +454,11 @@ def _compile_episode_data(
|
||||
|
||||
|
||||
@parser.wrap()
|
||||
def eval(cfg: EvalPipelineConfig):
|
||||
def eval_main(cfg: EvalPipelineConfig):
|
||||
logging.info(pformat(asdict(cfg)))
|
||||
|
||||
# Check device is available
|
||||
device = get_safe_torch_device(cfg.device, log=True)
|
||||
device = get_safe_torch_device(cfg.policy.device, log=True)
|
||||
|
||||
torch.backends.cudnn.benchmark = True
|
||||
torch.backends.cuda.matmul.allow_tf32 = True
|
||||
@@ -470,14 +470,14 @@ def eval(cfg: EvalPipelineConfig):
|
||||
env = make_env(cfg.env, n_envs=cfg.eval.batch_size, use_async_envs=cfg.eval.use_async_envs)
|
||||
|
||||
logging.info("Making policy.")
|
||||
|
||||
policy = make_policy(
|
||||
cfg=cfg.policy,
|
||||
device=device,
|
||||
env_cfg=cfg.env,
|
||||
)
|
||||
policy.eval()
|
||||
|
||||
with torch.no_grad(), torch.autocast(device_type=device.type) if cfg.use_amp else nullcontext():
|
||||
with torch.no_grad(), torch.autocast(device_type=device.type) if cfg.policy.use_amp else nullcontext():
|
||||
info = eval_policy(
|
||||
env,
|
||||
policy,
|
||||
@@ -499,4 +499,4 @@ def eval(cfg: EvalPipelineConfig):
|
||||
|
||||
if __name__ == "__main__":
|
||||
init_logging()
|
||||
eval()
|
||||
eval_main()
|
||||
|
||||
@@ -1,3 +1,16 @@
|
||||
# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
#
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
import os
|
||||
import time
|
||||
from pathlib import Path
|
||||
|
||||
@@ -120,7 +120,7 @@ def train(cfg: TrainPipelineConfig):
|
||||
set_seed(cfg.seed)
|
||||
|
||||
# Check device is available
|
||||
device = get_safe_torch_device(cfg.device, log=True)
|
||||
device = get_safe_torch_device(cfg.policy.device, log=True)
|
||||
torch.backends.cudnn.benchmark = True
|
||||
torch.backends.cuda.matmul.allow_tf32 = True
|
||||
|
||||
@@ -138,13 +138,12 @@ def train(cfg: TrainPipelineConfig):
|
||||
logging.info("Creating policy")
|
||||
policy = make_policy(
|
||||
cfg=cfg.policy,
|
||||
device=device,
|
||||
ds_meta=dataset.meta,
|
||||
)
|
||||
|
||||
logging.info("Creating optimizer and scheduler")
|
||||
optimizer, lr_scheduler = make_optimizer_and_scheduler(cfg, policy)
|
||||
grad_scaler = GradScaler(device, enabled=cfg.use_amp)
|
||||
grad_scaler = GradScaler(device.type, enabled=cfg.policy.use_amp)
|
||||
|
||||
step = 0 # number of policy updates (forward + backward + optim)
|
||||
|
||||
@@ -218,7 +217,7 @@ def train(cfg: TrainPipelineConfig):
|
||||
cfg.optimizer.grad_clip_norm,
|
||||
grad_scaler=grad_scaler,
|
||||
lr_scheduler=lr_scheduler,
|
||||
use_amp=cfg.use_amp,
|
||||
use_amp=cfg.policy.use_amp,
|
||||
)
|
||||
|
||||
# Note: eval and checkpoint happens *after* the `step`th training update has completed, so we
|
||||
@@ -249,7 +248,10 @@ def train(cfg: TrainPipelineConfig):
|
||||
if cfg.env and is_eval_step:
|
||||
step_id = get_step_identifier(step, cfg.steps)
|
||||
logging.info(f"Eval policy at step {step}")
|
||||
with torch.no_grad(), torch.autocast(device_type=device.type) if cfg.use_amp else nullcontext():
|
||||
with (
|
||||
torch.no_grad(),
|
||||
torch.autocast(device_type=device.type) if cfg.policy.use_amp else nullcontext(),
|
||||
):
|
||||
eval_info = eval_policy(
|
||||
eval_env,
|
||||
policy,
|
||||
|
||||
@@ -265,13 +265,25 @@ def main():
|
||||
),
|
||||
)
|
||||
|
||||
parser.add_argument(
|
||||
"--tolerance-s",
|
||||
type=float,
|
||||
default=1e-4,
|
||||
help=(
|
||||
"Tolerance in seconds used to ensure data timestamps respect the dataset fps value"
|
||||
"This is argument passed to the constructor of LeRobotDataset and maps to its tolerance_s constructor argument"
|
||||
"If not given, defaults to 1e-4."
|
||||
),
|
||||
)
|
||||
|
||||
args = parser.parse_args()
|
||||
kwargs = vars(args)
|
||||
repo_id = kwargs.pop("repo_id")
|
||||
root = kwargs.pop("root")
|
||||
tolerance_s = kwargs.pop("tolerance_s")
|
||||
|
||||
logging.info("Loading dataset")
|
||||
dataset = LeRobotDataset(repo_id, root=root)
|
||||
dataset = LeRobotDataset(repo_id, root=root, tolerance_s=tolerance_s)
|
||||
|
||||
visualize_dataset(dataset, **vars(args))
|
||||
|
||||
|
||||
@@ -158,7 +158,7 @@ def run_server(
|
||||
if major_version < 2:
|
||||
return "Make sure to convert your LeRobotDataset to v2 & above."
|
||||
|
||||
episode_data_csv_str, columns = get_episode_data(dataset, episode_id)
|
||||
episode_data_csv_str, columns, ignored_columns = get_episode_data(dataset, episode_id)
|
||||
dataset_info = {
|
||||
"repo_id": f"{dataset_namespace}/{dataset_name}",
|
||||
"num_samples": dataset.num_frames
|
||||
@@ -194,7 +194,7 @@ def run_server(
|
||||
]
|
||||
|
||||
response = requests.get(
|
||||
f"https://huggingface.co/datasets/{repo_id}/resolve/main/meta/episodes.jsonl"
|
||||
f"https://huggingface.co/datasets/{repo_id}/resolve/main/meta/episodes.jsonl", timeout=5
|
||||
)
|
||||
response.raise_for_status()
|
||||
# Split into lines and parse each line as JSON
|
||||
@@ -218,6 +218,7 @@ def run_server(
|
||||
videos_info=videos_info,
|
||||
episode_data_csv_str=episode_data_csv_str,
|
||||
columns=columns,
|
||||
ignored_columns=ignored_columns,
|
||||
)
|
||||
|
||||
app.run(host=host, port=port)
|
||||
@@ -233,9 +234,17 @@ def get_episode_data(dataset: LeRobotDataset | IterableNamespace, episode_index)
|
||||
This file will be loaded by Dygraph javascript to plot data in real time."""
|
||||
columns = []
|
||||
|
||||
selected_columns = [col for col, ft in dataset.features.items() if ft["dtype"] == "float32"]
|
||||
selected_columns = [col for col, ft in dataset.features.items() if ft["dtype"] in ["float32", "int32"]]
|
||||
selected_columns.remove("timestamp")
|
||||
|
||||
ignored_columns = []
|
||||
for column_name in selected_columns:
|
||||
shape = dataset.features[column_name]["shape"]
|
||||
shape_dim = len(shape)
|
||||
if shape_dim > 1:
|
||||
selected_columns.remove(column_name)
|
||||
ignored_columns.append(column_name)
|
||||
|
||||
# init header of csv with state and action names
|
||||
header = ["timestamp"]
|
||||
|
||||
@@ -291,7 +300,7 @@ def get_episode_data(dataset: LeRobotDataset | IterableNamespace, episode_index)
|
||||
csv_writer.writerows(rows)
|
||||
csv_string = csv_buffer.getvalue()
|
||||
|
||||
return csv_string, columns
|
||||
return csv_string, columns, ignored_columns
|
||||
|
||||
|
||||
def get_episode_video_paths(dataset: LeRobotDataset, ep_index: int) -> list[str]:
|
||||
@@ -318,7 +327,9 @@ def get_episode_language_instruction(dataset: LeRobotDataset, ep_index: int) ->
|
||||
|
||||
|
||||
def get_dataset_info(repo_id: str) -> IterableNamespace:
|
||||
response = requests.get(f"https://huggingface.co/datasets/{repo_id}/resolve/main/meta/info.json")
|
||||
response = requests.get(
|
||||
f"https://huggingface.co/datasets/{repo_id}/resolve/main/meta/info.json", timeout=5
|
||||
)
|
||||
response.raise_for_status() # Raises an HTTPError for bad responses
|
||||
dataset_info = response.json()
|
||||
dataset_info["repo_id"] = repo_id
|
||||
@@ -435,15 +446,31 @@ def main():
|
||||
help="Delete the output directory if it exists already.",
|
||||
)
|
||||
|
||||
parser.add_argument(
|
||||
"--tolerance-s",
|
||||
type=float,
|
||||
default=1e-4,
|
||||
help=(
|
||||
"Tolerance in seconds used to ensure data timestamps respect the dataset fps value"
|
||||
"This is argument passed to the constructor of LeRobotDataset and maps to its tolerance_s constructor argument"
|
||||
"If not given, defaults to 1e-4."
|
||||
),
|
||||
)
|
||||
|
||||
args = parser.parse_args()
|
||||
kwargs = vars(args)
|
||||
repo_id = kwargs.pop("repo_id")
|
||||
load_from_hf_hub = kwargs.pop("load_from_hf_hub")
|
||||
root = kwargs.pop("root")
|
||||
tolerance_s = kwargs.pop("tolerance_s")
|
||||
|
||||
dataset = None
|
||||
if repo_id:
|
||||
dataset = LeRobotDataset(repo_id, root=root) if not load_from_hf_hub else get_dataset_info(repo_id)
|
||||
dataset = (
|
||||
LeRobotDataset(repo_id, root=root, tolerance_s=tolerance_s)
|
||||
if not load_from_hf_hub
|
||||
else get_dataset_info(repo_id)
|
||||
)
|
||||
|
||||
visualize_dataset_html(dataset, **vars(args))
|
||||
|
||||
|
||||
@@ -42,22 +42,22 @@
|
||||
<ul>
|
||||
<template x-for="episode in paginatedEpisodes" :key="episode">
|
||||
<li class="font-mono text-sm mt-0.5">
|
||||
<a :href="'episode_' + episode"
|
||||
<a :href="'episode_' + episode"
|
||||
:class="{'underline': true, 'font-bold -ml-1': episode == {{ episode_id }}}"
|
||||
x-text="'Episode ' + episode"></a>
|
||||
</li>
|
||||
</template>
|
||||
</ul>
|
||||
|
||||
|
||||
<div class="flex items-center mt-3 text-xs" x-show="totalPages > 1">
|
||||
<button @click="prevPage()"
|
||||
<button @click="prevPage()"
|
||||
class="px-2 py-1 bg-slate-800 rounded mr-2"
|
||||
:class="{'opacity-50 cursor-not-allowed': page === 1}"
|
||||
:disabled="page === 1">
|
||||
« Prev
|
||||
</button>
|
||||
<span class="font-mono mr-2" x-text="` ${page} / ${totalPages}`"></span>
|
||||
<button @click="nextPage()"
|
||||
<button @click="nextPage()"
|
||||
class="px-2 py-1 bg-slate-800 rounded"
|
||||
:class="{'opacity-50 cursor-not-allowed': page === totalPages}"
|
||||
:disabled="page === totalPages">
|
||||
@@ -65,10 +65,10 @@
|
||||
</button>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
|
||||
<!-- episodes menu for small screens -->
|
||||
<div class="flex overflow-x-auto md:hidden" x-data="episodePagination">
|
||||
<button @click="prevPage()"
|
||||
<button @click="prevPage()"
|
||||
class="px-2 bg-slate-800 rounded mr-2"
|
||||
:class="{'opacity-50 cursor-not-allowed': page === 1}"
|
||||
:disabled="page === 1">«</button>
|
||||
@@ -83,7 +83,7 @@
|
||||
</p>
|
||||
</template>
|
||||
</div>
|
||||
<button @click="nextPage()"
|
||||
<button @click="nextPage()"
|
||||
class="px-2 bg-slate-800 rounded ml-2"
|
||||
:class="{'opacity-50 cursor-not-allowed': page === totalPages}"
|
||||
:disabled="page === totalPages">» </button>
|
||||
@@ -224,49 +224,58 @@
|
||||
</p>
|
||||
</div>
|
||||
|
||||
<table class="text-sm border-collapse border border-slate-700" x-show="currentFrameData">
|
||||
<thead>
|
||||
<tr>
|
||||
<th></th>
|
||||
<template x-for="(_, colIndex) in Array.from({length: columns.length}, (_, index) => index)">
|
||||
<th class="border border-slate-700">
|
||||
<div class="flex gap-x-2 justify-between px-2">
|
||||
<input type="checkbox" :checked="isColumnChecked(colIndex)"
|
||||
@change="toggleColumn(colIndex)">
|
||||
<p x-text="`${columns[colIndex].key}`"></p>
|
||||
</div>
|
||||
</th>
|
||||
</template>
|
||||
</tr>
|
||||
</thead>
|
||||
<tbody>
|
||||
<template x-for="(row, rowIndex) in rows">
|
||||
<tr class="odd:bg-gray-800 even:bg-gray-900">
|
||||
<td class="border border-slate-700">
|
||||
<div class="flex gap-x-2 max-w-64 font-semibold px-1 break-all">
|
||||
<input type="checkbox" :checked="isRowChecked(rowIndex)"
|
||||
@change="toggleRow(rowIndex)">
|
||||
</div>
|
||||
</td>
|
||||
<template x-for="(cell, colIndex) in row">
|
||||
<td x-show="cell" class="border border-slate-700">
|
||||
<div class="flex gap-x-2 justify-between px-2" :class="{ 'hidden': cell.isNull }">
|
||||
<div class="flex gap-x-2">
|
||||
<input type="checkbox" x-model="cell.checked" @change="updateTableValues()">
|
||||
<span x-text="`${!cell.isNull ? cell.label : null}`"></span>
|
||||
</div>
|
||||
<span class="w-14 text-right" x-text="`${!cell.isNull ? (typeof cell.value === 'number' ? cell.value.toFixed(2) : cell.value) : null}`"
|
||||
:style="`color: ${cell.color}`"></span>
|
||||
<div>
|
||||
<table class="text-sm border-collapse border border-slate-700" x-show="currentFrameData">
|
||||
<thead>
|
||||
<tr>
|
||||
<th></th>
|
||||
<template x-for="(_, colIndex) in Array.from({length: columns.length}, (_, index) => index)">
|
||||
<th class="border border-slate-700">
|
||||
<div class="flex gap-x-2 justify-between px-2">
|
||||
<input type="checkbox" :checked="isColumnChecked(colIndex)"
|
||||
@change="toggleColumn(colIndex)">
|
||||
<p x-text="`${columns[colIndex].key}`"></p>
|
||||
</div>
|
||||
</td>
|
||||
</th>
|
||||
</template>
|
||||
</tr>
|
||||
</template>
|
||||
</tbody>
|
||||
</table>
|
||||
</thead>
|
||||
<tbody>
|
||||
<template x-for="(row, rowIndex) in rows">
|
||||
<tr class="odd:bg-gray-800 even:bg-gray-900">
|
||||
<td class="border border-slate-700">
|
||||
<div class="flex gap-x-2 max-w-64 font-semibold px-1 break-all">
|
||||
<input type="checkbox" :checked="isRowChecked(rowIndex)"
|
||||
@change="toggleRow(rowIndex)">
|
||||
</div>
|
||||
</td>
|
||||
<template x-for="(cell, colIndex) in row">
|
||||
<td x-show="cell" class="border border-slate-700">
|
||||
<div class="flex gap-x-2 justify-between px-2" :class="{ 'hidden': cell.isNull }">
|
||||
<div class="flex gap-x-2">
|
||||
<input type="checkbox" x-model="cell.checked" @change="updateTableValues()">
|
||||
<span x-text="`${!cell.isNull ? cell.label : null}`"></span>
|
||||
</div>
|
||||
<span class="w-14 text-right" x-text="`${!cell.isNull ? (typeof cell.value === 'number' ? cell.value.toFixed(2) : cell.value) : null}`"
|
||||
:style="`color: ${cell.color}`"></span>
|
||||
</div>
|
||||
</td>
|
||||
</template>
|
||||
</tr>
|
||||
</template>
|
||||
</tbody>
|
||||
</table>
|
||||
|
||||
<div id="labels" class="hidden">
|
||||
<div id="labels" class="hidden">
|
||||
</div>
|
||||
|
||||
{% if ignored_columns|length > 0 %}
|
||||
<div class="m-2 text-orange-700 max-w-96">
|
||||
Columns {{ ignored_columns }} are NOT shown since the visualizer currently does not support 2D or 3D data.
|
||||
</div>
|
||||
{% endif %}
|
||||
</div>
|
||||
|
||||
</div>
|
||||
</div>
|
||||
|
||||
@@ -476,7 +485,7 @@
|
||||
episodes: {{ episodes }},
|
||||
pageSize: 100,
|
||||
page: 1,
|
||||
|
||||
|
||||
init() {
|
||||
// Find which page contains the current episode_id
|
||||
const currentEpisodeId = {{ episode_id }};
|
||||
@@ -485,23 +494,23 @@
|
||||
this.page = Math.floor(episodeIndex / this.pageSize) + 1;
|
||||
}
|
||||
},
|
||||
|
||||
|
||||
get totalPages() {
|
||||
return Math.ceil(this.episodes.length / this.pageSize);
|
||||
},
|
||||
|
||||
|
||||
get paginatedEpisodes() {
|
||||
const start = (this.page - 1) * this.pageSize;
|
||||
const end = start + this.pageSize;
|
||||
return this.episodes.slice(start, end);
|
||||
},
|
||||
|
||||
|
||||
nextPage() {
|
||||
if (this.page < this.totalPages) {
|
||||
this.page++;
|
||||
}
|
||||
},
|
||||
|
||||
|
||||
prevPage() {
|
||||
if (this.page > 1) {
|
||||
this.page--;
|
||||
@@ -515,7 +524,7 @@
|
||||
window.addEventListener('keydown', (e) => {
|
||||
// Use the space bar to play and pause, instead of default action (e.g. scrolling)
|
||||
const { keyCode, key } = e;
|
||||
|
||||
|
||||
if (keyCode === 32 || key === ' ') {
|
||||
e.preventDefault();
|
||||
const btnPause = document.querySelector('[x-ref="btnPause"]');
|
||||
|
||||
BIN
media/lekiwi/kiwi.webp
Normal file
|
After Width: | Height: | Size: 219 KiB |
BIN
media/tutorial/img1.jpg
Normal file
|
After Width: | Height: | Size: 66 KiB |
BIN
media/tutorial/img10.jpg
Normal file
|
After Width: | Height: | Size: 127 KiB |
BIN
media/tutorial/img11.jpg
Normal file
|
After Width: | Height: | Size: 109 KiB |
BIN
media/tutorial/img12.jpg
Normal file
|
After Width: | Height: | Size: 80 KiB |
BIN
media/tutorial/img13.jpg
Normal file
|
After Width: | Height: | Size: 88 KiB |
BIN
media/tutorial/img14.jpg
Normal file
|
After Width: | Height: | Size: 86 KiB |
BIN
media/tutorial/img15.jpg
Normal file
|
After Width: | Height: | Size: 96 KiB |
BIN
media/tutorial/img16.jpg
Normal file
|
After Width: | Height: | Size: 84 KiB |
BIN
media/tutorial/img17.jpg
Normal file
|
After Width: | Height: | Size: 72 KiB |
BIN
media/tutorial/img18.jpg
Normal file
|
After Width: | Height: | Size: 78 KiB |
BIN
media/tutorial/img19.jpg
Normal file
|
After Width: | Height: | Size: 97 KiB |
BIN
media/tutorial/img2.jpg
Normal file
|
After Width: | Height: | Size: 88 KiB |
BIN
media/tutorial/img20.jpg
Normal file
|
After Width: | Height: | Size: 42 KiB |
BIN
media/tutorial/img21.jpg
Normal file
|
After Width: | Height: | Size: 85 KiB |
BIN
media/tutorial/img22.jpg
Normal file
|
After Width: | Height: | Size: 62 KiB |
BIN
media/tutorial/img23.jpg
Normal file
|
After Width: | Height: | Size: 54 KiB |