diff --git a/README.md b/README.md index 29c5778..a6e3627 100644 --- a/README.md +++ b/README.md @@ -38,6 +38,7 @@ We use [uv](https://docs.astral.sh/uv/) to manage Python dependencies. See the [ ```bash GIT_LFS_SKIP_SMUDGE=1 uv sync +GIT_LFS_SKIP_SMUDGE=1 uv pip install -e . ``` NOTE: `GIT_LFS_SKIP_SMUDGE=1` is needed to pull LeRobot as a dependency. diff --git a/examples/aloha_real/README.md b/examples/aloha_real/README.md index 3addd4f..66fd836 100644 --- a/examples/aloha_real/README.md +++ b/examples/aloha_real/README.md @@ -28,13 +28,13 @@ uv pip sync examples/aloha_real/requirements.txt uv pip install -e packages/openpi-client # Run the robot -python examples/aloha_real/main.py +python -m examples.aloha_real.main ``` Terminal window 2: ```bash -roslaunch --wait aloha ros_nodes.launch +roslaunch aloha ros_nodes.launch ``` Terminal window 3: @@ -123,4 +123,4 @@ This task involves opening a tupperware filled with food and pouring the content We provide the [pi0_aloha_pen_uncap config](../../src/openpi/training/config.py) as an example. You should refer to the root [README](../../README.md) for how to run training with the new config. -IMPORTANT: Our base checkpoint includes normalization stats from various common robot configurations. When fine-tuning a base checkpoint with a custom dataset from one of these configurations, we recommend using the corresponding normalization stats provided in the base checkpoint. In the example, this is done by specifying the trossen asset_id and a path to the pretrained checkpoint’s asset directory within the AssetsConfig. \ No newline at end of file +IMPORTANT: Our base checkpoint includes normalization stats from various common robot configurations. When fine-tuning a base checkpoint with a custom dataset from one of these configurations, we recommend using the corresponding normalization stats provided in the base checkpoint. In the example, this is done by specifying the trossen asset_id and a path to the pretrained checkpoint’s asset directory within the AssetsConfig.