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[HIL-SERL]Remove overstrict pre-commit modifications (#1028)

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This commit is contained in:
Adil Zouitine
2025-04-24 13:48:52 +02:00
committed by GitHub
parent 671ac3411f
commit c58b504a9e
47 changed files with 163 additions and 757 deletions
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27
benchmarks/video/run_video_benchmark.py
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@@ -32,11 +32,7 @@ import numpy as np
import pandas as pd
import PIL
import torch
from skimage.metrics import (
mean_squared_error,
peak_signal_noise_ratio,
structural_similarity,
)
from skimage.metrics import mean_squared_error, peak_signal_noise_ratio, structural_similarity
from tqdm import tqdm
from lerobot.common.datasets.lerobot_dataset import LeRobotDataset
@@ -98,11 +94,7 @@ def load_original_frames(imgs_dir: Path, timestamps: list[float], fps: int) -> t
def save_decoded_frames(
imgs_dir: Path,
save_dir: Path,
frames: torch.Tensor,
timestamps: list[float],
fps: int,
imgs_dir: Path, save_dir: Path, frames: torch.Tensor, timestamps: list[float], fps: int
) -> None:
if save_dir.exists() and len(list(save_dir.glob("frame_*.png"))) == len(timestamps):
return
@@ -112,10 +104,7 @@ def save_decoded_frames(
idx = int(ts * fps)
frame_hwc = (frames[i].permute((1, 2, 0)) * 255).type(torch.uint8).cpu().numpy()
PIL.Image.fromarray(frame_hwc).save(save_dir / f"frame_{idx:06d}_decoded.png")
shutil.copyfile(
imgs_dir / f"frame_{idx:06d}.png",
save_dir / f"frame_{idx:06d}_original.png",
)
shutil.copyfile(imgs_dir / f"frame_{idx:06d}.png", save_dir / f"frame_{idx:06d}_original.png")
def save_first_episode(imgs_dir: Path, dataset: LeRobotDataset) -> None:
@@ -131,11 +120,7 @@ def save_first_episode(imgs_dir: Path, dataset: LeRobotDataset) -> None:
imgs_dataset = hf_dataset.select_columns(img_keys[0])
for i, item in enumerate(
tqdm(
imgs_dataset,
desc=f"saving {dataset.repo_id} first episode images",
leave=False,
)
tqdm(imgs_dataset, desc=f"saving {dataset.repo_id} first episode images", leave=False)
):
img = item[img_keys[0]]
img.save(str(imgs_dir / f"frame_{i:06d}.png"), quality=100)
@@ -290,9 +275,7 @@ def benchmark_encoding_decoding(
random.seed(seed)
benchmark_table = []
for timestamps_mode in tqdm(
decoding_cfg["timestamps_modes"],
desc="decodings (timestamps_modes)",
leave=False,
decoding_cfg["timestamps_modes"], desc="decodings (timestamps_modes)", leave=False
):
for backend in tqdm(decoding_cfg["backends"], desc="decodings (backends)", leave=False):
benchmark_row = benchmark_decoding(