From 368830fe8e85d77d5fabec7caef82f3fefd2a58a Mon Sep 17 00:00:00 2001 From: CarolinePascal Date: Wed, 24 Jun 2026 17:57:15 +0200 Subject: [PATCH] chore(format): format code --- src/lerobot/datasets/factory.py | 2 +- src/lerobot/scripts/lerobot_dataset_viz.py | 1 + src/lerobot/utils/visualization_utils.py | 4 +--- 3 files changed, 3 insertions(+), 4 deletions(-) diff --git a/src/lerobot/datasets/factory.py b/src/lerobot/datasets/factory.py index 0dd59748d..b9aea9b12 100644 --- a/src/lerobot/datasets/factory.py +++ b/src/lerobot/datasets/factory.py @@ -128,7 +128,7 @@ def make_dataset(cfg: TrainPipelineConfig) -> LeRobotDataset | MultiLeRobotDatas if cfg.dataset.use_imagenet_stats: for key in dataset.meta.camera_keys: if key in dataset.meta.depth_keys: - continue # Exclude depth keys from ImageNet stats + continue # Exclude depth keys from ImageNet stats for stats_type, stats in IMAGENET_STATS.items(): dataset.meta.stats[key][stats_type] = torch.tensor(stats, dtype=torch.float32) diff --git a/src/lerobot/scripts/lerobot_dataset_viz.py b/src/lerobot/scripts/lerobot_dataset_viz.py index 43f992f46..a5f3ba11b 100644 --- a/src/lerobot/scripts/lerobot_dataset_viz.py +++ b/src/lerobot/scripts/lerobot_dataset_viz.py @@ -86,6 +86,7 @@ def check_chw_float32(frame: torch.Tensor) -> None: c, h, w = frame.shape assert c < h and c < w, f"expect channel first images, but instead {frame.shape}" + def to_hwc_uint8_numpy(chw_float32_torch: torch.Tensor) -> np.ndarray: check_chw_float32(chw_float32_torch) hwc_uint8_numpy = (chw_float32_torch * 255).type(torch.uint8).permute(1, 2, 0).numpy() diff --git a/src/lerobot/utils/visualization_utils.py b/src/lerobot/utils/visualization_utils.py index 5a0f74378..e039f7b33 100644 --- a/src/lerobot/utils/visualization_utils.py +++ b/src/lerobot/utils/visualization_utils.py @@ -108,9 +108,7 @@ def log_rerun_data( rr.log(f"{key}_{i}", rr.Scalars(float(vi))) else: if arr.shape[-1] == 1: - img_entity = ( - rr.DepthImage(arr, colormap=rr.components.Colormap.Viridis) - ) + img_entity = rr.DepthImage(arr, colormap=rr.components.Colormap.Viridis) else: img_entity = rr.Image(arr).compress() if compress_images else rr.Image(arr) rr.log(key, entity=img_entity, static=True)