feat(script): add entry point for image transform viz (#2007)

* feat(Scripts): add entry point for img transform viz

* chore(style): pre-commit style

docs/source/lerobot-dataset-v3.mdx

@@ -246,7 +246,7 @@ You can also use any `torchvision.transforms.v2` transform by passing it directl
 Use the visualization script to preview how transforms affect your data:
 
 ```bash
-python -m lerobot.scripts.visualize_image_transforms \
+lerobot-imgtransform-viz \
   --repo-id=your-username/your-dataset \
   --output-dir=./transform_examples \
   --n-examples=5

pyproject.toml

@@ -173,6 +173,7 @@ lerobot-eval="lerobot.scripts.eval:main"
 lerobot-train="lerobot.scripts.train:main"
 lerobot-dataset-viz="lerobot.scripts.lerobot_dataset_viz:main"
 lerobot-info="lerobot.scripts.lerobot_info:main"
+lerobot-imgtransform-viz="lerobot.scripts.lerobot_imgtransform_viz:main"
 
 # ---------------- Tool Configurations ----------------
 [tool.setuptools.packages.find]

src/lerobot/scripts/lerobot_imgtransform_viz.py

@@ -20,10 +20,10 @@ Additionally, each individual transform can be visualized separately as well as
 
 Example:
 ```bash
-python -m lerobot.scripts.visualize_image_transforms \
-    --repo_id=lerobot/pusht \
-    --episodes='[0]' \
-    --image_transforms.enable=True
+lerobot-imgtransform-viz \
+  --repo_id=lerobot/pusht \
+  --episodes='[0]' \
+  --image_transforms.enable=True
 ```
 """
 
@@ -126,5 +126,9 @@ def visualize_image_transforms(cfg: DatasetConfig, output_dir: Path = OUTPUT_DIR
     save_each_transform(cfg.image_transforms, original_frame, output_dir, n_examples)
 
 
-if __name__ == "__main__":
+def main():
     visualize_image_transforms()
+
+
+if __name__ == "__main__":
+    main()

tests/datasets/test_image_transforms.py

@@ -29,7 +29,7 @@ from lerobot.datasets.transforms import (
     SharpnessJitter,
     make_transform_from_config,
 )
-from lerobot.scripts.visualize_image_transforms import (
+from lerobot.scripts.lerobot_imgtransform_viz import (
     save_all_transforms,
     save_each_transform,
 )