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diff --git a/tests/scripts/save_image_transforms.py b/tests/scripts/save_image_transforms.py
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+++ b/tests/scripts/save_image_transforms.py
@@ -0,0 +1,42 @@
+from pathlib import Path
+
+from torchvision.transforms import ToPILImage, v2
+
+from lerobot.common.datasets.lerobot_dataset import LeRobotDataset
+from lerobot.common.datasets.transforms import RangeRandomSharpness
+from lerobot.common.utils.utils import seeded_context
+
+DEFAULT_CONFIG_PATH = "lerobot/configs/default.yaml"
+ARTIFACT_DIR = "tests/data/save_image_transforms"
+SEED = 1336
+to_pil = ToPILImage()
+
+
+def main(repo_id):
+    dataset = LeRobotDataset(repo_id, transform=None)
+    output_dir = Path(ARTIFACT_DIR)
+    output_dir.mkdir(parents=True, exist_ok=True)
+
+    # Get first frame of given episode
+    from_idx = dataset.episode_data_index["from"][0].item()
+    original_frame = dataset[from_idx][dataset.camera_keys[0]]
+    to_pil(original_frame).save(output_dir / "original_frame.png", quality=100)
+
+    transforms = {
+        "brightness": v2.ColorJitter(brightness=(0.0, 2.0)),
+        "contrast": v2.ColorJitter(contrast=(0.0, 2.0)),
+        "saturation": v2.ColorJitter(saturation=(0.0, 2.0)),
+        "hue": v2.ColorJitter(hue=(-0.5, 0.5)),
+        "sharpness": RangeRandomSharpness(0.0, 2.0),
+    }
+
+    # Apply each single transformation
+    for name, transform in transforms.items():
+        with seeded_context(SEED):
+            transformed_frame = transform(original_frame)
+            to_pil(transformed_frame).save(output_dir / f"{SEED}_{name}.png", quality=100)
+
+
+if __name__ == "__main__":
+    repo_id = "lerobot/aloha_mobile_shrimp"
+    main(repo_id)