rename to image_transforms
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@@ -1,5 +1,5 @@
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"""
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This script demonstrates how to implement torchvision image augmentation on an instance of a LeRobotDataset and how to show some transformed images.
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This script demonstrates how to implement torchvision image augmentation on an instance of a LeRobotDataset and how to show some transformed images.
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The transformations are passed to the dataset as an argument upon creation, and transforms are applied to the observation images before they are returned.
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"""
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@@ -18,7 +18,7 @@ output_dir.mkdir(parents=True, exist_ok=True)
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repo_id = "lerobot/aloha_static_tape"
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# Create a LeRobotDataset with no transformations
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dataset = LeRobotDataset(repo_id, transform=None)
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dataset = LeRobotDataset(repo_id, image_transforms=None)
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# Get the index of the first observation in the first episode
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first_idx = dataset.episode_data_index["from"][0].item()
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@@ -41,7 +41,7 @@ transforms = v2.Compose(
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)
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# Create another LeRobotDataset with the defined transformations
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transformed_dataset = LeRobotDataset(repo_id, transform=transforms)
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transformed_dataset = LeRobotDataset(repo_id, image_transforms=transforms)
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# Get a frame from the transformed dataset
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transformed_frame = transformed_dataset[first_idx][transformed_dataset.camera_keys[0]]
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