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+ ## PartImageNet++ Dataset
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+ PartImageNet++ is an extensive dataset designed for robust object recognition and segmentation tasks. This dataset expands upon the original ImageNet dataset by providing detailed part annotations for each object category.
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+ ### Dataset Statistics
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+ | Obj. Cat. | Part Cat. | Img | Part Mask |
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+ | --------- | --------- | ------ | --------- |
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+ | 1000 | 3308 | 100000 | 452749 |
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+ The dataset includes:
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+ - **1000 object categories** derived from the original ImageNet.
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+ - **3308 part categories** representing different parts of objects.
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+ - **100,000 annotated images**, with each object category containing 100 images.
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+ - **452,749 part mask annotations** ensuring comprehensive coverage and detailed segmentation.
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+ ### Structure and Contents
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+ Each JSON file in the `json` directory represents one object category and its corresponding part annotations.
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+ The `including` folder provides detailed inclusion relations of parts, illustrating hierarchical relationships between different part categories.
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+ The `discarded_data.json` file lists low-quality images that were excluded from the dataset to maintain high annotation standards.
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+ ### Visualizations
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+ We provide a visualization demo tool to explore and inspect the annotations. This tool helps users to better understand the structure and details of the dataset.