Collection Pics 200zip 〈Linux〉

200 distinct categories (e.g., animals, vehicles, everyday objects). Image Resolution: pixels (full-color JPEG format). Data Split: Training: 100,000 images (500 per class). Validation: 10,000 images (50 per class). Test: 10,000 images (unlabeled). Implementation Details

: Contains the WordNet IDs (unique identifiers) for the 200 classes. COLLECTION PICS 200zip

: Includes a flat list of 10,000 images and a val_annotations.txt file that maps each image to its correct class for validation purposes. 200 distinct categories (e

For Python users, this dataset is commonly loaded using libraries like or TensorFlow via torchvision.datasets or tensorflow_datasets . 200 distinct categories (e.g.

: Maps those WordNet IDs to human-readable labels (e.g., "n02124075" becomes "Egyptian cat").

Adding dataset Tiny-Imagenet · Issue #6127 · pytorch/vision - GitHub