Collection Pics 200zip Apr 2026

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

Originally created for Stanford’s course, this dataset is a scaled-down version of the massive ImageNet database, designed to be more manageable for training models on standard hardware while remaining complex enough for meaningful research. Content: 120,000 total images. COLLECTION PICS 200zip

Adding dataset Tiny-Imagenet · Issue #6127 · pytorch/vision - GitHub 200 distinct categories (e

For Python users, this dataset is commonly loaded using libraries like or TensorFlow via torchvision.datasets or tensorflow_datasets . Validation: 10,000 images (50 per class)

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

: 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.