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The dataset contains 20,578 images of dogs in various poses, labeled as ‘standing’, ‘sitting’, ‘lying down’, or ‘undefined’. It is intended for computer‑vision tasks that identify dog behavior from images. The images span 120 dog breeds with varying resolutions; 50 % of the images have resolutions between 361 × 333 and 500 × 453 pixels. The dataset is adapted from the Stanford Dog Dataset with re‑labeled poses. Class distribution is imbalanced, with ‘lying down’ nearly double the ‘sitting’ images, and ‘undefined’ mainly consisting of close‑up portraits, which may limit processing of such images. Users should consider class‑balancing techniques such as oversampling or data augmentation.
