PASCAL VOC 2007 (PASCAL Visual Object Classes Challenge 2007) is a standard benchmark dataset for object detection, classification and segmentation. VOC2007 contains 9,963 images with annotations for 20 object classes (e.g., person, car, bicycle, dog) and about 24,640 annotated object instances. Annotations include class labels, object bounding boxes and (for some images) pixel-level segmentation masks, plus object attributes such as "difficult" and "truncated". The dataset is provided with standard train/val/test splits (the official VOC2007 test annotations were held out on the evaluation server), and the canonical detection evaluation metric reported on this dataset is mean Average Precision (mAP) computed using the PASCAL VOC protocol (AP at IoU 0.5). VOC2007 is widely used for benchmarking object detection models and is often combined with VOC2012 or COCO for additional training (e.g., VOC07+12 or COCO+07+12).
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