YOLOv5 is an open-source computer vision model developed by Ultralytics, implemented in PyTorch, designed for object detection, instance segmentation, and image classification. It processes various input types including URLs, filenames, and image arrays, and outputs detection results in formats such as torch tensors, pandas dataframes, or JSON. The model supports exporting to deployment formats like ONNX, CoreML, and TFLite.