A state-of-the-art, real-time object detection system that is able to recognize objects in images and video at high speeds. YOLO is novel because it frames object detection as a single regression problem, straight from image pixels to bounding box coordinates and class probabilities.
A framework built on top of TensorFlow that makes it easy to construct, train, and deploy object detection models. It includes a collection of pre-trained models that have been trained on various image recognition tasks, including the COCO dataset, Kitti dataset, and the Open Images dataset.
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