YOLOv5

YOLOv5 is family of object detections models pretrained on the COCO Dataset. It has been created by Ultralytics in 2020. This architecture contains 10 different models, each one with a different size and speed. YOLOv5 is also a part of the YOLO family of object detection models.

YOLOv5 is a family of object detection architectures and models pretrained on the COCO dataset and created By Ultralytics Team in 2020. This architecture uses single Neural Network to process entire image. It divides image into regions and predicts bounding boxes and probabilities for each region. These bounding boxes are weighted by the predicted probabilities. YOLOv5 is available in the Hub as a PyTorch module. You can use it directly in your code or in the Hub.

YOLOv5

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