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    Why is Yolo a breakthrough in object detection?YOLO (you only look once) was a breakthrough in the object detection field as it was the first single-stage object detector approach that treated detection as a regression problem. The detection architecture only looked once at the image to predict the location of the objects and their class labels.
    How do I use Yolo object detector?To apply YOLO object detection to video streams, make sure you use the “Downloads” section of this blog post to download the source, YOLO object detector, and example videos. From there, open up a terminal and execute the following command: --output output/car_chase_01.avi --yolo yolo-coco [INFO] loading YOLO from disk... [INFO] cleaning up...
    Why is Yolo not able to detect objects?The reason for this limitation is due to the YOLO algorithm itself: The YOLO object detector divides an input image into an SxS grid where each cell in the grid predicts only a single object. If there exist multiple, small objects in a single cell then YOLO will be unable to detect them, ultimately leading to missed object detections.
    Can Yolo predict object classes that don't have labeled detection data?The result is a YOLO model, called YOLO9000, that can predict detections for object classes that don’t have labeled detection data. While interesting and novel, YOLOv2’s performance was a bit underwhelming given the title and abstract of the paper.
  4. YOLOv4 - Ultralytics YOLOv8 Docs

  5. Introduction to the YOLO Family - PyImageSearch

  6. YOLO v8 Model Guide - Real-Time Object Detection Model …

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  8. Releases · ultralytics/yolov3 · GitHub

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