Update https://docs.ultralytics.com/models (#6513)
Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com> Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
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@ -28,7 +28,7 @@ In the world of machine learning and computer vision, the process of making sens
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| Manufacturing | Sports | Safety |
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|:-------------------------------------------------:|:----------------------------------------------------:|:-------------------------------------------:|
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| ![Vehicle Spare Parts Detection][car spare parts] | ![Football Player Detection][football player detect] | ![People Fall Detection][human fall detect] |
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| Vehicle Spare Parts Detection | Football Player Detection | People Fall Detection |
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| Vehicle Spare Parts Detection | Football Player Detection | People Fall Detection |
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## Why Use Ultralytics YOLO for Inference?
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@ -715,5 +715,7 @@ Here's a Python script using OpenCV (`cv2`) and YOLOv8 to run inference on video
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This script will run predictions on each frame of the video, visualize the results, and display them in a window. The loop can be exited by pressing 'q'.
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[car spare parts]: https://github.com/RizwanMunawar/ultralytics/assets/62513924/a0f802a8-0776-44cf-8f17-93974a4a28a1
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[football player detect]: https://github.com/RizwanMunawar/ultralytics/assets/62513924/7d320e1f-fc57-4d7f-a691-78ee579c3442
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[human fall detect]: https://github.com/RizwanMunawar/ultralytics/assets/62513924/86437c4a-3227-4eee-90ef-9efb697bdb43
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