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    Top Answeranswered Nov 13, 2020 at 14:52

    To run detections on a video file run detector demo. In your case:

    !.darknet detector demo build/darknet/x64/cfg/custom-yolov4-tiny-detector.cfg build/darknet/x64/backup/custom-yolov4-tiny-detector_final.weights -ext_output build/darknet/x64/data/obj/your_video.mp4 -dont_show

    If you want to see the predictions on the video, add -out_filename your_video.mp4

    So the command becomes:

    !.darknet detector demo build/darknet/x64/cfg/custom-yolov4-tiny-detector.cfg build/darknet/x64/backup/custom-yolov4-tiny-detector_final.weights -ext_output build/darknet/

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  3. WebThis repository contains neural networks for object detection using Darknet framework. It does not contain yolobit mp4, which is a video format for streaming live video.

  4. WebAbout. Implement YOLOv4 Object Detection on your Webcam from within Google Colab! This tutorial uses scaled-YOLOv4, the most fast and accurate object detection system there currently is. Perform object …

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    What are the evaluation results for yolov3 & mixed Yolo Lite for shipdata?Evaluation results for YOLOv3 and Mixed YOLOv3-LITE for ShipData. 4.2.4. Performance Tests Based on Embedded Platform Mixed YOLOv3-LITE was tested with a Jetson AGX Xavier device; the results are shown in Table 10. When inputting an image with a size of 224 × 224, it reached 43 FPS.
    Why is yolov4 a good choice?YOLOv4 is designed to provide the optimal balance between speed and accuracy, making it an excellent choice for many applications. YOLOv4 architecture diagram. Showcasing the intricate network design of YOLOv4, including the backbone, neck, and head components, and their interconnected layers for optimal real-time object detection.
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