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  1. Copilot Answer
    Github
    https://github.com › kiyoshiiriemon

    Yolo v4, v3 and v2 for Windows and Linux - GitHub

    • 1.Train it first on 1 GPU for like 1000 iterations: darknet.exe detector train cfg/coco.data cfg/yolov4.cfg yolov4.conv.137
      2.Then stop and by using partially-trained model … See more

    How to train (to detect your custom objects)

    (to train old Yolo v2 yolov2-voc.cfg, yolov2-tiny-voc.cfg, yolo-voc.cfg, yolo-voc.2.0.cfg, ... click by the link)
    Training Yolo v4 (and v3):
    1.For traini… See more

    Github
    When should I stop training

    Usually sufficient 2000 iterations for each class(object), but not less than number of training images and not less than 6000 iterations in total. But for a more precise definition w… See more

    Github
    How to improve object detection

    1.Before training:
    •set flag random=1 in your .cfg-file - it will increase precision by training Yolo for different resolutions: link
    •increase n… See more

    Github
    How to mark bounded boxes of objects and create annotation files

    Here you can find repository with GUI-software for marking bounded boxes of objects and generating annotation files for Yolo v2 - v4: … See more

    Github
    What is Yolo V4 object detection network?
    The you only look once version 4 (YOLO v4) object detection network is a one-stage object detection network and is composed of three parts: backbone, neck, and head. The backbone can be a pretrained convolutional neural network such as VGG16 or CSPDarkNet53 trained on COCO or ImageNet data sets.
    mathworks.com

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