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    answered Mar 23, 2021 at 19:34

    there's already an explanation on how to use the command line, especially to save result in .txt format, the link:

    https://github.com/AlexeyAB/darknet#how-to-use-on-the-command-line

    to save time, i will provide the point which is might be helpful:

    • To process a list of images data/train.txt and save results of detection to result.txt use:

    • darknet.exe detector test cfg/coco.data cfg/yolov4.cfg yolov4.weights -dont_show -ext_output < data/train.txt > result.txt

    might be late but maybe helpful to the others.

    Content Under CC-BY-SA license
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    What is yolov4 model?It is an easy-to-use multi-purpose model which can be used for the detection, classification, and segmentation of day-to-day objects. We will have a brief introduction to the YOLOv4 model and then explain to you how to use YOLOv4 for object detection in images and videos. What is YOLOv4?
    How does yolov4 work?The architecture of YOLOv4 includes CSPDarknet53 as the backbone, PANet as the neck, and YOLOv3 as the detection head. This design allows YOLOv4 to perform object detection at an impressive speed, making it suitable for real-time applications. YOLOv4 also excels in accuracy, achieving state-of-the-art results in object detection benchmarks.
    Which Yolo model is used in darknet?YOLOv4 (by Alexey et al.) was the last YOLO model to be written in Darknet. After that, there have been many YOLO object detections. Scaled YOLOv4, YOLOX, PP-YOLO, YOLOv6, and YOLOv7 are some of the prominent among them.
    Who wrote Yolo V4?The YOLO v4 release lists three authors: Alexey Bochkovskiy, the Russian developer who built the YOLO Windows version, Chien-Yao Wang, and Hong-Yuan Mark Liao.
    How to build Yolo V4?Building YOLO v4 using Make Switch to the darknet folder after download. Open the Makefile in the darknet folder. You can see some of the variables at the beginning of the Makefile. If you want to compile darknet for CPU, you can use the following flags. For CPU build
    What are Yolo variants?And today, we will give an introduction to the YOLO family by covering all the YOLO variants (e.g., YOLOv1, YOLOv2,…, YOLOX, YOLOR). Since its inception, the object detection field has grown significantly, and the state-of-the-art architectures generalize pretty well on various test datasets.
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    WebJul 17, 2021 · Learn how to use YOLOv4, a powerful object detector model, for images and videos on Google Colab. Follow the steps to set up Colab, mount your drive, clone the Darknet repository, build Darknet, and run

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  9. WebMay 1, 2020 · Learn the basics of object detection and the latest version of YOLO (You Only Look Once) in Ubuntu 20.04. Follow the steps to install, test and run YOLO v4 on images, videos and webcam.

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