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README.md
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pipeline_tag: object-detection
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#
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This
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### Prerequisites
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* YOLOv4: Optimal Speed and Accuracy of Object Detection [YOLOv4](https://arxiv.org/abs/2004.10934).
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* [darknet](https://github.com/AlexeyAB/darknet)
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This project is inspired by these previous fantastic YOLOv3 implementations:
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* [Yolov3 tensorflow](https://github.com/YunYang1994/tensorflow-yolov3)
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* [Yolov3 tf2](https://github.com/zzh8829/yolov3-tf2)
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pipeline_tag: object-detection
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# YOLOv4
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YOLO, for You Only Look Once, is an object detection system in real-time, introduced in [this paper](https://arxiv.org/abs/2004.10934), that recognizes various objects in a single enclosure. It identifies objects more rapidly and more precisely than other recognition systems. Three authors Alexey Bochkovskiy, the Russian developer who built the YOLO Windows version, Chien-Yao Wang, and Hong-Yuan Mark Liao, are accounted for in this work and the entire code is available on [Github](https://github.com/AlexeyAB/darknet).
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This YOLOv4 library, inspired by previous YOLOv3 implementations here:
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* [Yolov3 tensorflow](https://github.com/YunYang1994/tensorflow-yolov3)
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* [Yolov3 tf2](https://github.com/zzh8829/yolov3-tf2)uses Tensorflow 2.0 and is available on this [Github](https://github.com/hunglc007/tensorflow-yolov4-tflite).
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### Prerequisites
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* YOLOv4: Optimal Speed and Accuracy of Object Detection [YOLOv4](https://arxiv.org/abs/2004.10934).
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* [darknet](https://github.com/AlexeyAB/darknet)
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