Darknet is an open source neural network framework written in C and CUDA. It is fast, easy to install, and supports CPU and GPU computation.
Discord invite link for for communication and questions: https://discord.gg/zSq8rtW
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paper (CVPR 2021): https://openaccess.thecvf.com/content/CVPR2021/html/Wang_Scaled-YOLOv4_Scaling_Cross_Stage_Partial_Network_CVPR_2021_paper.html
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source code - Pytorch (use to reproduce results): https://github.com/WongKinYiu/ScaledYOLOv4
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source code - Darknet: https://github.com/AlexeyAB/darknet
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source code: https://github.com/AlexeyAB/darknet
For more information see the Darknet project website.
For questions or issues please use the Google Group.
AP50:95 - FPS (Tesla V100) Paper: https://arxiv.org/abs/2011.08036
@misc{bochkovskiy2020yolov4,
title={YOLOv4: Optimal Speed and Accuracy of Object Detection},
author={Alexey Bochkovskiy and Chien-Yao Wang and Hong-Yuan Mark Liao},
year={2020},
eprint={2004.10934},
archivePrefix={arXiv},
primaryClass={cs.CV}
}
@InProceedings{Wang_2021_CVPR,
author = {Wang, Chien-Yao and Bochkovskiy, Alexey and Liao, Hong-Yuan Mark},
title = {{Scaled-YOLOv4}: Scaling Cross Stage Partial Network},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2021},
pages = {13029-13038}
}
sudo apt install --reinstall g++
Fatal error: "cuda_runtime.h" not found
sudo apt install nvidia-cuda-toolkit
sudo ./darknet detector train cfg/ocr-net.data cfg/ocr-net.cfg ocr-net.weights
sudo ./darknet detector test cfg/ocr-net.data cfg/ocr-net.cfg /backup/ocr-net_final.weights /home/sahar/Documents/developments/Darknet-ocr/darknet/data/ocr-test/rgb_02030088_lp.png