mirror of
https://github.com/pjreddie/darknet.git
synced 2023-08-10 21:13:14 +03:00
Convolutional Neural Networks
cfg | ||
data | ||
examples | ||
include | ||
python | ||
scripts | ||
src | ||
.gitignore | ||
LICENSE | ||
LICENSE.fuck | ||
LICENSE.gen | ||
LICENSE.gpl | ||
LICENSE.meta | ||
LICENSE.mit | ||
LICENSE.v1 | ||
Makefile | ||
README.md |
Darknet
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
Scaled-YOLOv4:
-
paper (CVPR 2021): https://openaccess.thecvf.com/content/CVPR2021/html/Wang_Scaled-YOLOv4_Scaling_Cross_Stage_Partial_Network_CVPR_2021_paper.html
-
source code - Pytorch (use to reproduce results): https://github.com/WongKinYiu/ScaledYOLOv4
-
source code - Darknet: https://github.com/AlexeyAB/darknet
YOLOv4:
-
source code: https://github.com/AlexeyAB/darknet
For more information see the Darknet project website.
https://paperswithcode.com/sota/object-detection-on-coco
AP50:95 - FPS (Tesla V100) Paper: https://arxiv.org/abs/2011.08036
Citation
@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}
}