# pytorch-YOLOv4

**Repository Path**: wk_09/pytorch-YOLOv4

## Basic Information

- **Project Name**: pytorch-YOLOv4
- **Description**: Minimal PyTorch implementation of YOLOv4
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2020-04-27
- **Last Updated**: 2020-12-19

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# Pytorch-YOLOv4

A minimal PyTorch implementation of YOLOv4.
- Paper Yolo v4: https://arxiv.org/abs/2004.10934
- Source code:https://github.com/AlexeyAB/darknet
- More details: http://pjreddie.com/darknet/yolo/

![image](https://user-gold-cdn.xitu.io/2020/4/26/171b5a6c8b3bd513?w=768&h=576&f=jpeg&s=78882)

# Inference
- download model weight https://drive.google.com/open?id=1cewMfusmPjYWbrnuJRuKhPMwRe_b9PaT
```
python demo.py cfgfile weightfile imgfile
```

- [x] Convolution weight reshape
- [x] Mish activation
- [x] route number > 2
- [x] Maxpooling
- [ ] yololayer

Reference:
- https://github.com/eriklindernoren/PyTorch-YOLOv3
- https://github.com/marvis/pytorch-caffe-darknet-convert
- https://github.com/marvis/pytorch-yolo3

```
@article{yolov4,
  title={YOLOv4: YOLOv4: Optimal Speed and Accuracy of Object Detection},
  author={Alexey Bochkovskiy, Chien-Yao Wang, Hong-Yuan Mark Liao},
  journal = {arXiv},
  year={2020}
}
```