YOLO v3 implementation With pytorch

this repository only contain the detection module and we don't need the cfg from original YOLOv3, we implement it with pytorch.

This repository is based on the official code of YOLOv3 and pytorch-yolo-v3. There's also an implementation for YOLOv3 already for pytorch, but it uses a config file rather than a normal pytorch approch to defining the network. One of the goals of this repository is to remove the cfg file.

Requirements

• Python 3.5
• OpenCV
• PyTorch 0.4

Installation

• Install PyTorch-0.4.0 by selecting your environment on the website and running the appropriate command.
• Clone this repository
• Compile the nms
• convert yolov3.weights to pytorch

cd YOLOv3_Pytorch
./make.sh

mkdir weights
cd weights
wget https://pjreddie.com/media/files/yolov3.weights
cd ..
python convert_darknet.py --version coco --weights ./weights/yolov3.weights --save_name ./weights/convert_yolov3_coco.pth
# we will get the convert_yolov3_coco.pth

Train

We only train voc dataset because we don't have enough gpus to train coco datatset. This is still an experimental repository, we don't reproduce the original results very well.

dataset

merge VOC dataset

• structure

./data/datasets/VOCdevkit0712/VOC0712/Annotations
./data/datasets/VOCdevkit0712/VOC0712/ImageSets
./data/datasets/VOCdevkit0712/VOC0712/JPEGImages

• COCO

Same with COCO

train

you can train multiscale by changing data/config voc_config multiscale

• convert weights

cd weights
wget wget https://pjreddie.com/media/files/darknet53.conv.74
cd ../
python convert_darknet.py --version darknet53 --weights ./weights/darknet53.conv.74 --save_name ./weights/convert_darknet53.pth

• train yolov3

python train.py --input_wh 416 416 -b 64 --subdivisions 4 -d VOC --basenet ./weights/convert_darknet53.pth

eval

python eval.py --weights ./weights/convert_yolov3_voc.pth --dataset VOC --input_wh 416 416

darknet voc is trained by darknet, pytorch voc is trained by this repository

results

darknet voc 608	darknet voc 416	pytorch voc 608	pytorch voc 416
77.2 %	76.2%	74.7%	74.9%
27ms	18ms	27ms	18ms

Demo

python demo.py --images images --save_path ./output --weights ./weights/convert_yolov3_coco.pth -d COCO

Example

References

• YOLOv3: An Incremental Improvemet

• Original Implementation (Darknet)

• pytorch-yolo-v3

• pytorch-yolo2