Pyramidbox.pytorch

PyramidBox: A Context-assisted Single Shot Face Detector.##

A PyTorch Implementation of PyramidBox

Description

I train pyramidbox with pytorch and the result approaches the original paper result,the pretrained model can be downloaded in vgg,the final model can be downloaded in Pyramidbox.the AP in WIDER FACE as following:

| | Easy MAP | Medium MAP | hard MAP | | -------- | ---------|------------| --------- | | origin paper| 0.960 | 0.948 | 0.888 | | this repo | 0.948 | 0.938 | 0.880 |

the AP in AFW,PASCAL,FDDB as following:

| AFW | PASCAL | FDDB | | --------- |-----------| ---------| | 99.65 | 99.02 | 0.983 |

the gap is small with origin paper,I train 120k batch_size 4 which is different from paper,which maybe cause the gap,if you have more gpu ,the final result maybe better.

Requirement

• pytorch 0.3
• opencv
• numpy
• easydict

Prepare data

1. download WIDER face dataset
2. modify data/config.py
3. python prepare_wider_data.py

Train

python train.py --batch_size 4  
		--lr 5e-4

Evalution

according to yourself dataset path,modify data/config.py

1. Evaluate on AFW.

python tools/afw_test.py

2. Evaluate on FDDB

python tools/fddb_test.py

3. Evaluate on PASCAL face

python tools/pascal_test.py

4. test on WIDER FACE

python tools/wider_test.py

Demo

you can test yourself image

python demo.py

Result

<div align="center"> <img src="https://github.com/yxlijun/Pyramidbox.pytorch/blob/master/tmp/gsmarena_001.jpg" height="250px" alt="demo" > <img src="https://github.com/yxlijun/Pyramidbox.pytorch/blob/master/tmp/0_Parade_marchingband_1_488.jpg" height="200px" alt="demo" > </div>

References

• PyramidBox: A Context-assisted Single Shot Face Detector
• PyramidBox model
• ssd.pytorch