This is an unofficial Tensorflow re-implementation of PyramidBox: A Context-assisted Single Shot Face Detector, which achieves superior performance among the state-of-the-art on the two common face detection benchmarks, FDDB and WIDER FACE.
There is still a gap in performance from the paper. May be caused by several reasons:
- Without implementing data-anchor-sampling.
- Differences of data augmentation from original.
- The batch size in the paper is 16, but I used 1 because of the limitation of memory.
- Hyperparameters not mentioned in the paper.
- Differences of deep learning framework.
This is just a very casual training result. I believe you can achieve better results after trying some other hyperparameters. For example: batch size, learning rate and some parameters related to the loss function,etc.
Method | AP Easy | AP Medium | AP Hard |
---|---|---|---|
original | 96.1 | 95.0 | 88.9 |
this repo | 90.6 | 88.8 | 73.4 |
(Only tested on) Ubuntu 16.04 with:
- Python3
- Tensorflow-gpu 1.4
- OpenCV3
git clone https://github.com/EricZgw/PyramidBox.git
python makedir.py
Download PyramidBox models form BaiduYun.
Run the following script for visualization:
python demo.py
- Download pre-trained VGG16 models from here and put it to /checkpoints.
- Download WIDER FACE Datasets and convert to VOC format. Path looks like below:
datasets/
|->widerface/
| |->WIDER_train/
| |->WIDER_val/
| |->WIDER_test/
| |->Annotations/
| |->JPEGImages/
| |...
- Run the following script to generate TFRecords:
python datasets/pascalvoc_to_tfrecords.py
You can run `check_data_io.py` to check data. This step is not necessary.
- The training strategy is two-stages:
First run
train_model.py
with below setting to train additional PyramidBox layers:
self.fine_tune_vgg16 = False
- Then set
self.fine_tune_vgg16 =Ture
to runtrain_model.py
to train total network.
Run the following script for evaluation and get mAP:
python widerface_eval.py
cd eval/eval_tools
octave wider_eval.m
- Add data-anchor-sampling
- Try more logical and rigorous data augmentation
- Transfer to other backbone networks
SSD-Tensorflow
SSD_tensorflow_VOC
If you find any problems, welcome to open a new issue or contact [email protected] .