https://github.com/polarisZhao/PFLD-pytorch

PFLD pytorch Implementation
https://github.com/polarisZhao/PFLD-pytorch

face-landmark-detection ncnn pfld pfld-ncnn pfld-pytorch pytorch

Last synced: 13 days ago
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PFLD pytorch Implementation

• Host: GitHub
• URL: https://github.com/polarisZhao/PFLD-pytorch
• Owner: polarisZhao
• Created: 2019-08-25T05:05:29.000Z (about 5 years ago)
• Default Branch: master
• Last Pushed: 2022-06-21T22:46:24.000Z (over 2 years ago)
• Last Synced: 2024-08-01T05:12:26.152Z (3 months ago)
• Topics: face-landmark-detection, ncnn, pfld, pfld-ncnn, pfld-pytorch, pytorch
• Language: Python
• Homepage:
• Size: 25 MB
• Stars: 792
• Watchers: 11
• Forks: 196
• Open Issues: 47
• Metadata Files:
  • Readme: README.md

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• awesome-ncnn - PFLD-pytorch

README

        
# PFLD-pytorch

Implementation of  PFLD A Practical Facial Landmark Detector by pytorch.

#### 1. install requirements

~~~shell

pip3 install -r requirements.txt

~~~

#### 2. Datasets

- **WFLW Dataset Download**

​    [Wider Facial Landmarks in-the-wild (WFLW)](https://wywu.github.io/projects/LAB/WFLW.html) is a new proposed face dataset. It contains 10000 faces (7500 for training and 2500 for testing)  with 98 fully manual annotated landmarks.

1. WFLW Training and Testing images [[Google Drive](https://drive.google.com/file/d/1hzBd48JIdWTJSsATBEB_eFVvPL1bx6UC/view?usp=sharing)] [[Baidu Drive](https://pan.baidu.com/s/1paoOpusuyafHY154lqXYrA)]

2. WFLW  [Face Annotations](https://wywu.github.io/projects/LAB/support/WFLW_annotations.tar.gz)

3. Unzip above two packages and put them on `./data/WFLW/`

4. move `Mirror98.txt` to `WFLW/WFLW_annotations`

~~~shell

$ cd data 

$ python3 SetPreparation.py

~~~

#### 3. training & testing

training :

~~~shell

$ python3 train.py

~~~

use tensorboard, open a new terminal

~~~

$ tensorboard  --logdir=./checkpoint/tensorboard/

~~~

testing:

~~~shell

$ python3 test.py

~~~

#### 4. results:

![](./results/example.png)

#### 5. pytorch -> onnx -> ncnn

**Pytorch -> onnx**

~~~~shell

python3 pytorch2onnx.py

~~~~

**onnx -> ncnn**

how to build :https://github.com/Tencent/ncnn/wiki/how-to-build

~~~shell

cd ncnn/build/tools/onnx

./onnx2ncnn pfld-sim.onnx pfld-sim.param pfld-sim.bin

~~~

Now you can use **pfld-sim.param** and **pfld-sim.bin** in ncnn:

~~~cpp

ncnn::Net pfld;

pfld.load_param("path/to/pfld-sim.param");

pfld.load_model("path/to/pfld-sim.bin");

cv::Mat img = cv::imread(imagepath, 1);

ncnn::Mat in = ncnn::Mat::from_pixels_resize(img.data, ncnn::Mat::PIXEL_BGR, img.cols, img.rows, 112, 112);

const float norm_vals[3] = {1/255.f, 1/255.f, 1/255.f};

in.substract_mean_normalize(0, norm_vals);

ncnn::Extractor ex = pfld.create_extractor();

ex.input("input_1", in);

ncnn::Mat out;

ex.extract("415", out);

~~~

#### 6. reference: 

 PFLD: A Practical Facial Landmark Detector https://arxiv.org/pdf/1902.10859.pdf

Tensorflow Implementation: https://github.com/guoqiangqi/PFLD