Need help with PFLD-pytorch?
Click the “chat” button below for chat support from the developer who created it, or find similar developers for support.

About the developer

polarisZhao
475 Stars 141 Forks 55 Commits 32 Opened issues

Description

PFLD pytorch Implementation

Services available

!
?

Need anything else?

Contributors list

# 53,669
Python
ncnn
pytorch
face-la...
51 commits
# 376,764
Python
ncnn
pytorch
face-la...
1 commit

PFLD-pytorch

Implementation of PFLD A Practical Facial Landmark Detector by pytorch.

1. install requirements

pip3 install -r requirements.txt

2. Datasets

  • WFLW Dataset Download

Wider Facial Landmarks in-the-wild (WFLW) 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] [Baidu Drive]
  2. WFLW Face Annotations
  3. Unzip above two packages and put them on
    ./data/WFLW/
  4. move
    Mirror98.txt
    to
    WFLW/WFLW_annotations
$ cd data 
$ python3 SetPreparation.py

3. training & testing

training :

$ python3 train.py

use tensorboard, open a new terminal ~~~ $ tensorboard --logdir=./checkpoint/tensorboard/ ~~~ testing:

$ python3 test.py

4. results:

5. pytorch -> onnx -> ncnn

Pytorch -> onnx

python3 pytorch2onnx.py

onnx -> ncnn

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

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:

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

We use cookies. If you continue to browse the site, you agree to the use of cookies. For more information on our use of cookies please see our Privacy Policy.