YoloV3 Face and Hand

Implement Face and Hand detection using keras-yolo3.

Requirements

• Keras 2.2.4 or lower (Issue : qqwweee/keras-yolo3#544)
• keras2onnx 1.5.1 (1.5.2 failed to convert onnx)
• keras-yolo3 (checked on version Jul 31, 2018 e6598d13c703029b2686bc2eb8d5c09badf42992)
• Python 3.5 or later
• OpenCV

Install

git submodule init
git submodule update

Reference

• keras-yolo3 : https://github.com/qqwweee/keras-yolo3
• keras2onnx : https://github.com/onnx/keras-onnx/tree/master/applications/yolov3

Face detection

Create dataset

Download fddb dataset (FDDB-folds and originalPics folder) and put in the each folder.

http://vis-www.cs.umass.edu/fddb/

Folder layout examples.

f:/fddb/FDDB-folds/*.txt
f:/fddb/originalPics/2002/*
f:/fddb/originalPics/2003/*

Create annotation data.

python annotation.py f:/fddb/

Training

Training from 2845 pictures.

python train.py f:/fddb/ ./model_data/face_classes.txt ./model_data/tiny_yolo_anchors.txt

This is an output data path.

./model_data/log/trained_weights_final.h5

Convert to ONNX

cd keras-onnx
python keras-yolo3-to-onnx.py ../model_data/logs/trained_weights_final.h5 ../model_data/face_classes.txt ../model_data/tiny_yolo_anchors.txt ../model_data/ax_face.onnx

Inference using ONNX Runtime

cd keras-onnx
python inference.py ../model_data/ax_face.onnx ../model_data/face_classes.txt ../images/couple.jpg output.jpg

Convert to ailia SDK

Optimize onnx file and export prototxt file

cd onnx-ailia
python onnx_optimizer.py --yolov3 ../model_data/ax_face.onnx
python onnx2prototxt ../model_data/ax_face.opt.onnx

Inference using ailia SDK

Inference using detector API

cd onnx-ailia
python inference.py ../model_data/ax_face.opt.onnx ../model_data/face_classes.txt ../images/couple.jpg output.jpg

Hand detection

Create dataset

Download vivahand dataset and put in the each folder.

http://cvrr.ucsd.edu/vivachallenge/index.php/hands/hand-detection/

Folder layout examples.

f:/vivahand/detectiondata/train/posGt/*.txt
f:/vivahand/detectiondata/train/pos/*.png

Create annotation data.

python annotation_hand.py f:/vivahand/

Training

Training from 5500 pictures.

python train.py f:/vivahand/ ./model_data/face_classes.txt ./model_data/tiny_yolo_anchors.txt

This is an output data path.

./model_data/log/trained_weights_final.h5

Convert to ONNX

Same as face detection