Anime-Face-Detector

A Faster-RCNN based anime face detector.

This detector in trained on 6000 training samples and 641 testing samples, randomly selected from the dataset which is crawled from top 100 pixiv daily ranking.

Thanks to OpenCV based Anime face detector written by nagadomi, which helps labelling the data.

The original implementation of Faster-RCNN using Tensorflow can be found here

Dependencies

• Python 3.6.x
• tensorflow
• opencv-python
• cython
• Pre-trained ResNet101 model

Usage

1. Clone this repository

   git clone https://github.com/qhgz2013/anime-face-detector.git

2. Download the pre-trained model
   Google Drive: here
   Baidu Netdisk: here
3. Unzip the model file into model directory
4. Build the CPU NMS model (skip this step if use PY_NMS with argument: -nms-type PY_NMS)

   make clean
   make

5. Run the demo as you want
   • Visualize the result (without output path):

     python main.py -i /path/to/image.jpg

   • Save results to a json file

     python main.py -i /path/to/image.jpg -o /path/to/output.json

     Sample output file:

     {"/path/to/image.jpg": [{"score": 0.9999708, "bbox": [551.3375, 314.50253, 729.2599, 485.25674]}]}

   • Detecting a whole directory with recursion

     python main.py -i /path/to/dir -o /path/to/output.json

   • Customize threshold

     python main.py -i /path/to/image.jpg -nms 0.3 -conf 0.8

   • Customize model path

     python main.py -i /path/to/image.jpg -model /path/to/model.ckpt

   • Customize nms type (supports CPU_NMS and PY_NMS, not supports GPU_NMS because of the complicated build process for Windows platform)

     python main.py -i /path/to/image.jpg -nms-type PY_NMS

Results

Mean AP for this model: 0.9086

Copyright info: 東方まとめ by 羽々斬

Copyright info: 【C94】桜と刀 by 幻像黒兎

Copyright info: アイドルマスター　シンデレラガールズ by 我美蘭＠１日目 東A-40a