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mobile_phone_human_matting

This project provides training and testing codes to build real_time human mattig on mobile phone only based CPU. Anather repo (Fast_Portrait_Segmentation) show more details about whence the project.

requirements

• python3.5 / 3.6
• pytorch 0.4/0.4.1
• opencv-python

Usage

train

you need to prepare dataset and run ./train.sh.

test

use pre_trained model ./pre_train/erd_seg_matting.

test camera, you need a camera, run ./camera.sh. test image, run ./test.sh.

Speed Analysis

Platform : ncnn.

(use this tools convert the pytorch model to ncnn.)

Mobile phone: Samsung Galaxy S8+(cpu).

Demo video on my iphone 6 (baiduyun)

References

paper

• [1] U-Net: Convolutional Networks for Biomedical Image Segmentation
• [2] Fast Deep Matting for Portrait Animation on Mobile Phone
• [3] ERFNet: Efficient Residual Factorized ConvNet for Real-time Semantic Segmentation
• [4] ShuffleSeg: Real-time Semantic Segmentation Network

repos

• pytorch-fast-matting-portrait
• ESPNet
• Fast_Portrait_Segmentation
• Semantic_Human_Matting