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FGI-Matting

The official repository for Deep Image Matting with Flexible Guidance Input.

Paper: https://arxiv.org/abs/2110.10898

image

all

Requirements

  • easydict
  • numpy
  • opencv-python
  • Pillow
  • PyQt5
  • scikit-image
  • scipy
  • toml
  • torch>=1.5.0
  • torchvision

Models and supplementary data for DIM test set(Composition-1k) and Distinctions-646 test set

Google drive: https://drive.google.com/drive/folders/13qnlXUSKS5HfkfvzdMKAv7FvJ6YV_wPK?usp=sharing
百度网盘： https://pan.baidu.com/s/1ZYcbwyCIrL6G9t7pkCIBYw 提取码: zjtj

  • Weight_DIM.pth The model trained with Adobe matting dataset.

  • Weight_D646.pth The model trained with Distincions-646 dataset.

  • DIM_test_supp_data.zip Scribblemaps and Clickmaps for DIM test set.

  • D-646_test_supp_data.zip Scribblemaps and Clickmaps for Distinctions-646 test set.

Place Weight_DIM.pth and Weight_D646.pth in ./checkpoints.
Edit ./config/FGI_config to modify the path of the testset and choose the checkpoint name.

Test on DIM test set(Composition-1k)

Methods SAD MSE Grad Conn
Trimap test 30.19 0.0061 13.07 26.66
Scribblemap test 32.86 0.0090 14.18 29.09
Clickmap test 34.67 0.0112 15.45 30.96
No guidance test 36.36 0.0141 15.23 32.76

"checkpoint" in ./config/FGI_config.toml should be "Weight_DIM".
bash test.sh
Modify "guidancemap_phase" in ./config/FGI_config.toml to test on trimap, scribblemap, clickmap and No_guidance.
For further test, please use the code in ./DIM_evaluation_code and the predicted alpha mattes in ./alpha_pred.

Test on Distinctions-646 test set(Not appear in the paper)

Methods SAD MSE Grad Conn
Trimap test 28.90 0.0105 24.67 27.40
Scribblemap test 33.22 0.0131 26.93 31.38
Clickmap test 34.97 0.0146 27.60 33.11
No guidance test 36.83 0.0156 28.28 34.90

"checkpoint" in ./config/FGI_config.toml should be "Weight_D646".
bash test.sh
Modify "guidancemap_phase" in ./config/FGI_config.toml to test on trimap, scribblemap, clickmap and No_guidance.
For further test, please use the code in ./DIM_evaluation_code and the predicted alpha mattes in ./alpha_pred.

The QT Demo

Copy one of the pth file and rename it "Weight_qt_in_use.pth", also place it in ./checkpoints.
Run test_one_img_qt.py. Try images in ./testimg. It will use GPU if avaliable, otherwise it will use CPU.

demo

I recommend to use the one trained on DIM dataset.
Have fun :D

Acknowledgment

GCA-Matting: https://github.com/Yaoyi-Li/GCA-Matting