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MLDBD in PyTorch

Implementation of "IEEE Transactions on Multimedia: Full-scene Defocus Blur Detection with DeFBD+ via Multi-Level Distillation Learning" in PyTorch.

Datasets DeFBD+

  • train_data:
    • source: Contains 1924 training images.
    • gt: Contains 1924 ground truth images corresponding to source images.
  • test_data:
    • CUHK+: Contains 160 testing images and it's GT.
    • DUT+: Contains 800 testing images and it's GT.

Download and unzip datasets from baidu link: https://pan.baidu.com/s/1hgph3rHPd5u8yU17iY9YpA?pwd=7qh5 password: 7qh5

Test

You can use the following command to test：

python test.py

You can use the following model to output results directly.Here is our parameters: baidu link: https://pan.baidu.com/s/1gXcObnd8Ya0i4tNR7JmO-A?pwd=qumx password: qumx

Put "checkpoint.pth" in "./saved_models".

Eval

If you want to use Fmax and MAE to evaluate the results, you can run the following code in MATLAB. It shows the PR curve and F-measure curve at the same time.

./evaluate_dbd/evaluate.m