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Nested UNet (UNet++) for Building Detection

Demo

val_img val_label output CRF denoised
Input Image Ground Truth UNet++ Output Post-prosessed by Fully Connected CRF Post-prosessed by Fully Connected CRF and Denoising

Usage

  1. Install

    $ git clone https://github.com/hashi0203/Nested-UNet-Building-Detection.git
    $ cd Nested-UNet-Building-Detection
    $ pip install -r requirements.txt
  2. Prepare data

     data
     ├── test_img
     │   ├── xxx.png
     │    ︙
     │   └── xxx.png
     ├── train_img
     │   ├── xxx.png
     │    ︙
     │   └── xxx.png
     ├── train_label
     │   ├── xxx.png
     │    ︙
     │   └── xxx.png
     ├── val_img
     │   ├── xxx.png
     │    ︙
     │   └── xxx.png
     └── val_label
         ├── xxx.png
          ︙
         └── xxx.png
     
  3. Edit config.py

  4. Train

    $ mkdir graph
    $ python train.py
  5. Edit config.py

    Set the model to use for evaluation

  6. Evaluate

    Warning: Denoising may take a long time

    $ mkdir result
    $ python evaluate.py    # without post processing
    $ python evaluate.py -c # with post processing (Fully Connected CRF)
    $ python evaluate.py -d # with post processing (Fully Connected CRF and denoising)

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