README.md

metadata

dataset_info:
  features:
    - name: image
      dtype: image
    - name: mask
      dtype: image
  splits:
    - name: train
      num_bytes: 119307954.15
      num_examples: 2450
    - name: validation
      num_bytes: 27229918
      num_examples: 613
    - name: test
      num_bytes: 39479824
      num_examples: 955
  download_size: 169673709
  dataset_size: 186017696.15
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
      - split: validation
        path: data/validation-*
      - split: test
        path: data/test-*
task_categories:
  - image-segmentation
size_categories:
  - 1K<n<10K

Links

• Paper: https://arxiv.org/pdf/1908.09101v2
• Repository: https://github.com/Mhaiyang/ICCV2019_MirrorNet
• Project page: https://mhaiyang.github.io/ICCV2019_MirrorNet/index.html
• We got our data from: https://github.com/Charmve/Mirror-Glass-Detection

Split info

We split the train to train and validation with the ratio 80% and 20% respectively. If you want to use the original split, you can just combine train and validation.

License info

Refer to the project page, original repository, and paper. We retrieve the dataset from third party repository.