项目作者: AbhishekSinghDhadwal

项目描述 :
An experimental implementation of MultiRes-U-Net for facial feature segmentation using the CelebAMaskHQ dataset.
高级语言: Jupyter Notebook
项目地址: git://github.com/AbhishekSinghDhadwal/MRUNet-Masking.git
创建时间: 2020-04-23T13:45:08Z
项目社区:https://github.com/AbhishekSinghDhadwal/MRUNet-Masking

开源协议:Apache License 2.0

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MRUNet-Masking

An experimental implementation of MultiRes-U-Net for facial feature segmentation using the CelebAMaskHQ dataset.

The aim is to utilise and discover the compatibility provided by
MultiResUNet models, originally utilised for Medical Image segmentation, and check the
feasibility of utilising the aforementioned method in order to provide segmentation of facial
features (lips and eyes in our case).

Refer the pdf for further details on the documentation, code implemented and directions to follow before running the notebooks.

NOTE: The original implementation was created on Google Colab, and can be tested here with the sample implementations provided. I would recommend colab for viewing and using these notebooks for any and all purposes as many “improvements” are made in order to compensate for restraints pertaining to both Google Drive and Google Colab (eg. The workaround notebooks for time and RAM restraints in the /WorkAroundNB section of this repo) which are visible in the notebook code and comments.

Link to the CelebAMask-HQ dataset used for this investigation

Link to the original MultiRes-U-Net implementation is here.

Demo Picture
Output for a random image using the FD10 model in the project.