Shypd.aiThe largest open index of AI toolssiggraph2017_inpainting is an Open Source Content & Design tool that provides code for globally and locally consistent image completion. It allows users to fill in missing regions of images with deep convolutional networks.
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siggraph2017_inpainting offers an open-source implementation of the research paper 'Globally and Locally Consistent Image Completion'. This tool utilizes a deep convolutional network to intelligently fill in missing or damaged regions within images of arbitrary resolutions and shapes. It employs both global and local context discriminators to ensure the completed areas are visually consistent with the surrounding image. The project provides pre-trained models, including one for free-form holes on the Places2 dataset and another for face completion on the CelebA dataset, making it suitable for various image restoration and content generation tasks. Users can download models and run the inpainting process via command-line scripts.
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