Neural Doodle – Semantic Style Transfer for Artistic Image Generation

Neural Doodle – Semantic Style Transfer for Artistic Image Generation

Neural Doodle is an open-source project that transforms simple doodles into detailed artworks by leveraging deep neural networks. It utilizes semantic style transfer to apply the artistic style of a reference image to a target sketch, enabling the creation of seamless textures, style transfers, and example-based upscaling. The system operates by matching annotated patches from the style image to the target image, facilitating intricate and context-aware artistic renderings.

Key Features

  • Semantic style transfer using annotated masks
  • Generation of seamless textures from photographs
  • Application of artistic styles to sketches and doodles
  • Example-based image upscaling
  • Support for both CPU and GPU processing
  • Customizable parameters for iterative refinement
  • Python-based implementation with Docker support
  • Includes sample images and usage examples

Project Screenshots

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