zzxvictor/License-super-resolution
A TensorFlow 2 project applying GAN-based super-resolution to reconstruct and enhance low-quality license plate images.
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This project implements Single Image Super-Resolution (SISR) specifically for license plate enhancement, inspired by state-of-the-art models like ESRGAN and Residual Dense Networks. It trains a GAN where a generator creates realistic reconstructions and a discriminator evaluates authenticity. The model is trained on the Chinese City Parking Dataset containing diverse license plate images under various conditions.
Frequently asked
- What is zzxvictor/License-super-resolution?
- A TensorFlow 2 project applying GAN-based super-resolution to reconstruct and enhance low-quality license plate images.
- Is License-super-resolution open source?
- Yes — zzxvictor/License-super-resolution is open source, released under the MIT license.
- What language is License-super-resolution written in?
- zzxvictor/License-super-resolution is primarily written in Jupyter Notebook.
- How popular is License-super-resolution?
- zzxvictor/License-super-resolution has 414 stars on GitHub.
- Where can I find License-super-resolution?
- zzxvictor/License-super-resolution is on GitHub at https://github.com/zzxvictor/License-super-resolution.