YapengTian/Single-Image-Super-Resolution

• highreadme#1

  Reposition the README's opening to clarify the repo's core purpose

  Why:

  CURRENT

  A list of resources for example-based single image super-resolution, inspired by Awesome-deep-vision and Awesome Computer Vision .

  COPY-PASTE FIX

  Copy

  A comprehensive collection of state-of-the-art single-image super-resolution (SISR) methods, including unified PyTorch implementations for popular models like SRCNN, EDSR, ESRGAN, and SwinIR. This repository serves as both a resource list and a practical framework for researchers and developers.

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• hightopics#2

  Add relevant topics to the repository

  Why:

  COPY-PASTE FIX

  Copy

  super-resolution, single-image-super-resolution, deep-learning, computer-vision, pytorch, image-enhancement, sr-models, image-processing

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• highlicense#3

  Add a LICENSE file to the repository root

  Why:

  COPY-PASTE FIX

  Copy

  Create a `LICENSE` file in the repository root with a standard open-source license (e.g., MIT, Apache-2.0, or GPL-3.0). For example, for MIT:
  
  ```
  MIT License
  
  Copyright (c) [YEAR] [FULL NAME]
  
  Permission is hereby granted, free of charge, to any person obtaining a copy
  of this software and associated documentation files (the "Software"), to deal
  in the Software without restriction, including without limitation the rights
  to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
  copies of the Software, and to permit persons to whom the Software is
  furnished to do so, subject to the following conditions:
  
  The above copyright notice and this permission notice shall be included in all
  copies or substantial portions of the Software.
  
  THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
  IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
  FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
  AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
  LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
  OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
  SOFTWARE.
  ```

  OpenDoneDismiss

Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

• CATEGORY QUERY

  How to increase the resolution of a single image using AI models?

  you: not recommended
  AI recommended (in order):

  1. Upscayl
  2. Real-ESRGAN
  3. Topaz Photo AI
  4. Waifu2x
  5. SwinIR
  6. Let's Enhance

  AI recommended 6 alternatives but never named YapengTian/Single-Image-Super-Resolution. This is the gap to close.

  Show full AI answer
• CATEGORY QUERY

  Compare state-of-the-art methods for example-based image resolution enhancement.

  you: not recommended
  AI recommended (in order):

  1. ESRGAN
  2. Real-ESRGAN
  3. SwinIR
  4. EDSR
  5. RCAN
  6. SRGAN

  AI recommended 6 alternatives but never named YapengTian/Single-Image-Super-Resolution. This is the gap to close.

  Show full AI answer

• Metadata completeness

  warn

  Suggestion:

• README presence

  pass

• Compared to common alternatives in this category, what is the core differentiator of YapengTian/Single-Image-Super-Resolution?

  pass
  ✓AI named YapengTian/Single-Image-Super-Resolution explicitly

  AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

• If a team adopts YapengTian/Single-Image-Super-Resolution in production, what risks or prerequisites should they evaluate first?

  pass
  ✓AI named YapengTian/Single-Image-Super-Resolution explicitly

  AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

• In one sentence, what problem does the repo YapengTian/Single-Image-Super-Resolution solve, and who is the primary audience?

  pass
  ⚠AI did not name YapengTian/Single-Image-Super-Resolution — likely talking about a different project

  AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?