Real-ESRGAN-Video-Batch-Process VS Real-ESRGAN-ncnn-vulkan

Compare Real-ESRGAN-Video-Batch-Process vs Real-ESRGAN-ncnn-vulkan and see what are their differences.

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Real-ESRGAN-Video-Batch-Process Real-ESRGAN-ncnn-vulkan
1 38
23 1,358
- -
0.0 0.0
about 2 years ago 6 months ago
Jupyter Notebook C
- GNU General Public License v3.0 or later
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Real-ESRGAN-Video-Batch-Process

Posts with mentions or reviews of Real-ESRGAN-Video-Batch-Process. We have used some of these posts to build our list of alternatives and similar projects.

Real-ESRGAN-ncnn-vulkan

Posts with mentions or reviews of Real-ESRGAN-ncnn-vulkan. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-12-07.

What are some alternatives?

When comparing Real-ESRGAN-Video-Batch-Process and Real-ESRGAN-ncnn-vulkan you can also consider the following projects:

GFPGAN-for-Video-SR - A colab notebook for video super resolution using GFPGAN

realsr-ncnn-vulkan - RealSR super resolution implemented with ncnn library

Real-ESRGAN - Real-ESRGAN aims at developing Practical Algorithms for General Image/Video Restoration.

cupscale - Image Upscaling GUI based on ESRGAN

dl-colab-notebooks - Try out deep learning models online on Google Colab

CodeFormer - [NeurIPS 2022] Towards Robust Blind Face Restoration with Codebook Lookup Transformer

Real-ESRGAN-colab - A Real-ESRGAN model trained on a custom dataset

SwinIR - SwinIR: Image Restoration Using Swin Transformer (official repository)

Waifu2x-Extension-GUI - Video, Image and GIF upscale/enlarge(Super-Resolution) and Video frame interpolation. Achieved with Waifu2x, Real-ESRGAN, Real-CUGAN, RTX Video Super Resolution VSR, SRMD, RealSR, Anime4K, RIFE, IFRNet, CAIN, DAIN, and ACNet.

Anime4K - A High-Quality Real Time Upscaler for Anime Video

GCloneLab - A Google Colab Notebook for running GClone, an RClone mod that allows multiple Google Service Account configuration. Created for easy use of GClone

chaiNNer - A flowchart/node-based image processing GUI aimed at making chaining image processing tasks (especially upscaling done by neural networks) easy, intuitive, and customizable. [Moved to: https://github.com/chaiNNer-org/chaiNNer]