mmgeneration VS mmagic

Compare mmgeneration vs mmagic and see what are their differences.

mmgeneration

MMGeneration is a powerful toolkit for generative models, based on PyTorch and MMCV. (by open-mmlab)
Generative Gan Pytorch mmcv Openmmlab generative-adversarial-network diffusion-models
Source Code
mmgeneration.readthedocs.io
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mmagic

OpenMMLab Multimodal Advanced, Generative, and Intelligent Creation Toolbox. Unlock the magic 🪄: Generative-AI (AIGC), easy-to-use APIs, awsome model zoo, diffusion models, for text-to-image generation, image/video restoration/enhancement, etc. (by open-mmlab)
super-resolution inpainting matting image-generation generative-adversarial-network Pytorch Deep Learning video-interpolation video-frame-interpolation video-super-resolution Computer Vision Image Editing Image processing image-synthesis diffusion text2image aigc generative-ai diffusion-models
Source Code
mmagic.readthedocs.io
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mmgeneration mmagic
2 5
1,801 6,570
3.2% 2.6%
2.4 8.7
8 months ago about 1 month ago
Python Jupyter Notebook
Apache License 2.0 Apache License 2.0
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

mmgeneration

Posts with mentions or reviews of mmgeneration. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-11-21.

mmagic

Posts with mentions or reviews of mmagic. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-12-18.

What are some alternatives?

When comparing mmgeneration and mmagic you can also consider the following projects:

anomalib - An anomaly detection library comprising state-of-the-art algorithms and features such as experiment management, hyper-parameter optimization, and edge inference.

a-PyTorch-Tutorial-to-Super-Resolution - Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network | a PyTorch Tutorial to Super-Resolution

mmrotate - OpenMMLab Rotated Object Detection Toolbox and Benchmark

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

mim - MIM Installs OpenMMLab Packages

Image-Super-Resolution-via-Iterative-Refinement - Unofficial implementation of Image Super-Resolution via Iterative Refinement by Pytorch

pytorch-CycleGAN-and-pix2pix - Image-to-Image Translation in PyTorch

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

rich-text-to-image - Rich-Text-to-Image Generation

cnn-watermark-removal - Fully convolutional deep neural network to remove transparent overlays from images

mmtracking - OpenMMLab Video Perception Toolbox. It supports Video Object Detection (VID), Multiple Object Tracking (MOT), Single Object Tracking (SOT), Video Instance Segmentation (VIS) with a unified framework.

Deep-Exemplar-based-Video-Colorization - The source code of CVPR 2019 paper "Deep Exemplar-based Video Colorization".

mmgeneration vs anomalib mmagic vs a-PyTorch-Tutorial-to-Super-Resolution mmgeneration vs mmrotate mmagic vs Real-ESRGAN mmgeneration vs mim mmagic vs Image-Super-Resolution-via-Iterative-Refinement mmgeneration vs pytorch-CycleGAN-and-pix2pix mmagic vs Real-ESRGAN-colab mmgeneration vs rich-text-to-image mmagic vs cnn-watermark-removal mmgeneration vs mmtracking mmagic vs Deep-Exemplar-based-Video-Colorization