cnn-watermark-removal
Fully convolutional deep neural network to remove transparent overlays from images (by marcbelmont)
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)
cnn-watermark-removal | mmagic | |
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1 | 5 | |
1,216 | 6,602 | |
- | 1.5% | |
0.0 | 8.7 | |
about 3 years ago | 2 months ago | |
Python | Jupyter Notebook | |
- | Apache License 2.0 |
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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.
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.
cnn-watermark-removal
Posts with mentions or reviews of cnn-watermark-removal.
We have used some of these posts to build our list of alternatives
and similar projects.
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A minute of silence for this person please
There actually should be a way to remove static watermarks, at least there are AI libraries to to do so with still images, like https://github.com/marcbelmont/cnn-watermark-removal. The result will be mediocre, and it's gonna take enormous amount of time to clean up though.
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.
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What are some alternatives?
When comparing cnn-watermark-removal and mmagic you can also consider the following projects:
ImageAI - A python library built to empower developers to build applications and systems with self-contained Computer Vision capabilities
a-PyTorch-Tutorial-to-Super-Resolution - Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network | a PyTorch Tutorial to Super-Resolution