STEGO
pytorch-segmentation
| STEGO | pytorch-segmentation | |
|---|---|---|
| 1 | 1 | |
| 683 | 1,571 | |
| - | - | |
| 0.0 | 6.7 | |
| about 1 year ago | about 1 month ago | |
| Jupyter Notebook | Jupyter Notebook | |
| MIT License | MIT License |
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STEGO
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MIT Team Introduces STEGO: An Algorithm That Can Jointly Detect And Segment Things Down To The Last Pixel Without Any Human
Code: https://github.com/mhamilton723/STEGO
pytorch-segmentation
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Any luck training Segnet?
So I have read the paper on segnet and understood its architechture, and how the corresponding model has been written on the segnet.py file. I have a dataset and segmentation masks (in PNG). I came across the code given in this repo: https://github.com/yassouali/pytorch-segmentation
What are some alternatives?
rankseg - [JMLR 2023] RankSEG: A consistent ranking-based framework for segmentation
Human-Segmentation-PyTorch - Human segmentation models, training/inference code, and trained weights, implemented in PyTorch
SegGradCAM - SEG-GRAD-CAM: Interpretable Semantic Segmentation via Gradient-Weighted Class Activation Mapping
PixelLib - Visit PixelLib's official documentation https://pixellib.readthedocs.io/en/latest/
HugsVision - HugsVision is a easy to use huggingface wrapper for state-of-the-art computer vision
Subway-Station-Hazard-Detection - This project is part of the CS course 'Systems Engineering Meets Life Sciences II' at Goethe University Frankfurt. In this Computer Vision project, we developed a first prototype of a security system which uses the surveillance cameras at subway stations to recognize dangerous situations. The training data was artificially generated by a Unity-based simulation.
super-gradients - Easily train or fine-tune SOTA computer vision models with one open source training library. The home of Yolo-NAS.