OneFormer VS rankseg

Compare OneFormer vs rankseg and see what are their differences.

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OneFormer rankseg
1 1
1,342 15
2.2% -
3.4 4.6
7 months ago 8 months ago
Jupyter Notebook Jupyter Notebook
MIT License MIT License
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.

OneFormer

Posts with mentions or reviews of OneFormer. We have used some of these posts to build our list of alternatives and similar projects.

rankseg

Posts with mentions or reviews of rankseg. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing OneFormer and rankseg you can also consider the following projects:

PaddleSeg - Easy-to-use image segmentation library with awesome pre-trained model zoo, supporting wide-range of practical tasks in Semantic Segmentation, Interactive Segmentation, Panoptic Segmentation, Image Matting, 3D Segmentation, etc.

notebooks - Examples and tutorials on using SOTA computer vision models and techniques. Learn everything from old-school ResNet, through YOLO and object-detection transformers like DETR, to the latest models like Grounding DINO and SAM.

Vision-Project-Image-Segmentation

cellpose - a generalist algorithm for cellular segmentation with human-in-the-loop capabilities

Entity - EntitySeg Toolbox: Towards Open-World and High-Quality Image Segmentation

SegGradCAM - SEG-GRAD-CAM: Interpretable Semantic Segmentation via Gradient-Weighted Class Activation Mapping

STEGO - Unsupervised Semantic Segmentation by Distilling Feature Correspondences

PixelLib - Visit PixelLib's official documentation https://pixellib.readthedocs.io/en/latest/

Human-Segmentation-PyTorch - Human segmentation models, training/inference code, and trained weights, implemented in PyTorch

18337 - 18.337 - Parallel Computing and Scientific Machine Learning

gpu-benches - collection of benchmarks to measure basic GPU capabilities