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Top 23 Python semantic-segmentation Projects
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Swin-Transformer
This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows".
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labelme
Image Polygonal Annotation with Python (polygon, rectangle, circle, line, point and image-level flag annotation).
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WorkOS
The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.
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Pytorch-UNet
PyTorch implementation of the U-Net for image semantic segmentation with high quality images
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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.
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InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
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semantic-segmentation-pytorch
Pytorch implementation for Semantic Segmentation/Scene Parsing on MIT ADE20K dataset
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HRNet-Semantic-Segmentation
The OCR approach is rephrased as Segmentation Transformer: https://arxiv.org/abs/1909.11065. This is an official implementation of semantic segmentation for HRNet. https://arxiv.org/abs/1908.07919
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InternImage
[CVPR 2023 Highlight] InternImage: Exploring Large-Scale Vision Foundation Models with Deformable Convolutions
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efficientdet-pytorch
A PyTorch impl of EfficientDet faithful to the original Google impl w/ ported weights
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involution
[CVPR 2021] Involution: Inverting the Inherence of Convolution for Visual Recognition, a brand new neural operator
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medicaldetectiontoolkit
The Medical Detection Toolkit contains 2D + 3D implementations of prevalent object detectors such as Mask R-CNN, Retina Net, Retina U-Net, as well as a training and inference framework focused on dealing with medical images.
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PaddleViT
:robot: PaddleViT: State-of-the-art Visual Transformer and MLP Models for PaddlePaddle 2.0+
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Swin-Transformer-Semantic-Segmentation
This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows" on Semantic Segmentation.
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MaskDINO
[CVPR 2023] Official implementation of the paper "Mask DINO: Towards A Unified Transformer-based Framework for Object Detection and Segmentation"
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Project mention: Samsung expected to report 80% profit plunge as losses mount at chip business | news.ycombinator.com | 2023-10-10> there is really nothing that "normal" AI requires that is bound to CUDA. pyTorch and Tensorflow are backend agnostic (ideally...).
There are a lot of optimizations that CUDA has that are nowhere near supported in other software or even hardware. Custom cuda kernels also aren't as rare as one might think, they will often just be hidden unless you're looking at libraries. Our more well known example is going to be StyleGAN[0] but it isn't uncommon to see elsewhere, even in research code. Swin even has a cuda kernel[1]. Or find torch here[1] (which github reports that 4% of the code is cuda (and 42% C++ and 2% C)). These things are everywhere. I don't think pytorch and tensorflow could ever be agnostic, there will always be a difference just because you have to spend resources differently (developing kernels is time resource). We can draw evidence by looking at Intel MKL, which is still better than open source libraries and has been so for a long time.
I really do want AMD to compete in this space. I'd even love a third player like Intel. We really do need competition here, but it would be naive to think that there's going to be a quick catchup here. AMD has a lot of work to do and posting a few bounties and starting a company (idk, called "micro grad"?) isn't going to solve the problem anytime soon.
And fwiw, I'm willing to bet that most AI companies would rather run in house servers than from cloud service providers. The truth is that right now just publishing is extremely correlated to compute infrastructure (doesn't need to be but with all the noise we've just said "fuck the poor" because rejecting is easy) and anyone building products has costly infrastructure.
[0] https://github.com/NVlabs/stylegan2-ada-pytorch/blob/d72cc7d...
[1] https://github.com/microsoft/Swin-Transformer/blob/2cb103f2d...
[2] https://github.com/pytorch/pytorch/tree/main/aten/src
Project mention: Instance segmentation of small objects in grainy drone imagery | /r/computervision | 2023-12-09Also, I’d suggest considering switching to the segmentation-models library - it provides U-Net models with a variety of pretrained backbones of as encoders. The author also put out a PyTorch version. https://github.com/qubvel/segmentation_models.pytorch https://github.com/qubvel/segmentation_models
Project mention: Looking for Point Cloud deep learning, training sources | /r/deeplearning | 2023-07-13I already have a basic understanding with Open3D-ML and manage to get examples for training to work. However, my knowledge is not sufficient to transfer this to my own data or model deployment.
Project mention: A look at Apple’s new Transformer-powered predictive text model | news.ycombinator.com | 2023-09-16I'm pretty fatigued on constantly providing references and sources in this thread but an example of what they've made availably publicly:
https://github.com/snap-research/EfficientFormer
Project mention: I don't if this is right sub but can someone say what's going wrong | /r/StableDiffusion | 2023-06-30
NOTE:
The open source projects on this list are ordered by number of github stars.
The number of mentions indicates repo mentiontions in the last 12 Months or
since we started tracking (Dec 2020).
Python semantic-segmentation related posts
- OPENSCENE can identify objects, materials, affordances, activities, and room types in complex 3D scenes, all using a single model trained without any labeled 3D data
- What do you guys think of InternImage? - 65.5 mAP on COCO
- [D] What do you guys think of InternImage?
- [R] Mask DINO: Towards A Unified Transformer-based Framework for Object Detection and Segmentation
- Swin Transformer: Hierarchical Vision Transformer using Shifted Windows
- Swin Transformer: Hierarchical Vision Transformer Using Shifted Windows
- HFT: NEW Extended Research - star count:105.0
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A note from our sponsor - SaaSHub
www.saashub.com | 24 Apr 2024
Index
What are some of the best open-source semantic-segmentation projects in Python? This list will help you:
| Project | Stars | |
|---|---|---|
| 1 | Swin-Transformer | 12,917 |
| 2 | labelme | 12,300 |
| 3 | segmentation_models.pytorch | 8,800 |
| 4 | Pytorch-UNet | 8,358 |
| 5 | PaddleSeg | 8,227 |
| 6 | mmsegmentation | 7,380 |
| 7 | gluon-cv | 5,751 |
| 8 | semantic-segmentation-pytorch | 4,834 |
| 9 | HRNet-Semantic-Segmentation | 3,018 |
| 10 | InternImage | 2,299 |
| 11 | face-parsing.PyTorch | 2,084 |
| 12 | Open3D-ML | 1,660 |
| 13 | efficientdet-pytorch | 1,550 |
| 14 | involution | 1,306 |
| 15 | medicaldetectiontoolkit | 1,266 |
| 16 | PaddleViT | 1,169 |
| 17 | Swin-Transformer-Semantic-Segmentation | 1,081 |
| 18 | PixelLib | 1,013 |
| 19 | MaskDINO | 1,012 |
| 20 | EfficientFormer | 940 |
| 21 | GSCNN | 906 |
| 22 | UniFormer | 777 |
| 23 | nncf | 777 |
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