evaluate
mmsegmentation
evaluate | mmsegmentation | |
---|---|---|
3 | 7 | |
1,819 | 7,436 | |
3.0% | 2.1% | |
6.1 | 8.2 | |
7 days ago | 11 days ago | |
Python | Python | |
Apache License 2.0 | Apache License 2.0 |
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evaluate
- [D] The MMSegmentation library from OpenMMLab appears to return the wrong results when computing basic image segmentation metrics such as the Jaccard index (IoU - intersection-over-union). It appears to compute recall (sensitivity) instead of IoU, which artificially inflates the performance metrics.
- [P] Releasing 🤗 Evaluate - an evaluation library for ML
- HuggingFace/evaluate: A library for easily evaluating ML models and datasets
mmsegmentation
- [D] The MMSegmentation library from OpenMMLab appears to return the wrong results when computing basic image segmentation metrics such as the Jaccard index (IoU - intersection-over-union). It appears to compute recall (sensitivity) instead of IoU, which artificially inflates the performance metrics.
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Is there any ML model out there for room surfaces detection? (ceiling, floor, windows)
Segmentation models trained on datasets like ADE20k could probably be used for that, because it has separate classes for these things iirc. https://github.com/open-mmlab/mmsegmentation should have suitable pretrained models available.
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MMDeploy: Deploy All the Algorithms of OpenMMLab
MMSegmentation: OpenMMLab semantic segmentation toolbox and benchmark.
- Mmsegmentation - Openmmlab semantic segmentation toolbox and benchmark.
- Mmsegmentation – Openmmlab semantic segmentation toolbox and benchmark
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Semantic Segmentation models
This repo is amazing: https://github.com/open-mmlab/mmsegmentation
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What's A Simple Custom Segmentation Pipeline?
Mmsegmentation would be a good place to start for basic segmentation. They have lots of recent methods and pretained models you could fine-tune from. They also support quite a few datasets including VOC. There is a custom dataset format which looks straightforward to create.
What are some alternatives?
torch-fidelity - High-fidelity performance metrics for generative models in PyTorch
Pytorch-UNet - PyTorch implementation of the U-Net for image semantic segmentation with high quality images
datasets - 🤗 The largest hub of ready-to-use datasets for ML models with fast, easy-to-use and efficient data manipulation tools
Swin-Transformer-Semantic-Segmentation - This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows" on Semantic Segmentation.
EvalAI - :cloud: :rocket: :bar_chart: :chart_with_upwards_trend: Evaluating state of the art in AI
segmentation_models.pytorch - Segmentation models with pretrained backbones. PyTorch.
avalanche - Avalanche: an End-to-End Library for Continual Learning based on PyTorch.
Mask_RCNN - Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow
semantic-kitti-api - SemanticKITTI API for visualizing dataset, processing data, and evaluating results.
face-parsing.PyTorch - Using modified BiSeNet for face parsing in PyTorch
pycm - Multi-class confusion matrix library in Python
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.