mmsegmentation
mmocr
mmsegmentation | mmocr | |
---|---|---|
7 | 6 | |
7,414 | 4,086 | |
1.8% | 1.9% | |
8.2 | 4.7 | |
9 days ago | 12 days ago | |
Python | Python | |
Apache License 2.0 | Apache License 2.0 |
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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.
mmocr
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Show HN: BetterOCR combines and corrects multiple OCR engines with an LLM
Yup! But I'm still exploring options. (any recommendations would be welcomed!) Here are some candidates I'm considering:
- https://github.com/mindee/doctr
- https://github.com/open-mmlab/mmocr
- https://github.com/PaddlePaddle/PaddleOCR (honestly I don't know Mandarin so I'm a bit stuck)
- https://github.com/clovaai/donut - While it's primarily an "OCR-free document understanding transformer," I think it's worth experimenting with. Think I can sort this out by letting the LLM reason through it multiple times (although this will impact performance)
- yesterday got a suggestion to consider https://github.com/kakaobrain/pororo - I don't think development is still active but the results are pretty great on Korean text
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MMDeploy: Deploy All the Algorithms of OpenMMLab
MMOCR: OpenMMLab text detection, recognition, and understanding toolbox.
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[P]Modern open-source OCR capabilities and which model to choose
Link: https://github.com/open-mmlab/mmocr
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Text Classification Library for a Quick Baseline
For more text classification baselines (CRNN, NRTR, RubustScanner, SAR, SegOCR), checkout https://github.com/open-mmlab/mmocr They are reproducible, customizable.
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[N] MMOCR: A Toolbox for Text Detection, Recognition, and Understanding Based on PyTorch
We just released https://github.com/open-mmlab/mmocr, a new member in OpenMMLab https://openmmlab.com/. This first release supports
- OCR Baselines Based on PyTorch
What are some alternatives?
Pytorch-UNet - PyTorch implementation of the U-Net for image semantic segmentation with high quality images
PaddleOCR - Awesome multilingual OCR toolkits based on PaddlePaddle (practical ultra lightweight OCR system, support 80+ languages recognition, provide data annotation and synthesis tools, support training and deployment among server, mobile, embedded and IoT devices)
Swin-Transformer-Semantic-Segmentation - This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows" on Semantic Segmentation.
CRAFT-pytorch - Official implementation of Character Region Awareness for Text Detection (CRAFT)
segmentation_models.pytorch - Segmentation models with pretrained backbones. PyTorch.
doctr - docTR (Document Text Recognition) - a seamless, high-performing & accessible library for OCR-related tasks powered by Deep Learning.
Mask_RCNN - Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow
deep-text-recognition-benchmark - Text recognition (optical character recognition) with deep learning methods, ICCV 2019
face-parsing.PyTorch - Using modified BiSeNet for face parsing in PyTorch
iam-crnn-ctc-recognition - IAM Dataset Handwriting Recognition Using CRNN, CTC Loss, DeepSpeech Beam Search, And KenLM Scorer
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.
keras-ocr - A packaged and flexible version of the CRAFT text detector and Keras CRNN recognition model.