mmocr
mmaction2
| mmocr | mmaction2 | |
|---|---|---|
| 6 | 5 | |
| 4,086 | 3,916 | |
| 1.9% | 2.0% | |
| 4.7 | 7.2 | |
| 14 days ago | 28 days ago | |
| Python | Python | |
| Apache License 2.0 | Apache License 2.0 |
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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
mmaction2
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How good does contextual action recognition get?
Mmaction2: https://github.com/open-mmlab/mmaction2 Has some examples.
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MMDeploy: Deploy All the Algorithms of OpenMMLab
MMAction2: OpenMMLab's next-generation action understanding toolbox and benchmark.
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[D] Deep Learning Framework for C++.
I agree with you for most of the time this can work but there are some models that have certain layers that are not supported by ONNX. An example would be Spatiotemporal models in mmaction2 from open-mmlab.
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Textbook or blogs for video understanding
No book or blog, but a great framework: https://github.com/open-mmlab/mmaction2
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Applications of Deep Neural Networks [pdf]
shameless ad: try mmaction2, where every result is reproducible https://github.com/open-mmlab/mmaction2 . Modelzoo: https://mmaction2.readthedocs.io/en/latest/modelzoo.html
What are some alternatives?
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)
mmpose - OpenMMLab Pose Estimation Toolbox and Benchmark.
CRAFT-pytorch - Official implementation of Character Region Awareness for Text Detection (CRAFT)
compare_gan - Compare GAN code.
doctr - docTR (Document Text Recognition) - a seamless, high-performing & accessible library for OCR-related tasks powered by Deep Learning.
mmflow - OpenMMLab optical flow toolbox and benchmark
deep-text-recognition-benchmark - Text recognition (optical character recognition) with deep learning methods, ICCV 2019
temporal-shift-module - [ICCV 2019] TSM: Temporal Shift Module for Efficient Video Understanding
iam-crnn-ctc-recognition - IAM Dataset Handwriting Recognition Using CRNN, CTC Loss, DeepSpeech Beam Search, And KenLM Scorer
Video-Dataset-Loading-Pytorch - Generic PyTorch dataset implementation to load and augment VIDEOS for deep learning training loops.
keras-ocr - A packaged and flexible version of the CRAFT text detector and Keras CRNN recognition model.
mmrotate - OpenMMLab Rotated Object Detection Toolbox and Benchmark