Top 23 Python OCR Projects
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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)
PaddleOCR
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EasyOCR
Ready-to-use OCR with 80+ supported languages and all popular writing scripts including Latin, Chinese, Arabic, Devanagari, Cyrillic and etc.
Project mention: [P] Training to read PDF documents. Any ideas? | reddit.com/r/MachineLearning | 2022-05-20If all you need to do is OCR, check out https://github.com/JaidedAI/EasyOCR , it's a similar architecture to the cloud services, without all the $. You'll end up with extracted text and bounding boxes for it.
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Scout APM
Less time debugging, more time building. Scout APM allows you to find and fix performance issues with no hassle. Now with error monitoring and external services monitoring, Scout is a developer's best friend when it comes to application development.
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Worst case scenario, if you're not able to convert the Spl directly to a searchable PDF you can OCR them after the fact with https://github.com/ocrmypdf/OCRmyPDF
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Project mention: Looking for help with inference using TrOCR from MS | reddit.com/r/learnmachinelearning | 2022-06-22
I'm trying to use TrOCR, an OCR Transformer model from Microsoft. The model is available on Huggingface and I'm trying to use it in a colab notebook. My problem is that I cannot find how to do inference on a whole page using that model. All the examples seem to provide word snippets or line snippets for this, which is of course useless for real world scenarios. The engine itself can handle a whole image as an argument but the OCR results are garbage. My tests show the smaller the image the better the results and this seems to be confirmed by MS and their model description where it says that it was trained by breaking down an image into 16x16 segments. Can anyone understand how to do inference for a 2500x3300 A4 type image? A colab example would be great as well!
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Paperless-ng
A supercharged version of paperless: scan, index and archive all your physical documents
Apart from Paperless-NG and Papermerge there's also Docspell, Lodestone, LogicalDOC, Mayan, Teedy and probably more but I don't think that any of them might keep the structure.
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I'm going to use the Tesseract OCR engine and library, and its Python wrapper PyTesseract for text extraction. But there are numerous libraries out there to extract text from an image. In a real world application I would probably use cloud services from AWS, Google or Microsoft to handle this task.
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Project mention: Amateur programmer here. Will Rust be used in backend for software in the future? | reddit.com/r/rust | 2022-05-27
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JetBrains
Developer Ecosystem Survey 2022. Take part in the Developer Ecosystem Survey 2022 by JetBrains and get a chance to win a Macbook, a Nvidia graphics card, or other prizes. We’ll create an infographic full of stats, and you’ll get personalized results so you can compare yourself with other developers.
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AdelaiDet
AdelaiDet is an open source toolbox for multiple instance-level detection and recognition tasks.
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Project mention: [D] How to generate syntactically correct text examples for CRNN-CTC | reddit.com/r/MachineLearning | 2021-12-17
[1]: https://github.com/Belval/TextRecognitionDataGenerator
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pdftabextract
A set of tools for extracting tables from PDF files helping to do data mining on (OCR-processed) scanned documents.
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Project mention: [Question] I am trying to segment the image using python. | reddit.com/r/opencv | 2021-08-09
If you’re using tesserocr then you can use OpenCV images directly, so you can just extract the relevant image rows (e.g. query_image = main_image[prev_line:this_line]) and process then without needing to save each image.
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Recently I found out this LaTex-OCR, which can convert images of math formula and symbols to LaTeX code, and it is based on Python. I looked at the instruction on GitHub and even found this video but I still got no idea about things like Pytorch that I need to install and how am I supposed to run those commands. Can someone help me with a detailed, step-by-step guide and some errors I might encounter (because I saw a lot of people having difficulties installing these)? I don't know anything about Python so hope someone can help me out:)) This will boost my work by a lot.
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Project mention: Can anyone share some cool projects done with Python? | reddit.com/r/Python | 2022-02-13
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doctr
docTR (Document Text Recognition) - a seamless, high-performing & accessible library for OCR-related tasks powered by Deep Learning.
Project mention: DocTR: Open-Source OCR Based on TensorFlow or PyTorch | news.ycombinator.com | 2021-12-08 -
keras-ocr
A packaged and flexible version of the CRAFT text detector and Keras CRNN recognition model.
Project mention: Why do new architectures still use old models? | reddit.com/r/deeplearning | 2022-06-05Yes, you should be able to do it by replacing the the backbone and training the other parts again. The results may be better or worse than you expected. See: https://github.com/faustomorales/keras-ocr/issues/113
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Project mention: If you want to OCR your PDF, the fastest, easiest and less buggy tool out there is "pdfsandwich" | reddit.com/r/linux | 2022-05-07
I've had some success with normcap, but I'm not a heavy user.
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PaddleOCR2Pytorch
PaddleOCR inference in PyTorch. Converted from [PaddleOCR](https://github.com/PaddlePaddle/PaddleOCR)
Path №2: use the tools provided by the project https://github.com/frotms/PaddleOCR2Pytorch to convert the models of the Paddle Inference to the PTH files of Pytorch, then use the tools in Pytorch to convert the PTH files to the TorchScript files in Trace mode, and finally use PNNX in the NCNN toolbox to output them to PNNX and NCNN formats, and take the model files in NCNN format for deployment.
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Project mention: Kraken: Turn-key OCR system optimised for historical and non-Latin script | news.ycombinator.com | 2022-02-20
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Python OCR related posts
- Document management system wanted
- [Technical Article] OCR Upgrade
- PDF query?
- Why do new architectures still use old models?
- Amateur programmer here. Will Rust be used in backend for software in the future?
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Poricom VS Cloe - a user suggested alternative
2 projects | 23 May 2022
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Mayan EDMS VS formkiq-core - a user suggested alternative
2 projects | 22 May 2022
Index
What are some of the best open-source OCR projects in Python? This list will help you:
Project | Stars | |
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1 | PaddleOCR | 22,938 |
2 | EasyOCR | 15,117 |
3 | OCRmyPDF | 6,567 |
4 | unilm | 5,751 |
5 | Paperless-ng | 4,848 |
6 | pytesseract | 4,270 |
7 | layout-parser | 3,054 |
8 | AdelaiDet | 2,833 |
9 | mmocr | 2,529 |
10 | CRAFT-pytorch | 2,394 |
11 | TextRecognitionDataGenerator | 2,309 |
12 | pdftabextract | 1,992 |
13 | tesserocr | 1,646 |
14 | LaTeX-OCR | 1,623 |
15 | Papermerge | 1,577 |
16 | textshot | 1,371 |
17 | doctr | 1,110 |
18 | keras-ocr | 1,035 |
19 | receipt-parser-legacy | 701 |
20 | normcap | 431 |
21 | PaddleOCR2Pytorch | 424 |
22 | kraken | 390 |
23 | Paddle2ONNX | 383 |
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