madbg
PaddleOCR
| madbg | PaddleOCR | |
|---|---|---|
| 4 | 65 | |
| 246 | 42,471 | |
| - | 2.7% | |
| 4.4 | 9.1 | |
| about 1 year ago | 2 days ago | |
| Python | Python | |
| MIT License | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
madbg
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Debugging running Python scripts with PDB via GDB
Probably worth mention madbg⁽¹⁾, a fully-featured remote and preemptive debugger for Python with both a CLI and an API, that allows attaching to running programs preemptively (but does not require gdb).
⁽¹⁾https://github.com/kmaork/madbg
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This Week in Python
madbg – A fully-featured remote debugger for python
- A fully-featured remote debugger for Python
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Retain output sent to file from a background process
That's going to be hard; I guess you can use some debugger to attach to that process and tell it to flush. A quick google gave me https://github.com/kmaork/madbg, didn't try it, but if it works it should be to attach and run sys.stdout.flush().
PaddleOCR
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Show HN: LLM Aided OCR (Correcting Tesseract OCR Errors with LLMs)
Was this by any chance Paddle OCR https://github.com/PaddlePaddle/PaddleOCR
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OCR Solutions Uncovered: How to Choose the Best for Different Use Cases
Budget Constraints: For users with limited budgets, open-source options like Tesseract OCR or PaddleOCR provide good solutions that can be customized to meet specific business needs. Additionally, consider Klippa or API4AI OCR for affordable yet reliable OCR services that work out-of-the-box.
- Ask HN: What are you using to parse PDFs for RAG?
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PDF Hell and Practical RAG Applications
Paddle OCR
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Ask HN: I have many PDFs – what is the best local way to leverage AI for search?
If you want to run locally you can look into this https://github.com/PaddlePaddle/PaddleOCR
https://andrejusb.blogspot.com/2024/03/optimizing-receipt-pr...
But I suggest that you just skip that and use gpt-4o. They aren't actually going to steal your data.
Sort through it to find anything with a credit card number or anything ahead time.
Or you could look into InternVL..
Or a combination of PaddleOCR first and then use a strong LLM via API, like gpt-4o or llama3 70b via together.ai
If you truly must do it locally, then if you have two 3090s or 4090s it might work out. Otherwise it the LLMs may not be smart enough to give good results.
Leaving out the details of your hardware makes it impossible to give good advice about running locally. Other than, it's not really necessary.
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Leveraging GPT-4 for PDF Data Extraction: A Comprehensive Guide
PyTesseract Module [ Github ] EasyOCR Module [ Github ] PaddlePaddle OCR [ Github ]
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What is the best repo for hand written text recognition?
My default recommendation for OCR is https://github.com/PaddlePaddle/PaddleOCR but most of the examples there are not handwritten - so I'm not sure how well it'll handle it this time.
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Ask HN: Best way to perform complex OCR task in 2023?
Other than EasyOCR and Tesseract, PaddleOCR (https://github.com/PaddlePaddle/PaddleOCR) is probably the most well known open-source OCR solution.
What are you planning to do with the text after detecting / recognizing it? How fast does the detection / recognition need to be in order to be useful?
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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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How would you go about driving contextual data from images?
For images with text, if you want to do visual qa, document classification, table/key information extraction, checkout https://huggingface.co/blog/document-ai https://github.com/philschmid/document-ai-transformers https://github.com/google-research/pix2struct https://github.com/PaddlePaddle/PaddleOCR/blob/release/2.6/ppstructure/README.md
What are some alternatives?
scapy - Scapy: the Python-based interactive packet manipulation program & library.
EasyOCR - Ready-to-use OCR with 80+ supported languages and all popular writing scripts including Latin, Chinese, Arabic, Devanagari, Cyrillic and etc.
telminal - A Terminal in Telegram!
tesseract-ocr - Tesseract Open Source OCR Engine (main repository)
img2cmap - Create colormaps from images
mmocr - OpenMMLab Text Detection, Recognition and Understanding Toolbox
gdb-dashboard - Modular visual interface for GDB in Python
Tesseract.js - Pure Javascript OCR for more than 100 Languages 📖🎉🖥
ScoutSuite - Multi-Cloud Security Auditing Tool
OCRmyPDF - OCRmyPDF adds an OCR text layer to scanned PDF files, allowing them to be searched
pymg - pymg is a CLI that can interpret Python files by the Python interpreter and display the error message in a more readable way if an exception occurs.
keras-ocr - A packaged and flexible version of the CRAFT text detector and Keras CRNN recognition model.