fastgron
donut
fastgron | donut | |
---|---|---|
10 | 19 | |
577 | 5,370 | |
- | 3.9% | |
9.0 | 3.6 | |
5 months ago | 6 months ago | |
C++ | Python | |
MIT License | MIT License |
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fastgron
- FLaNK Stack Weekly 12 February 2024
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On-demand JSON: A better way to parse documents?
I don't really understand what's new here compared to what SIMDJSON already knew already.
Anyways, it's the best JSON parser I found (in any language)amazing, I implemented https://github.com/adamritter/fastgron on top of it because of the in demand library performance.
One problem with the library was that it needed extra padding at the end of the JSON, so it didn't support streaming / memory mapping.
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Make JSON Greppable
Thanks, it's a clear bug. I created a new issue for it: https://github.com/adamritter/fastgron/issues/19
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Jaq – A jq clone focused on correctness, speed, and simplicity
And also https://github.com/adamritter/fastgron that I've just discovered.
- FLaNK Stack Weekly 29 may 2023
- fastgron: A JSON to GRON Converter That's 40 Times Faster Than Gron
- Show HN: Fastgron: A JSON to GRON Converter That's 80 Times Faster Than Gron
donut
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Ask HN: Why are all OCR outputs so raw?
maybe this is better? https://github.com/clovaai/donut
I'm not sure
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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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New to ML, looking for some GPU and learning material info
I am also interested in experimenting with something like DONUT (https://github.com/clovaai/donut) but I have never seen anything on what the VRAM expectations are for something like this. Does anyone know also if there are any newer better models than this for document parsing as well? Or what the VRAM requirements for something like this tend to be?
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[D] Is there a good ai model for image-to-text where the images are diagrams and screenshots of interfaces?
Here are a few useful resources you could start with: [Pix2Struct by Google Research](https://github.com/google-research/pix2struct) might be a valuable tool, although it will most likely need some fine-tuning to fit your specifics. You can also find some fine-tuned models on HuggingFace by searching 'pix2struct'. Another option worth considering is [DonutI](https://github.com/clovaai/donut). Like Pix2Struct, fine-tuning likely needed to meet your requirements. Tesseract OCR is another alternative, particularly for handling text. It's primarily designed for pages of text, think books, but with some tweaking and specific flags, it can process tables as well as text chunks in regions of a screenshot. Bit too much tweaking for my taste. As I'm also in search of OCR tools for UI and chart screenshots, so share if you find something else.
- How to Automate Document Extraction from Insurance Documents
- FLaNK Stack Weekly 29 may 2023
- Donut: OCR-Free Document Understanding Transformer
What are some alternatives?
jikkou - The Open source Resource as Code framework for Apache Kafka
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)
Propan - Propan is a powerful and easy-to-use Python framework for building event-driven applications that interact with any MQ Broker
image-to-sound-python- - A python project for converting an Image into audible sound using OCR and speech synthesis
kafka-native - Kafka broker compiled to native using Quarkus and GraalVM.
qlora - QLoRA: Efficient Finetuning of Quantized LLMs
Deepstream - yolov5, yolov8, segmenations, face, pose, keypoints on deepstream
CascadeTabNet - This repository contains the code and implementation details of the CascadeTabNet paper "CascadeTabNet: An approach for end to end table detection and structure recognition from image-based documents"
trogon - Easily turn your Click CLI into a powerful terminal application
Multi-Type-TD-TSR - Extracting Tables from Document Images using a Multi-stage Pipeline for Table Detection and Table Structure Recognition:
datalakeStudio - Python+VueJS application to load, explore, combine,transform and deliver data
deepdoctection - A Repo For Document AI