donut
edenai-python
| donut | edenai-python | |
|---|---|---|
| 19 | 7 | |
| 5,312 | 22 | |
| 2.9% | - | |
| 3.6 | 6.1 | |
| 6 months ago | almost 2 years 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.
donut
-
Ask HN: Why are all OCR outputs so raw?
maybe this is better? https://github.com/clovaai/donut
I'm not sure
-
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
-
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?
-
[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
edenai-python
-
Which Face Detection API to choose for your project?
Here is the code in Python (GitHub repo) that allows to test Eden AI for face detection:
-
[P] AI engines aggregator (Amazon, Google, Open Source, etc.)
Here is what it looks like in Python for the first AI technologies we worked on: https://github.com/edenai/edenai-python/tree/main/ready-to-use (SDKs for other languages will be available in the coming weeks).
-
I Tried Creating My Own OCR Translator Tool Using Python and Tesseract
Very cool project! If you want try other OCR engines, you can use Eden AI gathers some nice OCR engines (Tesseract, Microsoft Azure, Google, Amazon, etc.) in one API. It's very easy to use with Python: https://github.com/edenai/edenai-python/blob/main/ready-to-use/ocr.py
-
Eden AI - How to combine Speech-to-Text (STT) and NLP (text in audio analysis)
For Python developers - ready-to-use scripts: https://github.com/edenai/edenai-python/tree/main/ready-to-use
- Eden AI - The new Python SDK
-
Python SDK - AI engines aggregator
Here's some ready-to-use examples on our GitHub. Don't hesitate to tell us what do you think about it ([[email protected]](mailto:[email protected])) and if you would use it. It would also help us if you put a star! :)
-
Python project: AI engines aggregator (Machine Translation, OCR, NLP, STT, etc.)
My teamates and I are working on Eden AI (developed in Python), an API that standardizes AI services from different providers: big cloud players (IBM Watson, AWS, GCP, etc.) but also companies more specialized on certain technologies as well as open source models. To use it with Python: https://github.com/edenai/edenai-python
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)
tesseract - Tesseract Open Source OCR Engine (main repository)
image-to-sound-python- - A python project for converting an Image into audible sound using OCR and speech synthesis
Screen-Translate - A Screen Translator/OCR Translator made by using Python and Tesseract, the user interface are made using Tkinter. All code written in python.
qlora - QLoRA: Efficient Finetuning of Quantized LLMs
konfuzio-sdk - OCR, extract and classify documents. In addition, annotate documents and build your own NLP and Computer Vision models using Python by downloading the data. Find examples in our Colab Notebooks, e. g. how to fine-tune Flair.
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"
Multi-Type-TD-TSR - Extracting Tables from Document Images using a Multi-stage Pipeline for Table Detection and Table Structure Recognition:
deepdoctection - A Repo For Document AI
DocumentInformationExtraction - Key Information Extraction From Documents: Evaluation And Generator
private-gpt - Interact with your documents using the power of GPT, 100% privately, no data leaks
langchain - ⚡ Building applications with LLMs through composability ⚡ [Moved to: https://github.com/langchain-ai/langchain]