SDV
keras-ocr
| SDV | keras-ocr | |
|---|---|---|
| 59 | 4 | |
| 2,141 | 1,332 | |
| 2.4% | - | |
| 9.4 | 3.5 | |
| 7 days ago | 6 months ago | |
| Python | Python | |
| GNU General Public License v3.0 or later | MIT License |
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.
SDV
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Synthetic data generation for tabular data
Can someone help me understand the licensing of this?
https://github.com/sdv-dev/SDV/blob/main/LICENSE
It was MIT licensed up until 2022 where it was changed to what it is now, where they say that it will become MIT again 4 years after release... but is that from when the license was changed or the first release of the software in GitHub?
- SDV: NEW Data - star count:1441.0
- FLaNK Stack Weekly for 30 April 2023
- SDV: NEW Data - star count:1196.0
keras-ocr
- FLaNK Stack Weekly for 30 April 2023
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Ask HN: Best pretrained OCR model for dashcam footage?
I'm trying to detect things like speed limits, stop signs, retail building signs from a relatively low quality dashcam. The video is 1440p, but the optics aren't great.
So far I've been using generic OCR models like [1] and [2], but the results aren't great.
[1] https://github.com/faustomorales/keras-ocr
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Why do new architectures still use old models?
Yes, 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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How easy would it be/how would I go about implementing automated OCR + word count estimate after a file upload for a translation website?
There's plenty of OCR models around. If you'll have a Python server handling this, you can try keras-ocr. If you want to do this right in the browser, you can use a tflite model.
What are some alternatives?
CTGAN - Conditional GAN for generating synthetic tabular data.
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)
gretel-python-client - The Gretel Python Client allows you to interact with the Gretel REST API.
doctr - docTR (Document Text Recognition) - a seamless, high-performing & accessible library for OCR-related tasks powered by Deep Learning.
machine-learning-for-trading - Code for Machine Learning for Algorithmic Trading, 2nd edition.
mmocr - OpenMMLab Text Detection, Recognition and Understanding Toolbox
tsfresh - Automatic extraction of relevant features from time series:
pandas-ai - Chat with your database (SQL, CSV, pandas, polars, mongodb, noSQL, etc). PandasAI makes data analysis conversational using LLMs (GPT 3.5 / 4, Anthropic, VertexAI) and RAG.
Copulas - A library to model multivariate data using copulas.
Image2CAD - An application to translate raster image of CAD drawing sheet to a user editable DXF format.
TimeSynth - A Multipurpose Library for Synthetic Time Series Generation in Python
CRAFT-pytorch - Official implementation of Character Region Awareness for Text Detection (CRAFT)