manim VS PaddleOCR

Also check out community edition: https://www.manim.community

manim – A community-maintained Python framework for creating mathematical animations

I recently wanted to make something similar and I completely fell in love with https://www.manim.community/ created by 3B1B.

https://github.com/gumyr/build123d :

> Build123d is a python-based, parametric, boundary representation (BREP) modeling framework for 2D and 3D CAD. It's built on the Open Cascade geometric kernel and allows for the creation of complex models using a simple and intuitive python syntax. Build123d can be used to create models for 3D printing, CNC machining, laser cutting, and other manufacturing processes. Models can be exported to a wide variety of popular CAD tools such as FreeCAD and SolidWorks.

> Build123d could be considered as an evolution of CadQuery where the somewhat restrictive Fluent API (method chaining) is replaced with stateful context managers* - e.g. with blocks - thus enabling the full python toolbox: for loops, references to objects, object sorting and filtering, etc.*

"Build123d: A Python CAD programming library" (2023) https://news.ycombinator.com/item?id=37576296

BREP: Boundary representation: https://en.wikipedia.org/wiki/Boundary_representation

Manim, Blender, PhysX, o3de, [FEM, CFD, [thermal, fluidic,] engineering]: https://github.com/ManimCommunity/manim/issues/3362

NURBS: Non-Uniform Rational B-Splines: https://en.wikipedia.org/wiki/Non-uniform_rational_B-spline

NURBS for COMPAS: https://github.com/gramaziokohler/compas_nurbs :

> This package is inspired by the NURBS-Python package, however uses a NumPy-based backend for better performance.

> Curve, and Surface are non-uniform non-rational B-Spline geometries (NUBS), RationalCurve, and RationalSurface are non-uniform rational B-Spline Geometries (NURBS). They all built upon the class BSpline. Coordinates have to be in 3D space (x, y, z)

test_curve.py, test_surface.py

https://github.com/compas-dev

compas_rhino, compas_blender

Blender docs > Modeling Surfaces; NURBs implementation, limits, challenges:

A template language that I wrote for generating HTML. Meant to be included as a C++ library. https://github.com/Ghoti-io/Tang

Plenty of other C++ code of mine is on Github (such as a bunch of utility stuff, a thread pool, and a HTTP server that I'm writing from scratch), even though I would only call myself an intermediate C++ programmer. I just happen to like the language.

Or, if I had to throw other stuff into the mix, a fairly recent patch to Manim (Python) that got accepted (https://github.com/ManimCommunity/manim/pull/3155).

If I were really pressed, I would dig up a lot of my Drupal (PHP) stuff that I did years ago.

I would love to have this https://github.com/manimCommunity/manim written in Rust. There have been previous attempts (bevy_manim and another one using nannou) but all of them are outdated

PyTesseract Module [ Github ] EasyOCR Module [ Github ] PaddlePaddle OCR [ Github ]

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.

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?

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

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

EasyOCR is a popular project if you are in an environment where you can use run Python and PyTorch (https://github.com/JaidedAI/EasyOCR). Other open source projects of note are PaddleOCR (https://github.com/PaddlePaddle/PaddleOCR) and docTR (https://github.com/mindee/doctr).

I think you can train tesseract with custom data if you have enough, or you can use deep learning models like https://pyimagesearch.com/2020/08/17/ocr-with-keras-tensorflow-and-deep-learning or https://www.google.com/amp/s/nanonets.com/blog/attention-ocr-for-text-recogntion/amp/ or try other existing tools like paddle-ocr https://github.com/PaddlePaddle/PaddleOCR

https://huggingface.co/blog/document-ai https://github.com/microsoft/table-transformer https://github.com/google-research/pix2struct https://github.com/PaddlePaddle/PaddleOCR/blob/release/2.6/ppstructure/table/README.md

when following the installation commands present in the paddleocr repo(https://github.com/PaddlePaddle/PaddleOCR/blob/release/2.6/doc/doc_en/quickstart_en.md) im still unable to install paddleocr. paddlepaddle is successfully installed on my m1 mac with python3.9.16 but while installing paddleocr im getting this error after long pip backtracking

When I was evaluating options a few months ago I found https://github.com/PaddlePaddle/PaddleOCR to be a very strong contender for my use case (reading product labels), but you'll definitely want to put together some representative docs/images and test a bunch of solutions to see what works for you.