manga-image-translator VS NeMo

OCR works pretty good. ocr.space, ocr.best and cotrans.touhou.ai/ are all pretty nice.

A lot of problem with Python packages is the fact that a lot of Python programs is not just Python. You have a significant amount of C++, Cython, and binaries (like Intel MKL) when it comes to scientific Python and machine learning. All of these tools have different build processes than pip so if you want to ship with them you end up bring the whole barn with you. A lot of these problems was fixed with python wheels, where they pack the binary in the package.

Personally, I haven't ran into a problem with Python packaging recently. I was running https://github.com/zyddnys/manga-image-translator (very cool project btw) and I didn't ran into any issues getting it to work locally on a Windows machine with Nvidia GPU.

https://cotrans.touhou.ai/ - I use this translator with different translator options to translate if I don't want to wait, it usually does a good job but it's very slow sometimes.

Manga Image Translator

There's a CLI and web interface for Image/Manga Translator to translate manga automatically. The REDRAWING is impressive, it's so clean and even works on colors. Sometimes it fails with complicated pages, but there's another software below. Also, its OCR (character recognition) only supports EN, JPN, CN, and KR for now, but it's very accurate and I'm satisfied. Kinda slow on my gen 7 core i5 laptop, but you can run it on Google Colab to use GPUs.

Need to try it, could give better result than manga-image-translator

by image translator, horizontal, google, english

I don't test WaveRNN but from the ones that I know the best that is open source is FastPitch. And it's easy to use, here is the tutorial for voice cloning.

Nowadays... bigger repos like https://github.com/NVIDIA/NeMo are all pytorch, lots of work also published by Meta and Microsoft is all torch. I check new work on GitHub all the time and I haven't seen a Tensorflow repo in years except one.

- https://github.com/NVIDIA/NeMo

Can’t you use the NeMo model and just strip the punctuation from the output again if you don’t want it? You can also fine tune the the model with capitalization only if you look at the examples https://github.com/NVIDIA/NeMo/blob/stable/tutorials/nlp/Punctuation_and_Capitalization.ipynb The capitalization and punctuation are annotated separately (U indicates that the word should be upper cased, and O - no capitalization ). The model seems to be a token level classifier not seq to seq so there should also be a way to get just the capitalization part but you would have to look into the model as it’s not shown in the examples.

I think there's been talk to do speaker diarization with whisper-asr-webservice[0] which is also written in python and should be able to make use of goodies such as pyannote-audio, py-webrtcvad, etc.

Whisper is great but at the point we get to kludging various things together it starts to make more sense to use something like Nvidia NeMo[1] which was built with all of this in mind and more

[0] - https://github.com/ahmetoner/whisper-asr-webservice

[1] - https://github.com/NVIDIA/NeMo

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