I have created a tool to translate any kind of VN by image analysis.

This page summarizes the projects mentioned and recommended in the original post on /r/visualnovels

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  • Pytorch

    Tensors and Dynamic neural networks in Python with strong GPU acceleration

  • Currently the tool supports 2 different OCRs. PaddleOCR and EasyOCR. In both cases, the OCR has a specific model for Japanese characters. They work quite well, as long as the characters have clear contrast. The problem is that these OCR implement Torch, which makes the program very heavy. I am looking for a way to optimize this.

  • K-AVT

    Discontinued A tool for translating games through image analysis

  • Github

  • InfluxDB

    Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

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  • 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)

  • Currently the tool supports 2 different OCRs. PaddleOCR and EasyOCR. In both cases, the OCR has a specific model for Japanese characters. They work quite well, as long as the characters have clear contrast. The problem is that these OCR implement Torch, which makes the program very heavy. I am looking for a way to optimize this.

  • EasyOCR

    Ready-to-use OCR with 80+ supported languages and all popular writing scripts including Latin, Chinese, Arabic, Devanagari, Cyrillic and etc.

  • Currently the tool supports 2 different OCRs. PaddleOCR and EasyOCR. In both cases, the OCR has a specific model for Japanese characters. They work quite well, as long as the characters have clear contrast. The problem is that these OCR implement Torch, which makes the program very heavy. I am looking for a way to optimize this.

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

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