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Convert bitmap subtitles into SubRip format using the macOS Vision framework

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ecdye/macSubtitleOCR

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macSubtitleOCR

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Overview

macSubtitleOCR converts bitmap subtitles into the SubRip subtitle format (SRT) using the macOS Vision framework to perform OCR. Currently PGS and VobSub subtitles are supported.

For more details on OCR accuracy, refer to the Accuracy section below.

An Apple M series processor is required for macSubtitleOCR, PRs adding additional support are welcomed.

Features

  • Export raw JSON output from Vision for further analysis
  • Save .png images of subtitles for manual correction of OCR output
  • Optional support for FFmpeg in case of any issues with internal decoder

Supported Formats

  • PGS (.mkv, .sup)
  • VobSub (.mkv, .sub, .idx)

Building the Project

Important

macSubtitleOCR requires Swift 6 support to compile

Follow the directions below to compile the project with your desired support option. The final build will be available in the .build/release directory.

Build Internal Decoder Only

To build macSubtitleOCR, follow these steps:

git clone https://github.com/ecdye/macSubtitleOCR
cd macSubtitleOCR
swift build --configuration release

Build With FFmpeg Decoder

To build with FFmpeg support, follow these steps:

brew install ffmpeg
git clone https://github.com/ecdye/macSubtitleOCR
cd macSubtitleOCR
mv Package.swift Package.internal.swift
mv Package.ffmpeg.swift Package.swift
swift build -Xswiftc -DFFMPEG --configuration release

Running Tests

The testing process compares OCR output against known correct results. Tests aim for at least 95% accuracy, as there are slight differences in Vision results between machines.

swift test

Accuracy

In general, Vision produces a highly accurate output for almost all subtitles. If you find an edge case with degraded performance, open an issue so it can be investigated.

In tests comparing Vision's output with Tesseract, Vision consistently gave better results, particularly with tricky cases like properly recognizing I.

While some tools, like SubtitleEdit, may use binary image compare for marginally better accuracy, Vision offers more flexibility with built-in language support.

Contribution and TODO

For information on how to contribute to the project, please refer to CONTRIBUTING.md.

If you're interested in working on specific features or improvements, check out issues tagged as enhancements.

References