OCR Burned-in Subtitle (Video OCR)

Extract hardcoded (burned-in) subtitles from a video into editable text lines using OCR.

• Menu: Video → OCR burned-in subtitle...

How to Use

1. Open Video → OCR burned-in subtitle... (a video file is required)
2. Use the preview slider to find a frame that shows a subtitle
3. Adjust the scan area rectangle so it covers where the subtitles appear (default: bottom third) — drag to move/resize, or use the preset buttons
4. Pick an OCR engine and language (for Ollama and llama.cpp, also pick a vision model)
5. Optionally click Test OCR to try the current frame before running the full pass
6. Click Start OCR — lines appear in the list as they are recognized
7. Click OK to load the result into the main window

The recognized text is editable directly in the list, so OCR mistakes can be fixed in place. Double-click a line to show the frame it came from in the preview, and press Delete to remove selected lines.

OCR Engines

• Paddle OCR — local, fast and accurate; downloaded automatically (Windows/Linux). Recommended.
• Paddle OCR Python — local, via a Python paddleocr installation (also works on macOS)
• Ollama vision — local vision model via Ollama, e.g. glm-ocr
• llama.cpp — local vision model via a managed llama.cpp server; the engine and models are downloaded automatically. Available models: GLM-OCR 0.9B, LightOnOCR 1B, and PaddleOCR-VL 1.6 (109 languages). A green dot marks models that are already downloaded; custom *.gguf files in the llama.cpp models folder also appear.
• GLM API — GLM vision model via the Z.ai / bigmodel.cn cloud API (requires an API key)

How It Works

Frames are sampled from the scan area at a few frames per second with ffmpeg. Consecutive near-identical frames are collapsed so each on-screen subtitle is OCR'ed only once, then consecutive OCR results with near-identical text are merged into one line with correct start/end times (the text variant shown the longest wins).

Settings

• Frames per second — how many frames per second to sample (higher = more precise timing, slower)
• Text brightness minimum — pixels darker than this are ignored when comparing frames, so the comparison follows the (bright) subtitle text instead of the moving video behind it; frames with no bright pixels are skipped entirely. Set to 0 to disable (e.g. for dark subtitle text).
• Merge lines with similarity (%) — how similar the text of two consecutive OCR results must be to merge into one line
• Max gap between lines (ms) — maximum time gap allowed when merging
• Minimum duration (ms) — lines shorter than this are dropped (removes OCR blips/false positives)
• Add ASSA position tag — prepend an alignment tag (e.g. {\an8} for a top scan area) based on the scan area position, for Advanced Sub Station Alpha output

Tips

• Scan only the region where subtitles actually appear — a smaller area is faster and has fewer false positives
• For subtitles at the top of the frame (e.g. sign translations), move the scan area up and enable the ASSA position tag
• If lines are duplicated with small OCR differences, raise Merge lines with similarity tolerance by lowering the percentage
• If short random text blips appear, raise Minimum duration