SubtitleYC v0.3.0

SubtitleYC v0.3.0

SubtitleYC is a free and open-source Windows app for extracting, reviewing,
and editing frame-timed subtitles from video.

SubtitleYC is distributed under the MIT License. Bundled third-party tools
retain their own licences, which are included with the installation.

Highlights

• Local video and URL workflows in one desktop app.
• Native PyAV frame preview with crop selection and subtitle overlay.
• CPU and Nvidia GPU VideOCR editions.
• 31 alphabetically listed OCR language choices, including common Asian languages.
• Correct Simplified and Traditional Chinese VideOCR language mapping.
• Subtitle import, cue timing edits, undo/redo, and SRT export.
• yt-dlp format and site-subtitle discovery.
• Project library, storage controls, activity rows, local logs, and crash logs.
• Dark and light themes with persisted settings.

Choose an Installer

• CPU is the safest default and does not require an Nvidia GPU.
• CUDA 12.9 is for supported Nvidia GTX 16 through RTX 50 systems.

Installing another edition replaces the app and OCR runtime while preserving
the user's workspace under %LOCALAPPDATA%\SubtitleYC\workspace.

Known Limitations

• This is an early release and may still contain crashes or UI defects.
• OCR accuracy depends on language, image quality, crop, and source frame rate.
• Video websites change independently; yt-dlp workflows can require app updates.
• The GPU installer is large because it includes the CUDA OCR runtime.
• These installers are not Authenticode-signed. Windows may show an unknown-publisher warning; compare the SHA-256 digest shown by GitHub before running them.

Verify the Download

GitHub displays a SHA-256 digest beside each installer asset. To calculate the
digest of a downloaded installer in PowerShell:

Get-FileHash .\SubtitleYC-0.3.0-windows-cpu-setup.exe -Algorithm SHA256

Compare the result with the digest shown on the release page before installation.

Please report reproducible problems through the issue forms. Do not attach
private media or unredacted logs.

SubtitleYC v0.2.0 Beta 2

SubtitleYC v0.2.0 Beta 2

SubtitleYC is a free and open-source Windows app for extracting, reviewing,
and editing frame-timed subtitles from video.

MIT Release

Beta 2 is the first release whose installers, bundled application files, and
installer licence page consistently use the MIT License. Bundled third-party
tools retain their own licences, which are included with the installation.

Highlights

• Local video and URL workflows in one desktop app.
• Native PyAV frame preview with crop selection and subtitle overlay.
• CPU and Nvidia GPU VideOCR editions.
• Subtitle import, cue timing edits, undo/redo, and SRT export.
• yt-dlp format and site-subtitle discovery.
• Project library, storage controls, activity rows, local logs, and crash logs.
• Dark and light themes with persisted settings.

Choose an Installer

• CPU is the safest default and does not require an Nvidia GPU.
• CUDA 12.9 is for supported Nvidia GTX 16 through RTX 50 systems.

Installing another edition replaces the app and OCR runtime while preserving
the user's workspace under %LOCALAPPDATA%\SubtitleYC\workspace.

Known Limitations

• This is prerelease software and may still contain crashes or UI defects.
• OCR accuracy depends on language, image quality, crop, and source frame rate.
• Video websites change independently; yt-dlp workflows can require app updates.
• The GPU installer is large because it includes the CUDA OCR runtime.
• These beta installers are not Authenticode-signed. Windows may show an unknown-publisher warning; compare the SHA-256 digest shown by GitHub before running them.

Verify the Download

GitHub displays a SHA-256 digest beside each installer asset. To calculate the
digest of a downloaded installer in PowerShell:

Get-FileHash .\SubtitleYC-0.2.0-beta.2-windows-cpu-setup.exe -Algorithm SHA256

Compare the result with the digest shown on the release page before installation.

Please report reproducible problems through the issue forms. Do not attach
private media or unredacted logs.

SubtitleYC v0.2.0 Beta 1 (Superseded)

Superseded: Download SubtitleYC v0.2.0 Beta 2. Beta 2 contains the refreshed MIT-licensed installers.

SubtitleYC v0.2.0 Beta 1

SubtitleYC is a free and open-source Windows app for extracting, reviewing, and editing frame-timed subtitles from video. The project is available under the MIT License.

This prerelease is for public testing and feedback.

Choose an Installer

Download one setup file:

• Windows CPU setup - recommended for most users and does not require an Nvidia GPU.
• Windows GPU (CUDA 12.9) setup - includes GPU-accelerated VideOCR for supported Nvidia GTX 16 through RTX 50 systems.

CUDA 11.8 is not included in this beta. Nvidia GTX 10 users should use the CPU edition. Installing a different edition replaces the application and OCR runtime while preserving the workspace under %LOCALAPPDATA%\SubtitleYC\workspace.

GitHub automatically includes the Source code archives on every tagged release. Those archives are for developers; Windows users who want to run SubtitleYC should download one of the setup files above.

Highlights

• Local video and URL download workflows in one desktop app.
• Native PyAV frame preview with crop selection and subtitle overlay.
• CPU and Nvidia GPU VideOCR editions.
• Subtitle import, cue timing edits, undo/redo, and SRT export.
• yt-dlp format and site-subtitle discovery.
• Project library, storage controls, activity rows, logs, and crash reports.
• Dark and light themes with persisted settings.

Open Source

The complete application source is published in this repository. Bug reports and contributions are welcome:

• Read the source
• Contribution guide
• Report a problem

Before Installing

• This is beta software and may contain crashes or UI defects.
• The installers are not Authenticode-signed, so Windows may show an unknown-publisher warning.
• The GPU installer is large because it includes the CUDA OCR runtime.
• OCR accuracy depends on the language, video quality, crop, and source frame rate.
• Video websites change independently, so yt-dlp workflows may require future updates.
• These installers were assembled before the repository's MIT transition and may display older beta license wording. The current source code is licensed under MIT.

Please do not attach private media or unredacted logs to public issues.