yaofanguk/video-subtitle-remover

基于AI的图片/视频硬字幕去除、文本水印去除,无损分辨率生成去字幕、去水印后的图片/视频文件。无需申请第三方API,本地实现。AI-based tool for removing hard-coded subtitles and text-like watermarks from videos or Pictures.

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Summary Information

Updated 36 minutes ago
Added to GitGenius on September 4th, 2026
Created on October 25th, 2023
Open Issues & Pull Requests: 187 (+0)
GitHub issues: Enabled
Number of forks: 1,620
Total Stargazers: 12,781 (+0)
Total Subscribers: 86 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 14.4 days
Mean response time: 50.3 days
90th percentile: 129.7 days
Tracked items: 93

How this project is maintained

Around half of the issues opened in the past year never receive a reply. 100% of open issues come from outside the core team, so the backlog reflects real-world use rather than internal planning. 56% of tracked open issues have had no activity in three months. Only 3% of issues opened in the past year have been closed.

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Issue Activity (beta)

Open issues: 136
New in 7 days: 1
Closed in 7 days: 0
Avg open age: 431 days
Stale 30+ days: 127
Stale 90+ days: 111

Recent activity

Opened in 7 days: 1
Closed in 7 days: 0
Comments in 7 days: 1
Events in 7 days: 1

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Detailed Description

Video-subtitle-remover is a tool for removing hard-coded subtitles and text watermarks from videos and images using AI-based inpainting.

The tool addresses the problem of permanently embedded subtitles in video files by using deep learning models to detect and remove text regions while reconstructing the underlying content. It performs inpainting on the areas where subtitles or watermarks are removed, filling them with plausible pixel values rather than simple interpolation or mosaic removal. The approach runs entirely locally without requiring third-party API calls. Users can either specify custom subtitle positions for targeted removal or enable automatic detection to remove all text from an entire video. The tool also supports batch processing of multiple images for watermark removal and can extract subtitles from videos for use with complementary tools.

The tool suits developers and users who need to process videos with hard-coded subtitles while preserving original resolution. It works across Windows, macOS, and Linux, with prebuilt packages available for different hardware configurations including CPU-only systems, non-NVIDIA GPUs via DirectML, and NVIDIA GPUs with various CUDA versions. Docker support is also provided. This approach is preferable to online services when privacy is a concern or when processing large volumes of video content locally is more practical than uploading to cloud services.

The project maintains multiple prebuilt distributions tailored to different computational environments and GPU capabilities, indicating attention to accessibility across hardware configurations. Development includes both a graphical interface and command-line interface for different usage patterns. The tool provides Docker containerization alongside traditional installation methods, suggesting consideration for deployment flexibility. Documentation is available in both simplified Chinese and English, reflecting effort to serve multiple language communities.