video-subtitle-remover

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视频硬字幕/水印去除技能。自动配置基于 YaoFANGUK/video-subtitle-remover 的环境并执行去字幕。当用户要求"去除视频字幕"、"去水印"、"把这个视频的字幕干掉"时触发此技能。

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视频字幕去除技能 (Video Subtitle Remover)

触发场景

当用户提到以下关键词时触发本技能：

"去字幕"、"去除视频字幕"
"去掉视频里的文字/水印"
"把这视频的字幕干掉"

工作流程

这是一个需要本地 GPU/Apple Silicon 加速的重型任务，你需要作为一个完整的执行器，从环境准备到执行全包揽。

第一阶段：环境检查与准备 (非常重要)

在首次运行前，必须检查环境并在用户机器上安装所需组件。工作目录约定为：~/.opencode/tools/video-subtitle-remover。

检查目录与代码 使用 bash 检查 ~/.opencode/tools/video-subtitle-remover/run_remove.py 是否存在。如果不存在，执行以下初始化操作：

# 1. 创建工作目录
mkdir -p ~/.opencode/tools/video-subtitle-remover/backend/models/{V4/ch_det,sttn}
cd ~/.opencode/tools/video-subtitle-remover

# 2. 拉取核心代码 (跳过模型文件)
curl -sL "https://api.github.com/repos/YaoFANGUK/video-subtitle-remover/git/trees/main?recursive=1" | python3 -c "
import sys, json, os, urllib.request
data = json.load(sys.stdin)
for item in data.get('tree', []):
    if item['type'] != 'blob': continue
    path = item['path']
    ext = os.path.splitext(path)[1].lower()
    if ext in {'.pth', '.onnx', '.pdiparams', '.pdmodel'} or '__pycache__' in path or item.get('size', 0) > 500000: continue
    
    os.makedirs(os.path.dirname(path) if os.path.dirname(path) else '.', exist_ok=True)
    url = f'https://raw.githubusercontent.com/YaoFANGUK/video-subtitle-remover/main/{path}'
    try:
        content = urllib.request.urlopen(url).read()
        with open(path, 'wb') as f: f.write(content)
    except: pass
"

安装 Python 依赖

pip3 install torch torchvision
pip3 install filesplit==3.0.2 scikit-image pyclipper lmdb PyYAML omegaconf tqdm easydict scikit-learn pandas webdataset einops av shapely paddleocr paddle2onnx albumentations imgaug

下载并合并模型 (STTN 模式必需) 如果 backend/models/sttn/infer_model.pth 或 backend/models/V4/ch_det/inference.pdiparams 不存在，使用 curl 下载：

cd ~/.opencode/tools/video-subtitle-remover/backend/models
# 下载 STTN 模型
curl -L -o sttn/infer_model.pth "https://raw.githubusercontent.com/YaoFANGUK/video-subtitle-remover/main/backend/models/sttn/infer_model.pth"

# 下载并合并 PaddleOCR 文本检测模型 (3个分割包)
curl -L -o V4/ch_det/inference_1.pdiparams "https://raw.githubusercontent.com/YaoFANGUK/video-subtitle-remover/main/backend/models/V4/ch_det/inference_1.pdiparams"
curl -L -o V4/ch_det/inference_2.pdiparams "https://raw.githubusercontent.com/YaoFANGUK/video-subtitle-remover/main/backend/models/V4/ch_det/inference_2.pdiparams"
curl -L -o V4/ch_det/inference_3.pdiparams "https://raw.githubusercontent.com/YaoFANGUK/video-subtitle-remover/main/backend/models/V4/ch_det/inference_3.pdiparams"
curl -L -o V4/ch_det/fs_manifest.csv "https://raw.githubusercontent.com/YaoFANGUK/video-subtitle-remover/main/backend/models/V4/ch_det/fs_manifest.csv"
curl -L -o V4/ch_det/inference.pdiparams.info "https://raw.githubusercontent.com/YaoFANGUK/video-subtitle-remover/main/backend/models/V4/ch_det/inference.pdiparams.info"
curl -L -o V4/ch_det/inference.pdmodel "https://raw.githubusercontent.com/YaoFANGUK/video-subtitle-remover/main/backend/models/V4/ch_det/inference.pdmodel"

# 使用 Python 合并
python3 -c "from fsplit.filesplit import Filesplit; fs=Filesplit(); fs.merge(input_dir='V4/ch_det')"

注入修复代码与启动脚本 使用 edit 工具修改 backend/config.py：
- 修复 Mac 的 MPS 设备支持 (device = torch.device('mps'))
- 修复 FFMPEG_PATH 指向系统 ffmpeg (shutil.which('ffmpeg'))
- 删除不必要的 LAMA 和 ProPainter 模型校验。
并使用 write 工具生成 run_remove.py 启动脚本。

第二阶段：执行任务

提取信息与评估 获取用户提供的视频绝对路径，运行 ffprobe 或 ls -lh 获取帧数，给用户预报处理时间。

执行处理 运行处理脚本：

export KMP_DUPLICATE_LIB_OK=True
python3 ~/.opencode/tools/video-subtitle-remover/run_remove.py "<视频绝对路径>"

注意：如果视频较长，务必使用 tmux 放后台跑。

结果交付 使用 open 命令为用户自动打开输出的 _no_sub.mp4 视频。