npx skills add smithery/zrt-ai-lab --skill videocut-install
zrt-ai-lab/opencode-skills
videocut-install
环境准备。安?
Installation
$
npx skills add zrt-ai-lab/opencode-skills --skill videocut-install
Similar popular skills
Related neighbors and high-traction skills in the same topics — useful to compare before installing.
Also in this package
Other skills from zrt-ai-lab/opencode-skills · top by installs.
npx skills add zrt-ai-lab/opencode-skills
More details
Agent compatibility
Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.
Claude Code
Declared
Cursor
Not declared
Codex
Not declared
GitHub Copilot
Not declared
Windsurf
Not declared
Gemini CLI
Not declared
Cline
Not declared
OpenCode
Declared
Also listed on
Alternate registries and mirrors of this skill.
Repository health
Stars
280
License
MIT
Default branch
main
Open issues
2
Status
Active
Skill metadata
Parsed from SKILL.md frontmatter.
Version1.0.0
Declared agents
claude-code
opencode
More metadata
- version
- 1.0.0
- alias
- "videocut:安�
Package contents
Files included with this skill beyond the listing page.
-
skill md
SKILL.md2,937 B -
docs
README.md311 B -
docs
SUMMARY.md126 B
History
- First seen on skills.sh
- First recorded snapshot · 203 installs
SKILL.md
<!-- input: 无 output: 环境就绪 pos: 前置 skill,首次使用前运行
架构守护者:一旦我被修改,请同步更新:
- ../README.md 的 Skill 清单
- /CLAUDE.md 路由表
-->
安装
首次使用前的环境准备
快速使用
用户: 安装环境
用户: 初始化
用户: 下载模型
依赖清单
| 依赖 | 用途 | 安装命令 |
|---|---|---|
| funasr | 口误识别 | pip install funasr |
| modelscope | 模型下载 | pip install modelscope |
| openai-whisper | 字幕生成 | pip install openai-whisper |
| ffmpeg | 视频剪辑 | brew install ffmpeg |
模型清单
FunASR 模型(口误识别用)
首次运行自动下载到 ~/.cache/modelscope/:
| 模型 | 大小 | 用途 |
|---|---|---|
| paraformer-zh | 953MB | 语音识别(带时间戳) |
| punc_ct | 1.1GB | 标点预测 |
| fsmn-vad | 4MB | 语音活动检测 |
| 小计 | ~2GB |
Whisper 模型(字幕生成用)
首次运行自动下载到 ~/.cache/whisper/:
| 模型 | 大小 | 用途 |
|---|---|---|
| large-v3 | 2.9GB | 字幕转录(质量最好) |
总计
约 5GB 模型文件
安装流程
1. 安装 Python 依赖
↓
2. 安装 FFmpeg
↓
3. 下载 FunASR 模型(口误识别)
↓
4. 下载 Whisper 模型(字幕生成)
↓
5. 验证环境
执行步骤
1. 安装 Python 依赖
pip install funasr modelscope openai-whisper
2. 安装 FFmpeg
# macOS
brew install ffmpeg
# Ubuntu
sudo apt install ffmpeg
# 验证
ffmpeg -version
3. 下载 FunASR 模型(约2GB)
from funasr import AutoModel
model = AutoModel(
model="paraformer-zh",
vad_model="fsmn-vad",
punc_model="ct-punc",
)
print("FunASR 模型下载完成")
4. 下载 Whisper 模型(约3GB)
import whisper
model = whisper.load_model("large-v3")
print("Whisper 模型下载完成")
5. 验证环境
from funasr import AutoModel
model = AutoModel(
model="paraformer-zh",
vad_model="fsmn-vad",
punc_model="ct-punc",
disable_update=True
)
# 测试转录(用任意音频/视频)
result = model.generate(input="test.mp4")
print("文本:", result[0]['text'][:50])
print("时间戳数量:", len(result[0]['timestamp']))
print("✅ 环境就绪")
常见问题
Q1: 模型下载慢
解决:使用国内镜像或手动下载
Q2: ffmpeg 命令找不到
解决:确认已安装并添加到 PATH
which ffmpeg # 应该输出路径
Q3: funasr 导入报错
解决:检查 Python 版本(需要 3.8+)
python3 --version