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video2imgs-视频关键帧获取

v1.0.0

Capture key frames from video files at fixed time intervals. Use when you need to understand video content by extracting screenshots, or when you need to ana...

⭐ 0· 140·0 current·0 all-time
by@chentx1243

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Previewing Install & Setup.
Prompt PreviewInstall & Setup
Install the skill "video2imgs-视频关键帧获取" (chentx1243/maple-video-capture) from ClawHub.
Skill page: https://clawhub.ai/chentx1243/maple-video-capture
Keep the work scoped to this skill only.
After install, inspect the skill metadata and help me finish setup.
Use only the metadata you can verify from ClawHub; do not invent missing requirements.
Ask before making any broader environment changes.

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openclaw skills install maple-video-capture

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npx clawhub@latest install maple-video-capture
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Benign
high confidence
✓
Purpose & Capability
The name/description (capture key frames) matches the included Python script and README. Required packages (opencv-python-headless, numpy) are appropriate for video frame extraction.
✓
Instruction Scope
SKILL.md instructs running the local script on local video files and installing dependencies via pip. The script only reads the specified input video, writes image files to the specified output directory, and logs progress — it does not contact external endpoints or read unrelated system data.
ℹ
Install Mechanism
No install spec is provided (instruction-only for installation); dependencies are pulled from PyPI via requirements.txt, which is normal for this use case. Installing opencv-python-headless is expected but brings native binaries from PyPI — standard but worthy of standard supply-chain caution.
ℹ
Credentials
The skill requests no environment variables or credentials, which is proportional. One minor note: the script conditionally inserts a hard-coded D:\SOFTware\py_dependent path into sys.path if that directory exists; this is likely intended for a developer environment but could cause imports to come from that local directory if present.
✓
Persistence & Privilege
The skill is not always-enabled and does not request elevated or persistent privileges or modify other skills or system-wide agent settings. It runs only when invoked.
Assessment
This skill appears coherent and implements exactly what it claims: extracting frames from local videos and optionally skipping similar frames. Before installing or running: 1) be prepared to run pip install -r requirements.txt (opencv packages include native binaries); 2) run the script only on videos you trust and choose an appropriate output directory (it will write images there); 3) note the script will add D:\SOFTware\py_dependent to Python's import path if that folder exists — if you have untrusted code in that folder it could influence imports, so ensure that path is either empty or trusted. Otherwise the skill's requested actions and resources look proportionate to its purpose.

Like a lobster shell, security has layers — review code before you run it.

latestvk9750esc6evan9715mqvh2av1s83agnp
140downloads
0stars
1versions
Updated 1mo ago
v1.0.0
MIT-0
@chentx1243
latest
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Video Frame Capture

Overview

This skill enables capturing key frames from video files at fixed time intervals. It's designed to help you understand video content by extracting screenshots for analysis or content recognition.

When to Use This Skill

Use this skill when:

  • You need to understand video content by extracting key frames
  • You want to analyze video frames for content recognition
  • You need to create a visual summary of a video
  • You want to skip similar frames to avoid redundant captures

Quick Start

Capture frames from a video at 10-second intervals:

python scripts/video_frame_capture.py --input "D:\videos\meeting.mp4" --output-dir "D:\frames\meeting" --interval-seconds 10

Parameters

  • --input: Path to the local video file (required)
  • --output-dir: Directory where captured frames will be stored (required)
  • --interval-seconds: Capture interval in seconds, must be greater than 0 (required)
  • --skip-similar-frames: Skip frames that are similar to the previous saved frame
  • --similarity-threshold: Similarity threshold in range 0-1, defaults to 0.70
  • --image-extension: Image format for saved frames, defaults to jpg

Output Naming

Output files follow the format: 视频文件原始名称_视频时间轴_第几次截取.jpg

Example: meeting_00h01m30s_0003.jpg

Similar Frame Skipping

When --skip-similar-frames is enabled, the script compares the current candidate frame with the previous saved frame:

  • Similarity > threshold: Frame is skipped
  • Similarity ≤ threshold: Frame is saved and becomes the new comparison baseline

Examples

Basic frame capture

python scripts/video_frame_capture.py --input "D:\videos\meeting.mp4" --output-dir "D:\frames\meeting" --interval-seconds 10

Skip similar frames

python scripts/video_frame_capture.py --input "D:\videos\meeting.mp4" --output-dir "D:\frames\meeting" --interval-seconds 10 --skip-similar-frames

Custom similarity threshold

python scripts/video_frame_capture.py --input "D:\videos\meeting.mp4" --output-dir "D:\frames\meeting" --interval-seconds 10 --skip-similar-frames --similarity-threshold 0.80

Resources

scripts/

  • video_frame_capture.py: Main script for capturing video frames

references/

  • video_formats.md: Supported video formats and technical details

Note: This skill requires OpenCV (opencv-python-headless) to be installed. Install dependencies with: pip install -r requirements.txt

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