Video Frame Extraction Skill

Purpose

This skill enables extraction of individual frames from video files (MP4, AVI, MOV, etc.) using OpenCV. Extracted frames are saved as image files in a specified output directory. It is suitable for video analysis, creating training datasets, thumbnail generation, and preprocessing video content for further processing.

When to Use

• Extracting frames for machine learning training data
• Creating image sequences from video content
• Generating video thumbnails or preview images
• Preprocessing videos for object detection or tracking
• Converting video segments to image collections for analysis
• Sampling frames at specific intervals for time-lapse effects

Required Libraries

The following Python libraries are required:

import cv2
import os
import json
from pathlib import Path

Input Requirements

• File formats: MP4, AVI, MOV, MKV, WMV, FLV, WEBM
• Video codec: Must be readable by OpenCV (most common codecs supported)
• File access: Read permissions on source video
• Output directory: Write permissions on destination folder
• Disk space: Ensure sufficient space for extracted frames (uncompressed images)

Output Schema

All extraction results must be returned as valid JSON conforming to this schema:

{
  "success": true,
  "source_video": "sample.mp4",
  "output_directory": "/path/to/frames",
  "frames_extracted": 150,
  "extraction_params": {
    "interval": 1,
    "start_frame": 0,
    "end_frame": null,
    "output_format": "jpg"
  },
  "video_metadata": {
    "total_frames": 300,
    "fps": 30.0,
    "duration_seconds": 10.0,
    "resolution": [1920, 1080]
  },
  "output_files": [
    "frame_000001.jpg",
    "frame_000002.jpg"
  ],
  "warnings": []
}

Field Descriptions