video-comparer
by daymade
This skill should be used when comparing two videos to analyze compression results or quality differences. Generates interactive HTML reports with quality metrics (PSNR, SSIM) and frame-by-frame visual comparisons. Triggers when users mention "compare videos", "video quality", "compression analysis", "before/after compression", or request quality assessment of compressed videos.
安装
安装命令
git clone https://github.com/daymade/claude-code-skills/tree/main/video-comparer文档
Video Comparer
Overview
Compare two videos and generate an interactive HTML report analyzing compression results. The script extracts video metadata, calculates quality metrics (PSNR, SSIM), and creates frame-by-frame visual comparisons with three viewing modes: slider, side-by-side, and grid.
When to Use This Skill
Use this skill when:
- Comparing original and compressed videos
- Analyzing video compression quality and efficiency
- Evaluating codec performance or bitrate reduction impact
- Users mention "compare videos", "video quality", "compression analysis", or "before/after compression"
Core Usage
Basic Command
python3 scripts/compare.py original.mp4 compressed.mp4
Generates comparison.html with:
- Video parameters (codec, resolution, bitrate, duration, file size)
- Quality metrics (PSNR, SSIM, size/bitrate reduction percentages)
- Frame-by-frame comparison (default: frames at 5s intervals)
Command Options
# Custom output file
python3 scripts/compare.py original.mp4 compressed.mp4 -o report.html
# Custom frame interval (larger = fewer frames, faster processing)
python3 scripts/compare.py original.mp4 compressed.mp4 --interval 10
# Batch comparison
for original in originals/*.mp4; do
compressed="compressed/$(basename "$original")"
output="reports/$(basename "$original" .mp4).html"
python3 scripts/compare.py "$original" "$compressed" -o "$output"
done
Requirements
System Dependencies
FFmpeg and FFprobe (required for video analysis and frame extraction):
# macOS
brew install ffmpeg
# Ubuntu/Debian
sudo apt update && sudo apt install ffmpeg
# Windows
# Download from https://ffmpeg.org/download.html
# Or use: winget install ffmpeg
Python 3.8+ (uses type hints, f-strings, pathlib)
Video Specifications
- Supported formats:
.mp4(recommended),.mov,.avi,.mkv,.webm - File size limit: 500MB per video (configurable)
- Processing time: ~1-2 minutes for typical videos; varies by duration and frame interval
Script Behavior
Automatic Validation
The script automatically validates:
- FFmpeg/FFprobe installation and availability
- File existence, extensions, and size limits
- Path security (prevents directory traversal)
Clear error messages with resolution guidance appear when validation fails.
Quality Metrics
The script calculates two standard quality metrics:
PSNR (Peak Signal-to-Noise Ratio): Pixel-level similarity measurement (20-50 dB scale, higher is better)
SSIM (Structural Similarity Index): Perceptual similarity measurement (0.0-1.0 scale, higher is better)
For detailed interpretation scales and quality thresholds, consult references/video_metrics.md.
Frame Extraction
The script extracts frames at specified intervals (default: 5 seconds), scales them to consistent height (800px) for comparison, and embeds them as base64 data URLs in self-contained HTML. Temporary files are automatically cleaned after processing.
Output Report
The generated HTML report includes:
- Slider Mode: Drag to reveal original vs compressed (default)
- Side-by-Side Mode: Simultaneous display for direct comparison
- Grid Mode: Compact 2-column layout
- Zoom Controls: 50%-200% magnification
- Self-contained format (no server required, works offline)
Important Implementation Details
Security
The script implements:
- Path validation (absolute paths, prevents directory traversal)
- Command injection prevention (no
shell=True, validated arguments) - Resource limits (file size, timeouts)
- Custom exceptions:
ValidationError,FFmpegError,VideoComparisonError
Common Error Scenarios
"FFmpeg not found": Install FFmpeg via platform package manager (see Requirements section)
"File too large": Compress videos before comparison, or adjust MAX_FILE_SIZE_MB in scripts/compare.py
"Operation timed out": Increase FFMPEG_TIMEOUT constant or use larger --interval value (processes fewer frames)
"Frame count mismatch": Videos have different durations/frame rates; script auto-truncates to minimum frame count and shows warning
Configuration
The script includes adjustable constants for file size limits, timeouts, frame dimensions, and extraction intervals. To customize behavior, edit the constants at the top of scripts/compare.py. For detailed configuration options and their impacts, consult references/configuration.md.
Reference Materials
Consult these files for detailed information:
references/video_metrics.md: Quality metrics interpretation (PSNR/SSIM scales, compression targets, bitrate guidelines)references/ffmpeg_commands.md: FFmpeg command reference (metadata extraction, frame extraction, troubleshooting)references/configuration.md: Script configuration options and adjustable constantsassets/template.html: HTML report template for customizing viewing modes and styling
相关 Skills
by daymade
Collect real financial data for any US publicly traded company from free public sources (yfinance). Output structured JSON consumable by downstream financial skills (DCF modeling, comps analysis, earnings review). Handles market data (price, shares, beta), historical financials (income statement, cash flow, balance sheet), WACC inputs, and analyst estimates. Use when users request collect data for ticker, get financials for company, pull market data, gather DCF inputs, or any task requiring structured financial data before analysis. Also triggers on financial data, company data, stock data.
by daymade
Analyze and reclaim macOS disk space through intelligent cleanup recommendations. This skill should be used when users report disk space issues, need to clean up their Mac, or want to understand what's consuming storage. Focus on safe, interactive analysis with user confirmation before any deletions.
by daymade
Multi-path parallel product analysis with cross-model test-time compute scaling. Spawns parallel agents (Claude Code agent teams + Codex CLI) to explore product from multiple perspectives, then synthesizes findings into actionable optimization plans. Can invoke competitors-analysis for competitive benchmarking. Use when "product audit", "self-review", "发布前审查", "产品分析", "analyze our product", "UX audit", or "信息架构审计".