DAEMLABS
Automated video transcoding and quality analysis tool using FFmpeg and OpenCV. Transcodes to multiple resolutions, extracts stream metadata, and detects visual blurriness—all in a single Markdown report.
Video engineers lack an automated, lightweight tool to simultaneously transcode videos across multiple resolutions, extract stream metadata, and detect visual quality degradation—forcing manual FFmpeg commands and subjective visual inspection that wastes time and misses subtle blurring issues.
We built a Python-powered pipeline using FFmpeg for multi-resolution transcoding (480p/720p/1080p), ffprobe for codec/bitrate/resolution extraction, and OpenCV's Laplacian variance algorithm to quantify frame-by-frame blurriness across sampled video frames. The orchestrator generates a comprehensive Markdown report with inline Matplotlib plots, enabling automated video QA without manual intervention.
3 simultaneous resolutions transcoded in a single run (480p, 720p, 1080p)
Real-time blur detection using Laplacian variance across sampled frames
Automatic metadata extraction (codec, bitrate, resolution) via ffprobe
Markdown report generation with inline performance plots
Reusable pipeline for both real-time diagnostics & offline video QA
Zero manual FFmpeg commands – fully automated workflow