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v0.2.0

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@KKenny0 KKenny0 released this 12 Jun 02:29
· 67 commits to main since this release
v0.2.0
affa106

What's new since v0.1.0

Features

  • videowipe clean intent-driven workflow — auto-detect removable regions from a video with --preview, --confirm, --target, --region, and --intent flags
  • Frequency-map detection pipeline — samples frames, builds per-pixel text frequency map, extracts connected components, classifies by position and content
  • Subtitle band fallback — catches bottom/top subtitle regions missed by the main pass
  • --detect-mode presets — fast / balanced / sensitive with tuned sample count, consistency threshold, and fallback behavior
  • --ocr text recognition — optional RapidOCR integration for reading detected text crops, helps classify timestamps and watermarks
  • External model adapter — --external-command runs any CLI-based inpainting tool through the benchmark harness
  • Docker delivery — CPU and GPU images, GHCR publishing via GitHub Actions CI
  • Quality/performance benchmark — benchmark.json output, scripts/benchmark_pipeline.py, IoU metrics in eval script

Fixes

  • Adaptive DBNet input size — widescreen (16:9) frames no longer compressed to 640×640 square, preserving bottom subtitle detection
  • Smart preview frame selection — preview now uses the frame with the most detected text instead of always picking the first sampled frame
  • FFmpeg pipe replaces cv2.VideoWriter — libx264 CRF 18 output instead of mp4v
  • Manual DBNet fallback — high-level OpenCV API returning empty results falls back to manual post-processing
  • Docker build fixes — quoted package spec, explicit --target builds, PR build verification

README

  • Auto-detection accuracy showcase with multilingual preview images
  • ProPainter comparison section with before/after images
  • Bilingual GitHub About description
  • Removed overstated model comparison conclusions

Full Changelog: v0.1.0...v0.2.0

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