AlphaCut v1.0.0

Video background removal & compositing.

AlphaCut uses ONNX segmentation models to isolate subjects from video backgrounds, with built-in compositing, batch processing.

---

Features

AI & Processing

• 8 AI Models — U2Net, ISNet, BiRefNet — from fast drafts to cinema-quality edges
• 5 Output Formats — ProRes 4444+Alpha, WebM VP9+Alpha, PNG sequences, green screen, grayscale matte
• Pipelined I/O — parallel decode/infer/save threads for higher throughput
• Frame Skip — process every Nth frame with mask reuse (up to 10x speedup)
• Benchmark Mode — test 10 samples to estimate total processing time
• Memory Monitoring — live RAM % during processing with warnings
• Resume Interrupted Jobs — progress saved every 50 frames, auto-resumes on restart

Advanced Compositing

• Background Replacement — solid color (6 presets + custom picker) or image file
• Color Spill Suppression — reduce green/blue/red spill along mask edges
• Shadow Preservation — detect and keep ground shadows via luminance analysis
• Mask Inversion — remove subject instead of background

Batch & Workflow

• Batch Queue — drop multiple files or a folder, process sequentially
• Job Table — per-file status, progress %, and output path
• CLI Mode — full argparse interface for headless/scripted operation
• Auto-Naming — configurable output patterns ({name}, {model}, {format}, {date})
• Export Presets — save/load all settings including compositing
• Recent Files — last 20 files quick-access menu

UI/UX

• Before/After Split View with draggable divider
• Smart Model Picker, Toast Notifications, Animated Progress
• System Tray integration, Scrubable Preview
• Menu Bar — File, Tools (Model Manager, Settings Folder), Help (Updates, About)
• About Dialog — version, system info, GitHub links
• Update Checker — checks GitHub releases on startup and on demand
• Model Manager — view/delete cached ONNX models with size info
• Settings Persistence — all preferences saved between sessions

Requirements

Requirement	Details
Python	3.9+
FFmpeg	On PATH
NVIDIA GPU	Optional — CUDA 12 + cuDNN 9

Quick Start

# GUI
python AlphaCut.py

# CLI — basic
python AlphaCut.py -i video.mp4 -f prores -m BiRefNet

# CLI — background replacement
python AlphaCut.py -i video.mp4 -f webm --bg-image beach.jpg

# CLI — green spill + shadow preservation
python AlphaCut.py -i greenscreen.mp4 -f prores --spill 60 --shadow 40

# CLI — batch with frame skip
python AlphaCut.py -i vid1.mp4 vid2.mp4 vid3.mp4 -f webm --frame-skip 3

# CLI — invert mask + custom background
python AlphaCut.py -i video.mp4 -f prores --invert --bg-color 0,0,0

CLI Reference

Flag	Default	Description
-i, --input	—	Input video file(s)
-o, --output	Auto-named	Output path
-m, --model	u2net_human_seg	Model name (partial match)
-f, --format	prores	prores, webm, png_seq, greenscreen, matte
--max-res	0 (original)	Max resolution
--edge	0	Edge softness (0-100)
--shift	0	Mask shift (-20 to +20)
--temporal	0	Temporal smooth (0-7)
--frame-skip	1	Process every Nth frame
--invert	—	Invert mask
--spill	0	Spill suppression (0-100)
--spill-color	green	Spill color: green, blue, red
--shadow	0	Shadow preservation (0-100)
--bg-color	—	Background R,G,B
--bg-image	—	Background image path
--no-audio	—	Strip audio

AI Models

Model	Speed	Quality	Best For
u2netp	Fast	Good	Quick previews
u2net_human_seg	Fast	Great	People (default)
silueta	Fast	Good	People (small)
u2net	Medium	Great	General subjects
isnet-general-use	Medium	Great	General subjects
isnet-anime	Medium	Great	Anime / illustrations
BiRefNet-portrait	Slow	Excellent	Portraits, hair detail
BiRefNet-general	Slow	Excellent	Best overall

Architecture

AlphaCut.py (single file, ~2,400 lines)
├── Crash Handler + Bootstrap (auto-installs all deps)
├── AlphaCutEngine — ONNX inference + mask refinement
│   ├── Edge refinement, temporal smoothing
│   ├── Spill suppression, shadow preservation
│   ├── Mask inversion, background compositing
│   └── Engine cache (singleton)
├── ProcessingWorker — Pipelined frame processing
│   ├── Reader thread → AI inference → Saver thread
│   ├── Frame skip with mask reuse
│   └── Resume from last saved frame
├── BatchWorker — Sequential multi-file processing
├── BenchmarkWorker — 10-frame speed estimation
├── PreviewFrameWorker — Single-frame preview
├── UpdateChecker — GitHub releases API
├── AboutDialog — Version/system info
├── ModelManagerDialog — Download/delete models
├── SplitPreviewWidget — Before/after comparison
├── ToastWidget — Floating notifications
├── CLI — Full argparse headless interface
└── Settings/Presets — JSON persistence