VID2IMG Pro is a local-first, high-performance video-to-image extraction framework designed for developers building computer vision, AI, photogrammetry, and privacy-aware media pipelines.
It provides a clean, extensible Python codebase that handles frame extraction, anonymization, and export with deterministic, photogrammetry-ready output — without cloud dependencies, logins, or external APIs.
Built on OpenCV, NumPy, and Tkinter/ttkbootstrap, VID2IMG Pro is ideal as a standalone desktop tool or as a foundation for custom CV workflows.
Why Developers Use VID2IMG Pro
Local-only processing (no telemetry, no cloud calls)
Deterministic frame extraction for reproducible pipelines
Privacy-first design (face + license plate anonymization)
Photogrammetry-safe output (lossless, sequential frames)
360° equirectangular-safe processing
Readable, hackable Python codebase
No vendor lock-in
Use it as:
A desktop utility
A CV preprocessing stage
A research tool
A base for internal tooling
A teaching reference for OpenCV + GUI integration
Core Capabilities
🎞 Frame Extraction Engine
Supports MP4, AVI, MOV
Interval-based extraction (frame count–based)
Fast OpenCV-backed decoding
Handles large videos (thousands of frames)
🔐 Automated Anonymization
Face detection with Gaussian blur
License plate detection with pixelation
Designed for GDPR / privacy-sensitive datasets
Modular anonymization logic (easy to extend)
🌍 360° Video Mode
Equirectangular-safe processing
Prevents seam distortion
Maintains spatial continuity
🧱 Photogrammetry Mode
Lossless PNG output
Sequential filenames (frame_00001.png)
No resizing, no recompression
Compatible with:
RealityCapture
Meshroom
Metashape
COLMAP
Design principles
Separation of GUI and processing logic
No global state
Safe cancellation via controlled loops
Predictable output paths
Synchronous local execution
GUI Framework
Tkinter (native, zero dependencies)
ttkbootstrap for modern theming
Responsive layout
Real-time log panel
Progress bar with frame counters
Safe Start / Stop controls
GUI can be removed entirely if you want a CLI-only build.
Extending VID2IMG Pro
Common extensions developers add:
CLI interface
YOLO / MediaPipe anonymization
Timestamp-based extraction
GPU acceleration
Custom metadata export (CSV / JSON)
Headless batch mode
Integration into ML pipelines
The codebase is intentionally clean and modification-friendly.
System Requirements
Source Code Version
Python 3.8+
OpenCV
NumPy
ttkbootstrap
Runs on:
Windows
macOS
Linux
EXE Version
Windows 10+
No Python required
Fully portable
No installer
Licensing (Developer-Friendly)
Single-user license
Personal and commercial use allowed
Source code modification permitted
❌ No resale or redistribution as a competing product
All rights reserved by Mate Technologies
Ideal Use Cases
AI dataset generation
CV preprocessing
Privacy-compliant research
Drone footage processing
360° video analysis
Photogrammetry pipelines
Internal tools for enterprises
Teaching OpenCV + GUI integration
Buy / More Details
👉 https://gum.new/gum/cmk5ut3j8000i04l1fdp098nh
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