🎬 I Built a Python Tool to Extract Images from Videos (with OpenCV + Tkinter)

Extracting frames from videos sounds simple… until you actually need: Custom frame intervals Privacy protection (faces, license plates) Clean datasets for AI or photogrammetry A usable UI (not just scripts) So I built a desktop tool to solve all of that. 👉 VID2IMG Free — a Python-based video-to-image extraction app with built-in anonymization and a modern UI. 🚀 What This Tool Does At its core, VID2IMG uses OpenCV to process video frames and export them as images. But I added a few features that make it more practical for real-world use: 🎥 Frame Extraction Engine Supports MP4, AVI, MOV Configurable frame interval Efficient sequential processing if idx % frame_interval.get() == 0: cv2.imwrite(path, frame) 🔒 Anonymization (Computer Vision) Using Haar cascades from OpenCV: Face detection → Gaussian blur License plates → pixelation faces = face_cascade.detectMultiScale(gray, 1.2, 5) frame[y:y+h, x:x+w] = cv2.GaussianBlur(roi, (51, 51), 0) This makes it useful for: Privacy-safe datasets Stre