Practical Computer Vision Mastery: 20+ Python & AI Projects

About this course

Unlock the power of image- and video-based AI in 2026 with 20+ real-time projects that guide you from foundational theory to fully functional applications. Designed for engineering and science students, STEM graduates, and professionals switching into AI, this hands-on course equips you with end-to-end computer vision skills to build a standout portfolio.

Key Highlights:

Environment Setup & Basics: Install Python, configure VS Code, and master OpenCV operations—image I/O, color spaces, resizing, thresholding, filters, morphology, bitwise ops, and histogram equalization.

Core & Advanced Techniques: Implement edge detection (Sobel, Canny), contour/corner/keypoint detection, texture analysis, optical flow, object tracking, segmentation, and OCR with Tesseract.

Deep Learning Integration: Train and deploy TensorFlow/Keras models (EfficientNet-B0) alongside YOLOv7-tiny and YOLOv8 for robust detection tasks.

GUI Development: Build interactive Tkinter interfaces to visualize live video feeds, detection results, and system dashboards.20+ Hands-On Projects Include:

• Smart Face Attendance with face enrollment, embedding extraction, model training, and GUI integration.
• Driver Drowsiness Detection using EAR/MAR algorithms and real-time alert dashboards.
• YOLO Object & Weapon Detection pipelines for live inference and visualization.
• People Counting & Entry/Exit Tracking with configurable line-coordinate logic.
• License-Plate & Traffic Sign Recognition leveraging Roboflow annotations and custom model training.
• Intrusion & PPE Detection for workplace safety monitoring.

Accident & Fall Detection

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