LiveDetect - Real-Time Object Detection
LiveDetect is a real-time object detection application that uses a pre-trained TensorFlow SSD MobileNet v2 COCO model to detect and classify objects in live video streams. The application captures video from your webcam, processes frames using OpenCV's DNN module, and displays detected objects with bounding boxes, class names, and confidence scores in real-time. It supports the full COCO dataset with 80 object classes, making it suitable for various computer vision applications.
Year
2024
Role
AI/ML Developer
Technologies
Python, OpenCV, TensorFlow, SSD MobileNet v2, NumPy, Matplotlib, Computer Vision, Deep Learning
Challenge
Implementing real-time object detection with high accuracy and performance. The challenge was to process video frames efficiently while maintaining detection accuracy and displaying results in real-time without significant lag.
Solution
Utilized OpenCV's DNN module with a pre-trained SSD MobileNet v2 model optimized for real-time performance. The lightweight MobileNet architecture ensures fast inference while maintaining good detection accuracy. Implemented efficient frame processing pipeline with OpenCV for video capture and visualization.
Results
Real-time object detection from webcam feed
Support for 80 COCO dataset object classes
Efficient processing with SSD MobileNet v2 architecture
Display of bounding boxes, labels, and confidence scores
Optimized for real-time performance