A live camera-based candy-object detection demonstration using a trained YOLO model.
YOLO Live Candy Detection is a computer-vision learning project where a camera feed is processed by a trained YOLO object-detection model to identify candy items.
camera_detect.py — live detection scriptbest.pt — saved model weightsI also explained and demonstrated the result in a LinkedIn video post. The public post URL can be added in the project editor when available.
ISSUE / 007
A final-year truck-booking and bidding platform connecting shippers with verified truck owners.
ISSUE / 005
A 3D helicopter and sky simulation built with C++ and OpenGL/GLUT for computer graphics coursework.
A deep learning-based playing card classifier built with PyTorch and EfficientNet-B0. Trained to recognize 53 playing card classes, achieving approximately 92% validation accuracy, with a Streamlit web app displaying predictions and top-5 class probabilities.