E-commerce Product Image Annotation for Object Detection Model
I Worked on a large-scale image annotation project for an e-commerce platform in New orleans to improve product recognition and search accuracy. The project involved labeling over 8,000 product images across categories such as clothing, footwear, and accessories. My responsibilities included drawing precise bounding boxes around products, ensuring correct classification, and maintaining consistency across similar items. I followed strict annotation guidelines and naming conventions to ensure dataset uniformity. Also Implemented quality control measures such as cross-reviewing annotations, correcting edge-case errors, and maintaining over 98% accuracy. Used annotation tools like LabelImg and CVAT to complete tasks efficiently within deadlines. This project contributed to training a computer vision model that improved automated product tagging and recommendation systems.