Mr
This project involved preparing high-quality training data for computer vision models used in object detection and image classification. The scope included annotating thousands of images and video frames with bounding boxes, segmentation masks, and classification labels according to detailed project guidelines. I performed tasks such as identifying and labeling objects of interest, ensuring consistency across similar images, and verifying annotations for accuracy. The project size included over 50,000 images, and I collaborated closely with the AI development team to meet strict quality standards. Quality measures included cross-checking labels, following annotation protocols, and using validation tools to ensure datasets met the required precision for optimal model training.