YOLO_oo : Workflow for Oocyte Detection Using YOLOv5

Description Oocyte quantification in histological slides has traditionally been manual, making it time-consuming and subjective. This project introduces an automated YOLOv5s-based workflow for detecting oocytes in mole-rat histological images. Validated across three species, the model achieved high accuracy and consistency, matching manual annotations while significantly reducing analysis time. This approach standardizes quantification and offers a scalable, objective alternative to manual assessment in reproductive biology.