hareemzahrah/African-Wildlife-Object-Detection

Computer Vision course project for detecting African wildlife using YOLOv8n, YOLOv8s, and YOLO11n # African Wildlife Object Detection It was my computer vision course project for detecting African wildlife using YOLO models. 1. Downloaded the wildlife dataset from Roboflow. 2. Prepared the dataset in YOLO format. 3. Trained three models: - YOLOv8n - YOLOv8s - YOLO11n 4. Compared the models using mAP, Precision and Recall. 5. Selected YOLOv8n as the best-performing model. 6. Tested the trained model on validation images. ## Best Result among all 3 models YOLOv8n - mAP50: 70.79% - mAP50-95: 50.52% - Precision: 57.11% - Recall: 80.75% ## Tools Python, Google Colab, Roboflow, Ultralytics YOLO, PyTorch