This repository demonstrates how to implement object detection using the YOLOv8 model with Ultralytics to detect dog faces in images. The project leverages a pre-trained YOLO model to accurately detect and localize dog faces, a task that falls under the category of object detection.
The dataset used for training and testing comes from Dog Face Detection (YOLO Format), which contains labeled images specifically tailored for identifying dog faces. The model has been fine-tuned on this dataset, demonstrating its effectiveness in detecting dog faces across a variety of images.
- YOLOv8 for Object Detection: Utilizes the latest version of the YOLO (You Only Look Once) algorithm to detect dog faces in real-time, offering fast and accurate results.
- Ultralytics Integration: Makes use of Ultralytics' seamless implementation of YOLOv8, which simplifies the training and deployment process.
- Pretrained Model: Starts with a pretrained YOLOv8 model to speed up training and enhance accuracy, taking advantage of the robust object detection capabilities of YOLO.
This project demonstrates the power of combining YOLOv8's object detection capabilities with Ultralytics’ ease of use, enabling efficient and accurate detection of dog faces in images.