jonalvarez01/reto2g2-Object-detection

Mobile and Hat Detection Model - YOLOv8

This repository contains a YOLOv8 model trained to detect mobile phones and hats in images.

Model Description

The model was trained using YOLOv8n architecture to detect two classes:

• Mobile phones
• Hats

Training Details

• Base model: YOLOv8n
• Training epochs: 100
• Hardware: CUDA-enabled GPU
• Framework: Ultralytics YOLO

Usage

from ultralytics import YOLO

# Load the model
model = YOLO('path_to_model.pt')

# Perform detection on an image
results = model('path_to_image.jpg')

Training Code

The model was trained using the following script:

from ultralytics import YOLO

# Load a model
model = YOLO("yolov8n.pt").to('cuda')
# Train the model
results = model.train(data="data.yaml", epochs=100)

Dataset

The model was trained on a custom dataset containing images of mobile phones and caps. The dataset was structured following YOLO format requirements.

Model Performance Metrics

The model's performance was evaluated over 100 epochs of training. Here are the key metrics:

Confusion Matrix

Precision-Recall Curve

F1-Score Curve