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jonalvarez01/
reto2g2-Object-detection

Name: reto2g2-Object-detection
Availability: InStock

jonalvarez01/reto2g2-dataset

Ultralytics/YOLOv8

finetune

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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

python

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:

python

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:

jonalvarez01/
reto2g2-Object-detection

Mobile and Hat Detection Model - YOLOv8

Model Description

Training Details

Usage

Training Code

Dataset

Model Performance Metrics

Confusion Matrix

Precision-Recall Curve

F1-Score Curve

jonalvarez01/reto2g2-Object-detection

Mobile and Hat Detection Model - YOLOv8

Model Description

Training Details

Usage

Training Code

Dataset

Model Performance Metrics

Confusion Matrix

Precision-Recall Curve

F1-Score Curve

jonalvarez01/
reto2g2-Object-detection