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sharathhhhh/
safetyHelmet-detection-yolov8

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Model Details

Model Description

This model is trained to detect whether a person is wearing a helmet or not, using YOLOv8. This is a custom-trained YOLOv8 model that detects whether a person is wearing a helmet or not. The goal is to improve road safety and ensure helmet compliance using computer vision.

Developed by: sharathhhhh
Model type: Object detection
Language(s) (NLP): English
License: Apache license 2.0
Finetuned from model [optional]: YOLOv8

Model Details

Model: YOLOv8
Framework: Ultralytics YOLO
Backbone: CSPDarknet
Trained for: Helmet detection on riders using CCTV/video surveillance
Input size: 640x640
Classes:
- with_helmet
- without_helmet

Training Configuration

Epochs: 28
Optimizer: SGD (default)
Loss: YOLOv8 objectness + box + class
Image Size: 640x640
Batch Size: 16

Feel free to reach out on LinkedIn(sharathup) or email me at sharathu0123@gmail.com for collaborations or suggestions.

Example Usage

Install dependencies:

bash

pip install ultralytics


#Load model and predict:

from ultralytics import YOLO
model = YOLO("sharathhhhh/helmet-detection-yolov8")

# Predict on image
results = model("rider.jpg")

# Display results
results[0].show()

sharathhhhh/safetyHelmet-detection-yolov8

Model Details

Model Description

Model Details

Training Configuration

Example Usage

sharathhhhh/
safetyHelmet-detection-yolov8