Yolov8m Smoke Detection

🚀 kittendev/YOLOv8m-smoke-detection

This project is a smoke detection model based on YOLOv8m, which can accurately detect smoke objects in images. It uses the ultralytics library and is trained on specific datasets to provide high-precision object detection results.

🚀 Quick Start

✨ Features

• Object Detection: Specifically designed for smoke detection, with high precision.
• Easy to Use: Simple installation and integration steps.

📦 Installation

Install ultralyticsplus:

pip install ultralyticsplus==0.0.28 ultralytics==8.0.43

💻 Usage Examples

Basic Usage

from ultralyticsplus import YOLO, render_result

# load model
model = YOLO('kittendev/YOLOv8m-smoke-detection')

# set model parameters
model.overrides['conf'] = 0.25  # NMS confidence threshold
model.overrides['iou'] = 0.45  # NMS IoU threshold
model.overrides['agnostic_nms'] = False  # NMS class-agnostic
model.overrides['max_det'] = 1000  # maximum number of detections per image

# set image
image = 'https://github.com/ultralytics/yolov5/raw/master/data/images/zidane.jpg'

# perform inference
results = model.predict(image)

# observe results
print(results[0].boxes)
render = render_result(model=model, image=image, result=results[0])
render.show()

Supported Labels

['smoke']

📄 License

This project is licensed under the AGPL-3.0 license.

📚 Documentation

Model Information