Yolov8m Plane Detection

🚀 keremberke/yolov8m-plane-detection

This model is designed for plane detection, leveraging the power of YOLOv8 in the ultralytics library. It offers high precision in the plane - detection task.

🚀 Quick Start

✨ Features

• Object Detection: Specialized in detecting planes.
• High Precision: Achieves a mAP@0.5(box) of 0.995 on the keremberke/plane - detection validation dataset.

📦 Installation

• Install ultralyticsplus:

pip install ultralyticsplus==0.0.23 ultralytics==8.0.21

💻 Usage Examples

Basic Usage

from ultralyticsplus import YOLO, render_result

# load model
model = YOLO('keremberke/yolov8m-plane-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()

📚 Documentation

Supported Labels

['planes']

Model Information

Model Performance

💡 Usage Tip

More models are available at awesome-yolov8-models.