Yolo V8 Football Players Detection

🚀 uisikdag/football_players_rf

This model is based on Ultralytics and is used for object detection in football scenarios, capable of identifying objects such as balls, goalkeepers, players, and referees.

🚀 Quick Start

This model is designed for object detection in football scenarios. It can identify various objects on the football field, including balls, goalkeepers, players, and referees.

✨ Features

• Supports object detection tasks in football scenarios.
• Can identify labels such as ball, goalkeeper, player, and referee.

📦 Installation

Install ultralyticsplus:

pip install ultralyticsplus==0.0.25 ultralytics==8.0.25

💻 Usage Examples

Basic Usage

from ultralyticsplus import YOLO, render_result

# load model
model = YOLO('uisikdag/football_players_rf')

# 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

['ball', 'goalkeeper', 'player', 'referee']

📊 Model Metrics