Yolo V8 Fog Or Smog Classification

🚀 uisikdag/fogsmog_v8

An image classification model based on Ultralytics and YOLOv8, capable of accurately classifying fog and smog images.

🚀 Quick Start

✨ Features

• Supports image classification tasks, specifically for classifying fog and smog.
• Utilizes the Ultralytics library, version 8.0.21.
• Achieves an accuracy of 0.8375 for top1 and 1 for top5.

📦 Installation

• Install ultralyticsplus:

pip install ultralyticsplus==0.0.23 ultralytics==8.0.21

💻 Usage Examples

Basic Usage

from ultralyticsplus import YOLO, postprocess_classify_output

# load model
model = YOLO('uisikdag/fogsmog_v8')

# set model parameters
model.overrides['conf'] = 0.25  # model confidence threshold

# 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].probs) # [0.1, 0.2, 0.3, 0.4]
processed_result = postprocess_classify_output(model, result=results[0])
print(processed_result) # {"cat": 0.4, "dog": 0.6}

📚 Documentation

Supported Labels

['fog', 'smog']

📄 License

No license information provided in the original document.