๐Ÿšฎ Waste Classification YOLOv8 (Kendrick's Model v1)

This is a YOLOv8-based object detection model trained to classify and detect various types of waste materials. It can help in automating smart waste segregation, improving recycling processes, and contributing to environmental sustainability.

๐Ÿ“‚ Classes Detected

The model was trained to recognize 12 waste categories:

  • battery
  • biological
  • brown-glass
  • cardboard
  • clothes
  • green-glass
  • metal
  • paper
  • plastic
  • shoes
  • trash
  • white-glass

๐Ÿ“Š Training Details

  • Model: YOLOv8
  • Dataset: Custom dataset structured with train/, valid/, and test/ folders
  • Image Size: 640x640
  • Epochs: 30
  • Batch Size: 16
  • Framework: Ultralytics YOLOv8 (PyTorch-based)
  • Hardware: Trained using GPU A100 on Google Colab

๐Ÿš€ How to Use

Install Ultralytics:

from ultralytics import YOLO

# Load the model from Hugging Face
model = YOLO("kendrickfff/waste-classification-yolov8-ken")

# Run inference on an image
results = model("path/to/image.jpg")

# Show results
results.show()
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