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SujalKh/
waste-classifier

Name: waste-classifier
Availability: InStock

pytorch

vit

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Waste Classification Model

This model classifies waste items into three categories:

Recyclable
Compostable
General Waste

Model Description

The model is based on the Vision Transformer (ViT) architecture and has been trained on a custom dataset of waste images. It uses the google/vit-base-patch16-224 backbone and has been fine-tuned for waste classification.

Usage

python

from transformers import ViTForImageClassification, ViTImageProcessor
from PIL import Image

# Load model and processor
model = ViTForImageClassification.from_pretrained("your-username/waste-classifier")
processor = ViTImageProcessor.from_pretrained("your-username/waste-classifier")

# Load and preprocess image
image = Image.open("path_to_image.jpg")
inputs = processor(images=image, return_tensors="pt")

# Get prediction
outputs = model(**inputs)
predicted_class = outputs.logits.argmax(-1).item()
classes = ['compostable', 'general_waste', 'recyclable']
prediction = classes[predicted_class]

Training Data

The model was trained on a custom dataset of waste images, including:

Recyclable items (plastic, glass, metal, paper)
Compostable items (food waste, plant materials)
General waste (non-recyclable materials)

Performance

The model achieves the following performance metrics:

Accuracy: ~X%
Precision: ~X%
Recall: ~X%
F1 Score: ~X%

Limitations

The model works best with clear, well-lit images
Performance may vary with different lighting conditions
Some items may be ambiguous between categories

License

This model is available for use under the MIT license.

SujalKh/waste-classifier