ysfad/openclip-finetune-waste

Finetuned CLIP for Waste Classification

This model is a finetuned version of OpenAI's CLIP ViT-B/16 for waste classification.

Model Details

• Model Name: ViT-B-16
• Pretrained: laion2b_s34b_b88k
• Classes: 30 waste categories
• Validation Accuracy: 0.9133

Classes

The model can classify the following waste items: aerosol_cans, aluminum_food_cans, aluminum_soda_cans, cardboard_boxes, cardboard_packaging, clothing, coffee_grounds, disposable_plastic_cutlery, eggshells, food_waste, glass_beverage_bottles, glass_cosmetic_containers, glass_food_jars, magazines, newspaper, office_paper, paper_cups, plastic_cup_lids, plastic_detergent_bottles, plastic_food_containers, plastic_shopping_bags, plastic_soda_bottles, plastic_straws, plastic_trash_bags, plastic_water_bottles, shoes, steel_food_cans, styrofoam_cups, styrofoam_food_containers, tea_bags

Usage

from clip_waste_classifier.finetuned_classifier import FinetunedCLIPWasteClassifier

# Load model from Hugging Face Hub
classifier = FinetunedCLIPWasteClassifier(hf_model_id="ysfad/openclip-finetune-waste")

# Classify image
result = classifier.classify_image("path/to/image.jpg")
print(f"Predicted: {result['predicted_item']} ({result['best_confidence']:.3f})")

Training

This model was finetuned on the Recyclable and Household Waste Classification dataset with:

• 15,000 images across 30 waste categories
• 15 epochs of training
• Batch size: 16
• Learning rate: 5e-6
• Train/Val/Test split: 70%/10%/20%

License

This model is released under the MIT License.