wastewise-garbage-cls

WasteWise Garbage Classifier (YOLOv8n-cls)

Fine-tuned YOLOv8n-cls model for waste segregation at office/public kiosks.

Model Details

Classes

Training

• Dataset: garbage_office (8 classes, ~15k images)
• Framework: Ultralytics YOLOv8 + exported to ONNX
• Epochs: 50
• Image size: 224x224
• Augmentation: Standard YOLOv8 augmentation pipeline

Usage (Python)

import numpy as np
from PIL import Image
import onnxruntime as ort

session = ort.InferenceSession("wastewise-yolo.onnx")
img = Image.open("test.jpg").convert("RGB").resize((224, 224))
arr = np.array(img, dtype=np.float32) / 255.0
tensor = arr.transpose(2, 0, 1)[np.newaxis]  # [1, 3, 224, 224]

outputs = session.run(None, {session.get_inputs()[0].name: tensor})
scores = outputs[0][0]
class_id = int(np.argmax(scores))

CLASS_NAMES = ["battery","biological","cardboard","glass","metal","paper","plastic","trash"]
print(f"Predicted: {CLASS_NAMES[class_id]} ({scores[class_id]:.1%})")

Part of WasteWise

This model powers WasteWise - an AI-powered waste segregation kiosk built on SAP BTP.