app.py

from fastapi import FastAPI, UploadFile, File, HTTPException
from PIL import Image
import torch
import logging
from models import GarbageClassifier

app = FastAPI()

logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)

# Load model and processor
model_dir = "youssefabdelmottaleb/Garbage-Classification-SWIN-Transformer"
classifier = GarbageClassifier(model_dir)


# Endpoint to receive images and return predictions
@app.post("/predict")
async def predict_endpoint(file: UploadFile = File(...)):
    try:
        image = Image.open(file.file).convert("RGB")
        inputs = classifier.processor(images=image, return_tensors="pt")

        with torch.no_grad():
            outputs = classifier.model(**inputs)

        logits = outputs.logits
        predicted_class_idx = logits.argmax(-1).item()
        predicted_class = classifier.labels[predicted_class_idx]

        return {"class": predicted_class}

    except Exception as e:
        logger.error(f"Error processing image: {e}")
        raise HTTPException(status_code=500, detail="Error processing image")


image_path = "C:/Users/youss/Downloads/paperr.jpg"
classifier.evaluate_image(image_path)

# To run the app: uvicorn app:app --host 0.0.0.0 --port 8000