read.py

import torch
from PIL import Image

def classify(model, img, trans=None, classes=[], device=torch.device("cpu")):
    try:
        model = model.eval()
        img = img.convert("RGB")
        img = trans(img)
        img = img.unsqueeze(0)
        img = img.to(device)

        output = model(img)
        _, pred = torch.max(output, 1)
        procent = torch.sigmoid(output)
        
        return f"It {classes[pred.item()]} i'm {procent[0][pred[0]]*100:.2f}% sure"
    except Exception:
        return "Something went wrong😕, please notify the developer with the following message: " + str(Exception)