# -*- coding: utf-8 -*-
"""
Created on Tue Dec 17 20:35:41 2023

@author: luofeng
"""

from transformers import ViTImageProcessor, ViTForImageClassification
from PIL import Image
#import requests

#url = 'http://images.cocodataset.org/val2017/000000039769.jpg'
#image = Image.open(requests.get(url, stream=True).raw)

processor = ViTImageProcessor.from_pretrained('google/vit-base-patch16-224')
model = ViTForImageClassification.from_pretrained('google/vit-base-patch16-224')

#inputs = processor(images=image, return_tensors="pt")
#outputs = model(**inputs)
#logits = outputs.logits
# model predicts one of the 1000 ImageNet classes
#predicted_class_idx = logits.argmax(-1).item()
#print("Predicted class:", model.config.id2label[predicted_class_idx])


def imageClassification(image_path):
    image = Image.open(image_path)
    inputs = processor(images=image, return_tensors="pt")
    outputs = model(**inputs)
    logits = outputs.logits
    # model predicts one of the 1000 ImageNet classes
    predicted_class_idx = logits.argmax(-1).item()
    classification_result = model.config.id2label[predicted_class_idx]
    print("Predicted class:", classification_result)    
    return classification_result