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from transformers import ViTFeatureExtractor, ViTForImageClassification
from PIL import Image
import requests

# url = 'http://images.cocodataset.org/val2017/000000039769.jpg'

url = 'https://www.transports.gouv.ci/sites/default/files/securite/103954442_3606826602680429_4157569258353658362_n.jpg'
image = Image.open(requests.get(url, stream=True).raw)

# from IPython.display import Image
image.show()
feature_extractor = ViTFeatureExtractor.from_pretrained(
    'google/vit-base-patch16-224')
model = ViTForImageClassification.from_pretrained(
    'google/vit-base-patch16-224')

inputs = feature_extractor(images=image, return_tensors="pt")
outputs = model(**inputs)
logits = outputs.logits

predicted_class_idx = logits.argmax(-1).item()
print("Predicted class:", model.config.id2label[predicted_class_idx])