nateraw/food

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

# Cargar el model
model = ViTForImageClassification.from_pretrained('nateraw/food')
# Extraer características
feature_extractor = ViTFeatureExtractor.from_pretrained('nateraw/food')

# Función de predicción
def predict(image_path):
    image = Image.open(image_path)
    inputs = feature_extractor(images=image, return_tensors='pt')
    outputs = model(**inputs)
    logits = outputs.logits
    predicted_class_idx = logits.argmax(-1).item()
    return predicted_class_idx

# Ejemplo de uso
predicted_class = predict('ruta/a/la/imagen.jpg')
print(f'Predicted class: {predicted_class}')