from PIL import Image
import requests
from transformers import CLIPProcessor, CLIPModel
def classife(img):
    model = CLIPModel.from_pretrained("openai/clip-vit-large-patch14")
    processor = CLIPProcessor.from_pretrained("openai/clip-vit-large-patch14")
    image = Image.open(img)
    inputs = processor(text=["Health Person", "Weak Person","Fat person"], images=image, return_tensors="pt", padding=True)
    outputs = model(**inputs)
    logits_per_image = outputs.logits_per_image # this is the image-text similarity score
    probs = logits_per_image.softmax(dim=1)
    labels = ["Health", "weak","fat"]
    predicted_label = labels[probs.argmax()]
    return predicted_label

# url = "https://c8.alamy.com/comp/GJ4Y4H/very-obese-man-GJ4Y4H.jpg"
# img = requests.get(url, stream=True).raw

# probabilities = classif(img)
# print(f"Probabilities: {probabilities}")