from transformers import CLIPProcessor
from aesthetic_scorer import AestheticScorer
import torch
from PIL import Image

# Load the model
processor = CLIPProcessor.from_pretrained("rsinema/aesthetic-scorer")
model = torch.load("rsinema/aesthetic-scorer/model.pt")

# Process an image
image = Image.open("your_image.jpg")
inputs = processor(images=image, return_tensors="pt")["pixel_values"]

# Get scores
with torch.no_grad():
    scores = model(inputs)

# Print results
aesthetic_categories = ["Overall", "Quality", "Composition", "Lighting", "Color", "Depth of Field", "Content"]
for category, score in zip(aesthetic_categories, scores):
    print(f"{category}: {score.item():.2f}/5")