app.py

import gradio as gr
from transformers import CLIPProcessor, CLIPModel

model = CLIPModel.from_pretrained("openai/clip-vit-base-patch16")
processor = CLIPProcessor.from_pretrained("openai/clip-vit-base-patch16")


def calculate_score(image, text):
  labels = text.split(';')
  labels = [l.strip() for l in labels]
  labels = list(filter(None, labels))
  if len(labels) == 0 :
    return dict()
  inputs = processor(text=labels, images=image, return_tensors="pt", padding=True)
  outputs = model(**inputs)
  logits_per_image = outputs.logits_per_image.detach().numpy()
  
  results_dict = {label:score/100.0 for label,score in zip(labels, logits_per_image[0])}
  return  results_dict


if __name__ == "__main__":
    demo = gr.Interface(fn=calculate_score, inputs=["image", "text"], outputs="label")
    demo.launch()