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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() |