Create app.py

app.py

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+import gradio as gr
+from transformers import CLIPModel, CLIPProcessor
+from PIL import Image
+import torch
+
+# Load model and processor
+model_name = "jinaai/jina-clip-v1"
+model = CLIPModel.from_pretrained(model_name)
+processor = CLIPProcessor.from_pretrained(model_name)
+
+def compute_similarity(image, text):
+    image = Image.fromarray(image)  # Convert NumPy array to PIL image
+
+    # Process inputs
+    inputs = processor(text=[text], images=image, return_tensors="pt", padding=True, truncation=True)
+
+    with torch.no_grad():
+        outputs = model(**inputs)
+        logits_per_image = outputs.logits_per_image  # Image-to-text similarity
+        similarity_score = logits_per_image.item()
+    
+    return similarity_score
+
+# Gradio UI
+demo = gr.Interface(
+    fn=compute_similarity,
+    inputs=[gr.Image(type="numpy"), gr.Textbox(label="Enter text")],
+    outputs=gr.Number(label="Similarity Score"),
+    title="CLIP Image-Text Similarity",
+    description="Upload an image and enter a text prompt to get the similarity score."
+)
+
+demo.launch()