init

app.py

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+import gradio as gr
+import numpy as np
+from PIL import Image
+from sentence_transformers import SentenceTransformer
+
+model = SentenceTransformer('clip-ViT-B-32')
+
+
+def image_to_embedding(img: np.ndarray):
+    embedding = model.encode(sentences=[Image.fromarray(img)], batch_size=128)
+    return embedding
+
+
+iface = gr.Interface(fn=image_to_embedding, inputs="image", outputs="textbox", cache_examples=True)
+iface.launch()

requirements.txt

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+gradio~=3.41.2
+sentence-transformers
+numpy~=1.25.2
+Pillow~=10.0.0