| from sentence_transformers import SentenceTransformer, util | |
| from PIL import Image | |
| from io import BytesIO | |
| import gradio as gr | |
| import requests | |
| def get_image_embedding(image): | |
| image_model = SentenceTransformer('clip-ViT-B-32') | |
| # Load and preprocess the image | |
| img_emb = image_model.encode(image) | |
| print(img_emb) | |
| print(type(img_emb)) | |
| return {"prediction": img_emb.tolist()} | |
| image_input = gr.Image(type="pil") | |
| label_output = gr.JSON() | |
| gr.Interface(fn=get_image_embedding, inputs=image_input, outputs=label_output).launch() | |