from typing import Dict, List, Any import numpy as np from transformers import CLIPProcessor, CLIPModel from PIL import Image from io import BytesIO import base64 print ("Start Pleds") class EndpointHandler(): def __init__(self, path=""): # Preload all the elements you we need at inference. self.model = CLIPModel.from_pretrained("openai/clip-vit-base-patch32") self.processor = CLIPProcessor.from_pretrained("openai/clip-vit-base-patch32") def __call__(self, data: Dict[str, Any]) -> List[Dict[str, Any]]: inputs = data.get("inputs") text = inputs.get("text") imageData = inputs.get("image") image = Image.open(BytesIO(base64.b64decode(imageData))) inputs = self.processor(text=text, images=image, return_tensors="pt", padding=True) outputs = self.model(**inputs) embeddings = outputs.image_embeds.detach().numpy().flatten().tolist() return { "embeddings": embeddings }