added model

handler.py

@@ -0,0 +1,27 @@
+from typing import Any, Dict, List, AnyStr
+import numpy as np
+from transformers import CLIPProcessor, CLIPModel
+from PIL import Image
+from io import BytesIO
+import base64
+
+class EndpointHandler():
+    def __init__(self, path="") -> None:
+        "Preload all the elements we need at inference."
+        self.model = CLIPModel.from_pretrained("openai/clip-vit-base-patch32")
+        self.processor = CLIPProcessor.from_pretrained("openai/clip-vit-base-patch32")
+        self.path = path
+    
+    def __call__(self, data: Dict[str, AnyStr]) -> List[Dict[str, AnyStr]]:
+        "Run the inference."
+        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)
+        image_embeds = outputs.image_embeds.detach().numpy().flatten().tolist()
+        text_embeds = outputs.text_embeds.detach().numpy().flatten().tolist()
+        logits_per_image = outputs.logits_per_image.detach().numpy().flatten().tolist()
+        return {'image_embeddings': image_embeds, 'text_embeddings': text_embeds, 'logits_per_image': logits_per_image}
+    

requirements.txt

@@ -0,0 +1,2 @@
+pillow
+numpy