Update main.py

main.py

@@ -2,6 +2,7 @@ from fastapi import FastAPI
 from pydantic import BaseModel
 from typing import List
 from PIL import Image
+import io
 from sentence_transformers import SentenceTransformer, util
 
 class Item(BaseModel):
@@ -31,7 +32,10 @@ def predict(item: Item):
     # encoded_image = model.encode(Image.open(filepath))
     #image_names = list(glob.glob('./*.jpg'))
     #print("Images:", len(image_names))
-    encoded_image = model.encode([Image.open(item.image1), Image.open(item.image2)], batch_size=128, convert_to_tensor=True, show_progress_bar=True)
+
+
+    
+    encoded_image = model.encode([Image.open(io.BytesIO(item.image1)), Image.open(io.BytesIO(item.image2))], batch_size=128, convert_to_tensor=True, show_progress_bar=True)
     
     # Now we run the clustering algorithm. This function compares images aganist 
     # all other images and returns a list with the pairs that have the highest