Update app.py

app.py

@@ -60,7 +60,7 @@ def generate_image(images, prompt, negative_prompt, preserve_face_structure, fac
     for image in images:
         face = cv2.imread(image)
         faces = app.get(face)
-        faceid_embed = torch.from_numpy(faces[0].normed_embedding).unsqueeze(0)
+        faceid_embed = torch.from_numpy(faces[0].normed_embedding).unsqueeze(0).to(dtype=torch.float32)  # Ensure embedding dtype matches model dtype
         faceid_all_embeds.append(faceid_embed)
         if(first_iteration and preserve_face_structure):
             face_image = face_align.norm_crop(face, landmark=faces[0].kps, image_size=224)  # you can also segment the face