Update app.py

app.py

@@ -30,13 +30,14 @@ pipe = StableDiffusionPipeline.from_pretrained(
     base_model_path,
     torch_dtype=torch.float16,
     scheduler=noise_scheduler,
-    vae=vae,
-    safety_checker=None  # Disconnected the safety checker
+    vae=vae
 ).to(device)
 
+# Instantiate IPAdapter models
 ip_model = IPAdapterFaceID(pipe, ip_ckpt, device)
 ip_model_plus = IPAdapterFaceIDPlus(pipe, image_encoder_path, ip_plus_ckpt, device)
 
+# Initialize the FaceAnalysis application
 app = FaceAnalysis(name="buffalo_l", providers=['CPUExecutionProvider'])
 app.prepare(ctx_id=0, det_size=(640, 640))
 
@@ -52,7 +53,7 @@ def generate_image(images, prompt, negative_prompt, preserve_face_structure, fac
         faceid_embed = torch.from_numpy(faces[0].normed_embedding).unsqueeze(0)
         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)
+            face_image = face_align.norm_crop(face, landmark=faces[0].kps, image_size=224) # you can also segment the face
             first_iteration = False
             
     average_embedding = torch.mean(torch.stack(faceid_all_embeds, dim=0), dim=0)