Update pipline_StableDiffusionXL_ConsistentID.py

pipline_StableDiffusionXL_ConsistentID.py

@@ -261,15 +261,8 @@ class ConsistentIDStableDiffusionXLPipeline(StableDiffusionXLPipeline):
                 attn_processor.scale = scale
 
     @torch.inference_mode()
-    def get_prepare_faceid(self, input_image_file=None, input_image_path=None):
-        try:
-            faceid_image = cv2.imread(input_image_path)
-            print(f"input_image_path is : {input_image_path}")
-        except:
-            faceid_image = np.array(input_image_file) ### use the numpy image
-            print(f"input_image_file is : {input_image_file}\r\n")
-
-        print(f"faceid_image is : {faceid_image}")
+    def get_prepare_faceid(self, input_image_path=None):
+        faceid_image = cv2.imread(input_image_path)
         face_info = self.app.get(faceid_image)
         if face_info==[]:
             faceid_embeds = torch.zeros_like(torch.empty((1, 512)))
@@ -514,7 +507,7 @@ class ConsistentIDStableDiffusionXLPipeline(StableDiffusionXLPipeline):
         do_classifier_free_guidance = guidance_scale >= 1.0
         input_image_file = input_id_images[0]
 
-        faceid_embeds = self.get_prepare_faceid(input_image_file=input_image_file, input_image_path=input_image_path)
+        faceid_embeds = self.get_prepare_faceid(input_image_path=input_image_path)
         face_caption = self.get_prepare_llva_caption(input_image_file=input_image_file)
         key_parsing_mask_list, vis_parsing_anno_color = self.get_prepare_facemask(input_image_file)
 
@@ -719,13 +712,4 @@ class ConsistentIDStableDiffusionXLPipeline(StableDiffusionXLPipeline):
         if not return_dict:
             return (image,)
 
-        return StableDiffusionXLPipelineOutput(images=image)
-
-
-
-
-
-
-
-
-
+        return StableDiffusionXLPipelineOutput(images=image)