Update app.py

app.py

@@ -129,7 +129,7 @@ def infer(
     ip_source_image=None,   # Исходное изображение IP_adapter
     ip_adapter_image=None,  # Контрольное изображение IP_adapter
     remove_bg=None,         # Удаление фона с изображения
-    LCM_adapter_mode=None,  # Параметр для выбора LCM_adapter
+    LCM_adapter=None,       # Параметр для выбора LCM_adapter
     progress=gr.Progress(track_tqdm=True)
 ):
 
@@ -491,37 +491,73 @@ def infer(
                             generator=generator
                         ).images[0]
         else:
-            # Генерация изображений с LORA без ControlNet и IP_Adapter ---------------------------------------------------------------------------------------------
-
-            # Инициализация ControlNet
-            controlnet_model_path = "lllyasviel/sd-controlnet-openpose"
-            controlnet = ControlNetModel.from_pretrained(controlnet_model_path, torch_dtype=torch_dtype)
+            # Генерация изображений с LCM_Adapter ---------------------------------------------------------------------------------------------
+            
+            if use_LCM_adapter:
+            
+                if LCM_adapter == "lcm-lora-sdv1-5":
+                    adapter_id = "latent-consistency/lcm-lora-sdv1-5"
 
-            generator = torch.Generator(device).manual_seed(seed)
+                generator = torch.Generator(device).manual_seed(seed)
 
-            if model != model_default:
-                pipe = StableDiffusionPipeline.from_pretrained(model, torch_dtype=torch_dtype).to(device)
-                prompt_embeds = long_prompt_encoder(prompt, pipe.tokenizer, pipe.text_encoder)
-                negative_prompt_embeds = long_prompt_encoder(negative_prompt, pipe.tokenizer, pipe.text_encoder)
-                prompt_embeds, negative_prompt_embeds = align_embeddings(prompt_embeds, negative_prompt_embeds)
-            else:
                 pipe = pipe_default
+                pipe.scheduler = LCMScheduler.from_config(pipe.scheduler.config)
+                pipe.to(device)
+
+                pipe.load_lora_weights(adapter_id)
+                pipe.fuse_lora()
+
                 prompt_embeds = long_prompt_encoder(prompt, pipe.tokenizer, pipe.text_encoder)
-                negative_prompt_embeds = long_prompt_encoder(negative_prompt, pipe.tokenizer, pipe.text_encoder)
+                negative_prompt_embeds = long_prompt_encoder(negative_prompt, pipe.tokenizer, pipe_1.text_encoder)
                 prompt_embeds, negative_prompt_embeds = align_embeddings(prompt_embeds, negative_prompt_embeds)
-                pipe.fuse_lora(lora_scale=lora_scale)
 
-            params = {
-                'prompt_embeds': prompt_embeds,
-                'negative_prompt_embeds': negative_prompt_embeds,
-                'guidance_scale': guidance_scale,
-                'num_inference_steps': num_inference_steps,
-                'width': width,
-                'height': height,
-                'generator': generator,
-            }
+                params = {
+                    'prompt_embeds': prompt_embeds,
+                    'negative_prompt_embeds': negative_prompt_embeds,
+                    'guidance_scale': guidance_scale,
+                    'num_inference_steps': num_inference_steps,
+                    'width': width,
+                    'height': height,
+                    'generator': generator,
+                }
+
+                image = pipe(**params).images[0]    
+
+
+            else:        
+            
+                # Генерация изображений с LORA без ControlNet и IP_Adapter ---------------------------------------------------------------------------------------------
+
+                # Инициализация ControlNet
+                controlnet_model_path = "lllyasviel/sd-controlnet-openpose"
+                controlnet = ControlNetModel.from_pretrained(controlnet_model_path, torch_dtype=torch_dtype)
 
-            image = pipe(**params).images[0]
+                generator = torch.Generator(device).manual_seed(seed)
+
+                if model != model_default:
+                    pipe = StableDiffusionPipeline.from_pretrained(model, torch_dtype=torch_dtype).to(device)
+                    prompt_embeds = long_prompt_encoder(prompt, pipe.tokenizer, pipe.text_encoder)
+                    negative_prompt_embeds = long_prompt_encoder(negative_prompt, pipe.tokenizer, pipe.text_encoder)
+                    prompt_embeds, negative_prompt_embeds = align_embeddings(prompt_embeds, negative_prompt_embeds)
+                else:
+                    pipe_default = get_lora_sd_pipeline(lora_dir='lora_man_animestyle', base_model_name_or_path=model_default, dtype=torch_dtype).to(device)
+                    pipe = pipe_default
+                    prompt_embeds = long_prompt_encoder(prompt, pipe.tokenizer, pipe.text_encoder)
+                    negative_prompt_embeds = long_prompt_encoder(negative_prompt, pipe.tokenizer, pipe.text_encoder)
+                    prompt_embeds, negative_prompt_embeds = align_embeddings(prompt_embeds, negative_prompt_embeds)
+                    pipe.fuse_lora(lora_scale=lora_scale)
+
+                params = {
+                    'prompt_embeds': prompt_embeds,
+                    'negative_prompt_embeds': negative_prompt_embeds,
+                    'guidance_scale': guidance_scale,
+                    'num_inference_steps': num_inference_steps,
+                    'width': width,
+                    'height': height,
+                    'generator': generator,
+                }
+
+                image = pipe(**params).images[0]
 
     # Если выбрано удаление фона
     if remove_bg:
@@ -761,13 +797,12 @@ with gr.Blocks(css=css) as demo:
                     interactive=True
                 )
 
-            #with gr.Column(visible=False) as LCM_adapter_options:      
-                LCM_adapter_mode = gr.Dropdown(
-                    label="LCM_Adapter Mode",
+                LCM_adapter = gr.Dropdown(
+                    label="LCM_Adapter Selection",
                     choices=[
-                        "lcm-lora-sdv1-5 ",
+                        "lcm-lora-sdv1-5",
                     ],
-                    value="lcm-lora-sdv1-5 ",
+                    value="lcm-lora-sdv1-5",
                     visible=False,
                     interactive=True,
                 )
@@ -775,7 +810,7 @@ with gr.Blocks(css=css) as demo:
             use_LCM_adapter.change(
                 fn=lambda x: gr.update(visible=x), 
                 inputs=use_LCM_adapter,
-                outputs=LCM_adapter_mode #LCM_adapter_options
+                outputs=LCM_adapter
             )
         # ---------------------------------------------------------------------------------------------------------
 
@@ -819,7 +854,7 @@ with gr.Blocks(css=css) as demo:
             ip_source_image,    # Исходное изображение IP_adapter
             ip_adapter_image,   # Контрольное изображение IP_adapter
             remove_bg,          # Удаление фона с изображения
-            LCM_adapter_mode,   # Параметр для выбора LCM_adapter
+            LCM_adapter,        # Параметр для выбора LCM_adapter
         ],
         outputs=[result],
     )