Update app.py

app.py

@@ -103,7 +103,7 @@ def infer(
 ):
     generator = torch.Generator(device).manual_seed(seed)
 
-    # Генерация с Ip_Adapter
+    # Генерация с Ip_Adapter ------------------------------------------------------------------------------------------------------------------
     if use_ip_adapter and ip_source_image is not None and ip_adapter_image is not None:
         #pipe_controlnet = StableDiffusionControlNetImg2ImgPipeline.from_pretrained(    
         pipe_ip_adapter = StableDiffusionControlNetPipeline.from_pretrained(
@@ -166,7 +166,7 @@ def infer(
             generator=generator,
         ).images[0]
     else:
-        # Генерация с ControlNet
+        # Генерация с ControlNet ----------------------------------------------------------------------------------------------------------------
         if use_control_net and control_image is not None and cn_source_image is not None:
             pipe_controlnet = StableDiffusionControlNetImg2ImgPipeline.from_pretrained(    
                 model_default,
@@ -224,7 +224,7 @@ def infer(
                 generator=generator
             ).images[0]
         else:
-            # Генерация без ControlNet и IP_adapter
+            # Генерация без ControlNet и IP_adapter ---------------------------------------------------------------------------------------------
             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)
@@ -249,7 +249,8 @@ def infer(
         
             image = pipe(**params).images[0]
     
-    return image
+    return image 
+    # ---------------------------------------------------------------------------------------------------------------------------------------------
 
 examples = [
     "A young man in anime style. The image is characterized by high definition and resolution. Handsome, thoughtful man, attentive eyes. The man is depicted in the foreground, close-up or in the middle. High-quality images of the face, eyes, nose, lips, hands and clothes. The background and background are blurred and indistinct. The play of light and shadow is visible on the face and clothes.",
@@ -272,6 +273,7 @@ available_models = [
     "CompVis/stable-diffusion-v1-4",
 ]
 
+# -------------------------------------------------------------------------------------------------------------------------------------------------
 with gr.Blocks(css=css) as demo:
     with gr.Column(elem_id="col-container"):
         gr.Markdown(" # Text-to-Image Gradio Template from V. Gorsky")
@@ -351,7 +353,7 @@ with gr.Blocks(css=css) as demo:
                     value=512,
                 )
 
-        # ControlNet ---------------------------------------------------------------------------------
+        # ControlNet -----------------------------------------------------------------------------------------------
         with gr.Blocks():
             with gr.Row():
                 use_control_net = gr.Checkbox(
@@ -397,7 +399,7 @@ with gr.Blocks(css=css) as demo:
                 outputs=control_net_options
             )
 
-        # IP_Adapter ---------------------------------------------------------------------------------
+        # IP_Adapter ------------------------------------------------------------------------------------------------
         with gr.Blocks():
             with gr.Row():
                 use_ip_adapter = gr.Checkbox(
@@ -442,7 +444,7 @@ with gr.Blocks(css=css) as demo:
                 inputs=use_ip_adapter,
                 outputs=ip_adapter_options
             )
-        # --------------------------------------------------------------------------------------
+        # ---------------------------------------------------------------------------------------------------------
         
         gr.Examples(examples=examples, inputs=[prompt], label="Examples for prompt:")
         gr.Examples(examples=examples_negative, inputs=[negative_prompt], label="Examples for negative prompt:")