Update app.py

app.py

@@ -11,14 +11,14 @@ tqdm.monitor_interval = 0
 
 # Load the diffusion pipelines
 pipe1 = StableDiffusionXLPipeline.from_pretrained(
-    "kayfahaarukku/UrangDiffusion-1.3", 
+    "kayfahaarukku/UrangDiffusion-1.4", 
     torch_dtype=torch.float16, 
     custom_pipeline="lpw_stable_diffusion_xl",
 )
 pipe1.scheduler = EulerAncestralDiscreteScheduler.from_config(pipe1.scheduler.config)
 
 pipe2 = StableDiffusionXLPipeline.from_pretrained(
-    "kayfahaarukku/UrangDiffusion-1.4", 
+    "kayfahaarukku/UrangDiffusion-2.0", 
     torch_dtype=torch.float16, 
     custom_pipeline="lpw_stable_diffusion_xl",
 )
@@ -33,7 +33,7 @@ def generate_comparison(prompt, negative_prompt, use_defaults, resolution, guida
     if randomize_seed:
         seed = random.randint(0, 99999999)
     if use_defaults:
-        prompt = f"{prompt}, masterpiece, best quality, amazing quality, very aesthetic"
+        prompt = f"{prompt}, best quality, amazing quality, very aesthetic"
         negative_prompt = f"nsfw, lowres, (bad), text, error, fewer, extra, missing, worst quality, jpeg artifacts, low quality, watermark, unfinished, displeasing, oldest, early, chromatic aberration, signature, extra digits, artistic error, username, scan, [abstract], {negative_prompt}"
     generator = torch.manual_seed(seed)
     
@@ -43,7 +43,7 @@ def generate_comparison(prompt, negative_prompt, use_defaults, resolution, guida
     
     width, height = map(int, resolution.split('x'))
     
-    # Generate image with UrangDiffusion-1.3
+    # Generate image with UrangDiffusion-1.4
     image1 = pipe1(
         prompt, 
         negative_prompt=negative_prompt,
@@ -56,7 +56,7 @@ def generate_comparison(prompt, negative_prompt, use_defaults, resolution, guida
         callback_steps=1
     ).images[0]
 
-    # Generate image with UrangDiffusion-1.4
+    # Generate image with UrangDiffusion-2.0
     image2 = pipe2(
         prompt, 
         negative_prompt=negative_prompt,
@@ -81,12 +81,12 @@ def interface_fn(prompt, negative_prompt, use_defaults, resolution, guidance_sca
     return image1, image2, seed, gr.update(value=metadata_text)
 
 def reset_inputs():
-    return gr.update(value=''), gr.update(value=''), gr.update(value=True), gr.update(value='896x1152'), gr.update(value=7), gr.update(value=28), gr.update(value=0), gr.update(value=True), gr.update(value='')
+    return gr.update(value=''), gr.update(value=''), gr.update(value=True), gr.update(value='832x1216'), gr.update(value=7), gr.update(value=28), gr.update(value=0), gr.update(value=True), gr.update(value='')
 
 with gr.Blocks(title="UrangDiffusion Comparison Demo", theme="NoCrypt/miku@1.2.1") as demo:
     gr.HTML(
-        "<h1>UrangDiffusion 1.3 vs 1.4 Comparison Demo</h1>"
-        "This demo showcases a comparison between UrangDiffusion 1.3 and 1.4."
+        "<h1>UrangDiffusion 1.4 vs 2.0 Comparison Demo</h1>"
+        "This demo showcases a comparison between UrangDiffusion 1.4 and 2.0."
         )
     with gr.Row():
         with gr.Column():
@@ -99,19 +99,19 @@ with gr.Blocks(title="UrangDiffusion Comparison Demo", theme="NoCrypt/miku@1.2.1
                     "1344x768", "768x1344", "1536x640", "640x1536"
                 ],
                 label="Resolution",
-                value="896x1152"
+                value="832x1216"
             )
-            guidance_scale_input = gr.Slider(minimum=1, maximum=20, step=0.5, label="Guidance Scale", value=5)
-            num_inference_steps_input = gr.Slider(minimum=1, maximum=100, step=1, label="Number of Inference Steps", value=26)
-            seed_input = gr.Slider(minimum=0, maximum=99999999, step=1, label="Seed", value=0, interactive=True)
+            guidance_scale_input = gr.Slider(minimum=1, maximum=20, step=0.5, label="Guidance Scale", value=7)
+            num_inference_steps_input = gr.Slider(minimum=1, maximum=100, step=1, label="Number of Inference Steps", value=28)
+            seed_input = gr.Slider(minimum=0, maximum=999999999, step=1, label="Seed", value=0, interactive=True)
             randomize_seed_input = gr.Checkbox(label="Randomize Seed", value=True)
             generate_button = gr.Button("Generate Comparison")
             reset_button = gr.Button("Reset")
 
         with gr.Column():
             with gr.Row():
-                output_image1 = gr.Image(type="pil", label="UrangDiffusion 1.3")
-                output_image2 = gr.Image(type="pil", label="UrangDiffusion 1.4")
+                output_image1 = gr.Image(type="pil", label="UrangDiffusion 1.4")
+                output_image2 = gr.Image(type="pil", label="UrangDiffusion 2.0")
             with gr.Accordion("Parameters", open=False):
                 gr.Markdown(
                     """
@@ -122,9 +122,9 @@ with gr.Blocks(title="UrangDiffusion Comparison Demo", theme="NoCrypt/miku@1.2.1
             gr.Markdown(
                 """
                 ### Recommended prompt formatting:
-                `1girl/1boy, character name, from what series, everything else in any order, masterpiece, best quality`
+                `1girl/1boy, character name, from what series, everything else in any order, best quality, amazing quality, very aesthetic`
 
-                **PS:** `masterpiece, best quality, amazing quality, very aesthetic` is automatically added when "Use Default Quality Tags and Negative Prompt" is enabled
+                **PS:** `best quality, amazing quality, very aesthetic` is automatically added when "Use Default Quality Tags and Negative Prompt" is enabled
 
                 ### Recommended settings:
                 - Steps: 25-30