Update app.py

app.py

@@ -1,14 +1,12 @@
-import os
 import gradio as gr
 import numpy as np
-import random
 import torch
 from diffusers import StableDiffusionPipeline
 from peft import PeftModel, LoraConfig
-
+import os
 
 def get_lora_sd_pipeline(
-    ckpt_dir='./lora_man_animestyle', 
+    ckpt_dir='./lora_logos', 
     base_model_name_or_path=None, 
     dtype=torch.float16, 
     adapter_name="default"
@@ -55,10 +53,10 @@ def align_embeddings(prompt_embeds, negative_prompt_embeds):
            torch.nn.functional.pad(negative_prompt_embeds, (0, 0, 0, max_length - negative_prompt_embeds.shape[1]))
 
 device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
-model_id_default = "stable-diffusion-v1-5/stable-diffusion-v1-5"
+model_id_default = "CompVis/stable-diffusion-v1-4"
 torch_dtype = torch.float16 if torch.cuda.is_available() else torch.float32
 
-pipe_default = get_lora_sd_pipeline(ckpt_dir='./lora_man_animestyle', base_model_name_or_path=model_id_default, dtype=torch_dtype).to(device)
+pipe_default = get_lora_sd_pipeline(ckpt_dir='./lora_logos', base_model_name_or_path=model_id_default, dtype=torch_dtype).to(device)
 
 MAX_SEED = np.iinfo(np.int32).max
 MAX_IMAGE_SIZE = 1024
@@ -69,9 +67,9 @@ def infer(
     width=512, 
     height=512, 
     num_inference_steps=20, 
-    model_id="stable-diffusion-v1-5/stable-diffusion-v1-5", 
+    model_id='CompVis/stable-diffusion-v1-4', 
     seed=42, 
-    guidance_scale=7.5, 
+    guidance_scale=7.0, 
     lora_scale=0.5,
     progress=gr.Progress(track_tqdm=True)
     ):
@@ -104,21 +102,6 @@ def infer(
     
     return pipe(**params).images[0]
 
-
-examples = [
-    "Young man in anime style. The image is of high sharpness and resolution. A handsome, thoughtful man. The man is depicted in the foreground, close-up or middle plan. The background is blurry, not sharp. The play of light and shadow is visible on the face and clothes."
-    "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k.",
-    "An astronaut riding a green horse.",
-    "A delicious ceviche cheesecake slice.",
-    "A futuristic sports car is located on the surface of Mars. Stars, planets, mountains and craters are visible.",
-]
-
-examples_negative = [
-    "blurred details, low resolution, poor image of a man's face, poor quality, artifacts, black and white image"
-    "blurry details, low resolution, poorly defined edges",
-    "bad face, bad quality, artifacts, low-res, black and white",
-]
-
 css = """
 #col-container {
     margin: 0 auto;
@@ -126,55 +109,30 @@ css = """
 }
 """
 
-available_models = [
-    "stable-diffusion-v1-5/stable-diffusion-v1-5",
-    "SG161222/Realistic_Vision_V3.0_VAE",
-    "CompVis/stable-diffusion-v1-4",
-    "stabilityai/sdxl-turbo",
-    "runwayml/stable-diffusion-v1-5",
-    "sd-legacy/stable-diffusion-v1-5",
-    "prompthero/openjourney",
-    "stabilityai/stable-diffusion-3-medium-diffusers",
-    "stabilityai/stable-diffusion-3.5-large",
-    "stabilityai/stable-diffusion-3.5-large-turbo",
-]
-
 with gr.Blocks(css=css) as demo:
-
     with gr.Column(elem_id="col-container"):
-        gr.Markdown(" # Text-to-Image Gradio Template from V. Gorsky")
-
+        gr.Markdown(" # DEMO Text-to-Image")
+        
         with gr.Row():
-            model_id = gr.Dropdown(
-                label="Model Selection",
-                choices=available_models,
-                value="stable-diffusion-v1-5/stable-diffusion-v1-5",
-                interactive=True
+            model_id = gr.Textbox(
+                label="Model ID",
+                max_lines=1,
+                placeholder="Enter model id like 'CompVis/stable-diffusion-v1-4'",
+                value=model_id_default
             )
 
-        prompt = gr.Text(
+        prompt = gr.Textbox(
             label="Prompt",
-            show_label=False,
             max_lines=1,
             placeholder="Enter your prompt",
-            container=False,
         )
-        negative_prompt = gr.Text(
+
+        negative_prompt = gr.Textbox(
             label="Negative prompt",
             max_lines=1,
             placeholder="Enter a negative prompt",
-            visible=True,
         )
 
-        with gr.Row():
-            lora_scale = gr.Slider(
-                label="LoRA scale",
-                minimum=0.0,
-                maximum=1.0,
-                step=0.1,
-                value=0.5,
-            )
-
         with gr.Row():
             seed = gr.Number(
                 label="Seed",
@@ -184,60 +142,67 @@ with gr.Blocks(css=css) as demo:
                 value=42,
             )
 
-        with gr.Row():    
+        with gr.Row():
             guidance_scale = gr.Slider(
                 label="Guidance scale",
                 minimum=0.0,
                 maximum=10.0,
                 step=0.1,
-                value=7.5,  # Replace with defaults that work for your model
+                value=7.0,
+            )
+
+        with gr.Row():
+            lora_scale = gr.Slider(
+                label="LoRA scale",
+                minimum=0.0,
+                maximum=1.0,
+                step=0.1,
+                value=0.5,
             )
 
-        with gr.Row():    
+        with gr.Row():
             num_inference_steps = gr.Slider(
-               label="Number of inference steps",
-               minimum=1,
-               maximum=100,
-               step=1,
-               value=30,  # Replace with defaults that work for your model
+                label="Number of inference steps",
+                minimum=1,
+                maximum=50,
+                step=1,
+                value=20,
             )
 
-        with gr.Accordion("Advanced Settings", open=False):
+        with gr.Accordion("Optional Settings", open=False):
             with gr.Row():
                 width = gr.Slider(
                     label="Width",
                     minimum=256,
                     maximum=MAX_IMAGE_SIZE,
                     step=32,
-                    value=512,  # Replace with defaults that work for your model
+                    value=512,
                 )
-
+            
+            with gr.Row():
                 height = gr.Slider(
                     label="Height",
                     minimum=256,
                     maximum=MAX_IMAGE_SIZE,
                     step=32,
-                    value=512,  # Replace with defaults that work for your model
+                    value=512,
                 )
 
-        gr.Examples(examples=examples, inputs=[prompt])
-        gr.Examples(examples=examples_negative, inputs=[negative_prompt])
-
-        run_button = gr.Button("Run", scale=0, variant="primary")
+        run_button = gr.Button("Run", scale=1, variant="primary")
         result = gr.Image(label="Result", show_label=False)
-
+    
     gr.on(
         triggers=[run_button.click, prompt.submit],
         fn=infer,
         inputs=[
-            model_id,
             prompt,
             negative_prompt,
-            seed,
             width,
             height,
-            guidance_scale,
             num_inference_steps,
+            model_id,
+            seed,
+            guidance_scale,
             lora_scale,
         ],
         outputs=[result],
@@ -245,3 +210,4 @@ with gr.Blocks(css=css) as demo:
 
 if __name__ == "__main__":
     demo.launch()
+