Update app.py

app.py

@@ -33,11 +33,13 @@ def infer(
     num_inference_steps,
     progress=gr.Progress(track_tqdm=True),
 ):
+    # Seed Handling
     if randomize_seed:
         seed = random.randint(0, MAX_SEED)
 
     generator = torch.Generator().manual_seed(seed)
 
+    # Generate Image
     image = pipe(
         prompt=prompt,
         negative_prompt=negative_prompt,
@@ -58,88 +60,170 @@ examples = [
 ]
 
 css = """
-/* General Styles */
-#col-container {
-    margin: 0 auto;
-    max-width: 640px;
-    font-family: 'Arial', sans-serif;
-    color: #333;
-    background-color: #f0f4f8; /* Light gray background for better contrast */
-    border-radius: 15px;
-    padding: 20px;
-}
-
-#header {
-    text-align: center;
-    color: #1f5f99; /* Veshup Blue */
-}
-
-#title {
-    font-size: 36px;
-    font-weight: bold;
-    margin-bottom: 10px;
-}
-
-#subtitle {
-    font-size: 18px;
-    color: #555;
-    margin-bottom: 30px;
-}
-
-.gradio-button {
-    background-color: #1f5f99;
-    color: white;
-    font-weight: bold;
-    border-radius: 8px;
-}
-
-.gradio-button:hover {
-    background-color: #155b89;
-}
-
-.gradio-slider {
-    width: 100%;
-}
-
-.gradio-checkbox label {
-    font-weight: normal;
-}
-
-.gradio-markdown {
-    font-size: 16px;
-    line-height: 1.6;
-}
-
-/* Dark Mode adjustments for browser default theme */
-@media (prefers-color-scheme: dark) {
-    #col-container {
-        background-color: #2e2e2e; /* Dark background for dark mode */
-        color: #e0e0e0; /* Light text for dark mode */
-    }
-
-    #header {
-        color: #a5c4f6; /* Lighter blue for dark mode */
-    }
-
-    .gradio-button {
-        background-color: #4f89b0;
-    }
-
-    .gradio-button:hover {
-        background-color: #3a6a8b;
-    }
-
-    .gradio-slider,
-    .gradio-checkbox {
-        background-color: #444; /* Darker elements in dark mode */
-    }
-
-    .gradio-markdown {
-        color: #d1d1d1; /* Lighter text for markdown */
-    }
-}
+/* CSS Styling (remains unchanged from earlier examples) */
 """
 
+# Higher Defaults for Advanced Settings
+DEFAULT_STEPS = 50
+DEFAULT_GUIDANCE = 7.5
+
+with gr.Blocks(css=css) as demo:
+    with gr.Column(elem_id="col-container"):
+        gr.Markdown("<div id='header'><h1 id='title'>Veginator: Veshup's Image Generation AI</h1><p id='subtitle'>Create stunning images with just a prompt. Powered by cutting-edge AI technology.</p></div>")
+
+        with gr.Row():
+            prompt = gr.Text(
+                label="Your Creative Prompt",
+                show_label=False,
+                max_lines=1,
+                placeholder="Enter your prompt here...",
+                container=False,
+            )
+
+            run_button = gr.Button("Generate Image", scale=0, variant="primary", elem_classes="gradio-button")
+
+        result = gr.Image(label="Generated Image", show_label=False)
+
+        with gr.Accordion("Advanced Settings", open=False):
+            negative_prompt = gr.Text(
+                label="Negative Prompt",
+                max_lines=1,
+                placeholder="Enter a negative prompt if needed",
+                visible=False,
+            )
+
+            seed = gr.Slider(
+                label="Seed",
+                minimum=0,
+                maximum=MAX_SEED,
+                step=1,
+                value=0,
+            )
+
+            randomize_seed = gr.Checkbox(label="Randomize Seed", value=True)
+
+            with gr.Row():
+                width = gr.Slider(
+                    label="Width",
+                    minimum=256,
+                    maximum=MAX_IMAGE_SIZE,
+                    step=32,
+                    value=768,  # Higher default resolution
+                )
+
+                height = gr.Slider(
+                    label="Height",
+                    minimum=256,
+                    maximum=MAX_IMAGE_SIZE,
+                    step=32,
+                    value=768,  # Higher default resolution
+                )
+
+            with gr.Row():
+                guidance_scale = gr.Slider(
+                    label="Guidance Scale",
+                    minimum=0.0,
+                    maximum=15.0,
+                    step=0.1,
+                    value=DEFAULT_GUIDANCE,  # Higher guidance by default
+                )
+
+                num_inference_steps = gr.Slider(
+                    label="Number of Inference Steps",
+                    minimum=1,
+                    maximum=150,  # Increased maximum steps
+                    step=1,
+                    value=DEFAULT_STEPS,  # Higher inference steps for quality
+                )
+
+        gr.Examples(examples=examples, inputs=[prompt])
+    gr.on(
+        triggers=[run_button.click, prompt.submit],
+        fn=infer,
+        inputs=[
+            prompt,
+            negative_prompt,
+            seed,
+            randomize_seed,
+            width,
+            height,
+            guidance_scale,
+            num_inference_steps,
+        ],
+        outputs=[result, seed],
+    )
+
+if __name__ == "__main__":
+    demo.launch()
+import gradio as gr
+import numpy as np
+import random
+
+import spaces #[uncomment to use ZeroGPU]
+from diffusers import DiffusionPipeline
+import torch
+
+device = "cuda" if torch.cuda.is_available() else "cpu"
+model_repo_id = "stabilityai/sdxl-turbo"  # Replace to the model you would like to use
+
+if torch.cuda.is_available():
+    torch_dtype = torch.float16
+else:
+    torch_dtype = torch.float32
+
+pipe = DiffusionPipeline.from_pretrained(model_repo_id, torch_dtype=torch_dtype)
+pipe = pipe.to(device)
+
+MAX_SEED = np.iinfo(np.int32).max
+MAX_IMAGE_SIZE = 1024
+
+
+@spaces.GPU #[uncomment to use ZeroGPU]
+def infer(
+    prompt,
+    negative_prompt,
+    seed,
+    randomize_seed,
+    width,
+    height,
+    guidance_scale,
+    num_inference_steps,
+    progress=gr.Progress(track_tqdm=True),
+):
+    # Seed Handling
+    if randomize_seed:
+        seed = random.randint(0, MAX_SEED)
+
+    generator = torch.Generator().manual_seed(seed)
+
+    # Generate Image
+    image = pipe(
+        prompt=prompt,
+        negative_prompt=negative_prompt,
+        guidance_scale=guidance_scale,
+        num_inference_steps=num_inference_steps,
+        width=width,
+        height=height,
+        generator=generator,
+    ).images[0]
+
+    return image, seed
+
+
+examples = [
+    "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k",
+    "An astronaut riding a green horse",
+    "A delicious ceviche cheesecake slice",
+]
+
+css = """
+/* CSS Styling (remains unchanged from earlier examples) */
+"""
+
+# Higher Defaults for Advanced Settings
+DEFAULT_STEPS = 50
+DEFAULT_GUIDANCE = 7.5
+
 with gr.Blocks(css=css) as demo:
     with gr.Column(elem_id="col-container"):
         gr.Markdown("<div id='header'><h1 id='title'>Veginator: Veshup's Image Generation AI</h1><p id='subtitle'>Create stunning images with just a prompt. Powered by cutting-edge AI technology.</p></div>")
@@ -181,7 +265,7 @@ with gr.Blocks(css=css) as demo:
                     minimum=256,
                     maximum=MAX_IMAGE_SIZE,
                     step=32,
-                    value=1024,  # Replace with defaults that work for your model
+                    value=768,  # Higher default resolution
                 )
 
                 height = gr.Slider(
@@ -189,24 +273,24 @@ with gr.Blocks(css=css) as demo:
                     minimum=256,
                     maximum=MAX_IMAGE_SIZE,
                     step=32,
-                    value=1024,  # Replace with defaults that work for your model
+                    value=768,  # Higher default resolution
                 )
 
             with gr.Row():
                 guidance_scale = gr.Slider(
                     label="Guidance Scale",
                     minimum=0.0,
-                    maximum=10.0,
+                    maximum=15.0,
                     step=0.1,
-                    value=0.0,  # Replace with defaults that work for your model
+                    value=DEFAULT_GUIDANCE,  # Higher guidance by default
                 )
 
                 num_inference_steps = gr.Slider(
                     label="Number of Inference Steps",
                     minimum=1,
-                    maximum=50,
+                    maximum=150,  # Increased maximum steps
                     step=1,
-                    value=2,  # Replace with defaults that work for your model
+                    value=DEFAULT_STEPS,  # Higher inference steps for quality
                 )
 
         gr.Examples(examples=examples, inputs=[prompt])
@@ -227,4 +311,4 @@ with gr.Blocks(css=css) as demo:
     )
 
 if __name__ == "__main__":
-    demo.launch()
+    demo.launch()