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PixelPhraser

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fsadeek commited on Oct 13, 2024

Commit

430f6e9

1 Parent(s): 8a0ab5b

Changed the HTML and CSS

Browse files

Files changed (2) hide show

app.py +54 -13
index.html +30 -0

app.py CHANGED Viewed

@@ -1,13 +1,11 @@
 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
@@ -20,8 +18,6 @@ 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,
@@ -50,7 +46,6 @@ def infer(
     return image, seed
 examples = [
     "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k",
     "An astronaut riding a green horse",
@@ -61,12 +56,59 @@ css = """
 #col-container {
     margin: 0 auto;
     max-width: 640px;
 }
 """
 with gr.Blocks(css=css) as demo:
     with gr.Column(elem_id="col-container"):
-        gr.Markdown(" # Text-to-Image Gradio Template")
         with gr.Row():
             prompt = gr.Text(
@@ -105,7 +147,7 @@ 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
                 )
                 height = gr.Slider(
@@ -113,7 +155,7 @@ 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
                 )
             with gr.Row():
@@ -122,7 +164,7 @@ with gr.Blocks(css=css) as demo:
                     minimum=0.0,
                     maximum=10.0,
                     step=0.1,
-                    value=0.0,  # Replace with defaults that work for your model
                 )
                 num_inference_steps = gr.Slider(
@@ -130,7 +172,7 @@ with gr.Blocks(css=css) as demo:
                     minimum=1,
                     maximum=50,
                     step=1,
-                    value=2,  # Replace with defaults that work for your model
                 )
         gr.Examples(examples=examples, inputs=[prompt])
@@ -151,5 +193,4 @@ with gr.Blocks(css=css) as demo:
     )
 if __name__ == "__main__":
-    demo.launch()
-## Added a comment

 import gradio as gr
 import numpy as np
 import random
 from diffusers import DiffusionPipeline
 import torch
 device = "cuda" if torch.cuda.is_available() else "cpu"
+model_repo_id = "stabilityai/sdxl-turbo"
 if torch.cuda.is_available():
     torch_dtype = torch.float16
 MAX_SEED = np.iinfo(np.int32).max
 MAX_IMAGE_SIZE = 1024
 def infer(
     prompt,
     negative_prompt,
     return image, seed
 examples = [
     "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k",
     "An astronaut riding a green horse",
 #col-container {
     margin: 0 auto;
     max-width: 640px;
+    background-color: #f9f9f9;
+    border-radius: 10px;
+    padding: 20px;
+    box-shadow: 0 4px 20px rgba(0, 0, 0, 0.1);
+}
+h1 {
+    color: #333;
+    font-family: 'Arial', sans-serif;
+}
+input, .gr-button {
+    border-radius: 5px;
+    border: 1px solid #ccc;
+    padding: 10px;
+    font-size: 14px;
+}
+input:focus, .gr-button:focus {
+    border-color: #007bff;
+    outline: none;
+}
+.gr-button {
+    background-color: #007bff;
+    color: white;
+    transition: background-color 0.3s;
+}
+.gr-button:hover {
+    background-color: #0056b3;
+}
+.accordion-header {
+    background-color: #e9ecef;
+    border-radius: 5px;
+    padding: 10px;
+}
+.accordion-content {
+    background-color: #fff;
+    border: 1px solid #ccc;
+    border-radius: 5px;
+}
+.gr-slider {
+    margin-top: 10px;
 }
 """
 with gr.Blocks(css=css) as demo:
     with gr.Column(elem_id="col-container"):
+        gr.Markdown("<h1>Text-to-Image Gradio Template</h1>")
         with gr.Row():
             prompt = gr.Text(
                     minimum=256,
                     maximum=MAX_IMAGE_SIZE,
                     step=32,
+                    value=1024,
                 )
                 height = gr.Slider(
                     minimum=256,
                     maximum=MAX_IMAGE_SIZE,
                     step=32,
+                    value=1024,
                 )
             with gr.Row():
                     minimum=0.0,
                     maximum=10.0,
                     step=0.1,
+                    value=0.0,
                 )
                 num_inference_steps = gr.Slider(
                     minimum=1,
                     maximum=50,
                     step=1,
+                    value=2,
                 )
         gr.Examples(examples=examples, inputs=[prompt])
     )
 if __name__ == "__main__":
+    demo.launch()

index.html ADDED Viewed

	@@ -0,0 +1,30 @@

+<!DOCTYPE html>
+<html lang="en">
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <meta name="description" content="Embedded content from Pixel Phraser">
+    <title>Embedded Pixel Phraser</title>
+    <style>
+        body {
+            margin: 0;
+            padding: 0;
+            height: 100vh;
+            /* Full height */
+        }
+        iframe {
+            width: 100%;
+            height: 100%;
+            /* Full height */
+            border: none;
+        }
+    </style>
+</head>
+<body>
+    <iframe src="https://fsadeek-pixelphraser.hf.space" title="Pixel Phraser"></iframe>
+</body>
+</html>