final draft - December 13

app.py

@@ -9,12 +9,11 @@ import torch
 from diffusers import StableDiffusionXLPipeline, EulerAncestralDiscreteScheduler
 from typing import Tuple
 
-# Function to apply the style
 def apply_style(style_name: str, positive: str, negative: str = "") -> Tuple[str, str]:
     styles = {
         "3840 x 2160": (
-            "hyper-realistic 8K image of {prompt}. ultra-detailed, lifelike, high-resolution, sharp, vibrant colors, photorealistic",
-            "",
+            "hyper-realistic image of {prompt}. lifelike, authentic, natural colors, true-to-life details, realistic lighting, immersive, highly detailed",
+            "unrealistic, low resolution, artificial, over-saturated, distorted, fake",
         ),
         "Style Zero": ("{prompt}", ""),
     }
@@ -23,7 +22,6 @@ def apply_style(style_name: str, positive: str, negative: str = "") -> Tuple[str
     p, n = styles.get(style_name, styles[DEFAULT_STYLE_NAME])
     return p.replace("{prompt}", positive), n + negative
 
-# Load and prepare the model
 def load_and_prepare_model():
     model_id = "SG161222/RealVisXL_V5.0_Lightning"
     pipe = StableDiffusionXLPipeline.from_pretrained(
@@ -37,30 +35,16 @@ def load_and_prepare_model():
 
 model = load_and_prepare_model()
 
-# Helper function for randomizing seed
 def randomize_seed_fn(seed: int, randomize_seed: bool) -> int:
     if randomize_seed:
         seed = random.randint(0, np.iinfo(np.int32).max)
     return seed
 
-# Helper function to save the image
 def save_image(img):
     unique_name = str(uuid.uuid4()) + ".png"
     img.save(unique_name)
     return unique_name
 
-# Function to save the thumbnail
-def save_thumbnail(img):
-    # Ensure the thumbnails directory exists
-    os.makedirs('/tmp/thumbnails', exist_ok=True)
-    thumbnail_path = "/tmp/thumbnails/" + str(uuid.uuid4()) + "_thumb.png"
-    
-    # Resize the image to a smaller size (150x150 px)
-    img.thumbnail((100, 100))  # Resize the thumbnail
-    img.save(thumbnail_path)
-    return thumbnail_path
-
-# Generate the image
 @spaces.GPU(duration=60, enable_queue=True)
 def generate(
         prompt: str,
@@ -93,7 +77,6 @@ def generate(
     image_path = save_image(images[0])  # Saving the first generated image
     return image_path
 
-# Gradio app with layout and History section
 with gr.Blocks(theme="soft") as demo:
     # Block for "SNAPSCRIBE" centered at the top
     with gr.Row():
@@ -101,7 +84,6 @@ with gr.Blocks(theme="soft") as demo:
             gr.Markdown("<h1 style='text-align:center; color:white; font-weight:bold; text-decoration:underline;'>SNAPSCRIBE</h1>")
             gr.Markdown("<h2 style='text-align:center; color:white; font-weight:bold; text-decoration:underline;'>Developed using RealVisXL_V5.0_Lightning model with ❤ by Aklavya</h2>")
     
-    # Input prompt and generate button
     with gr.Row():
         with gr.Column(scale=3):
             prompt = gr.Textbox(
@@ -111,48 +93,36 @@ with gr.Blocks(theme="soft") as demo:
             )
             run_button = gr.Button("Generate Image")
 
+            # Example prompts box
+            example_prompts_text = (
+                "Dew-covered spider web in morning sunlight, with blurred greenery\n"
+                "--------------------------------------------\n"
+                "Glass of cold water with ice cubes and condensation on a wooden table\n"
+                "--------------------------------------------\n"
+                "Coffee cup with latte art, steam rising, and morning sunlight\n"
+                "--------------------------------------------\n"
+                "Autumn forest with golden leaves, sunlight through trees, and a breeze"
+            )
+
+            example_prompts = gr.Textbox(
+                value=example_prompts_text,
+                lines=5,
+                label="Sample Inputs",
+                interactive=False,
+            )
+
         with gr.Column(scale=7):
             result_image = gr.Image(
                 label="Generated Image",
                 type="filepath",
                 elem_id="output_image",
-                height=650  # Height for the generated image
+                height=650  # Increased the height by 100%
             )
 
-    # Create a section for history below the output image section
-    with gr.Row():
-        with gr.Column(scale=7):
-            gr.Markdown("<h3 style='text-align:center; color:white; font-weight:bold;'>History</h3>")
-            history_images_output = gr.Gallery(
-                label="History",
-                elem_id="history_images",
-                columns=5,  # Number of columns for thumbnails
-                show_label=False,  # Hide the label
-                height=100  # Set the height for smaller thumbnails
-            )
-
-    # Function to handle image generation and saving history
-    history_images = []  # List to store the paths of generated images
-
-    def handle_generate_and_history(prompt):
-        # Generate image
-        image_path = generate(prompt)
-        
-        # Load the image and create a mini thumbnail
-        img = Image.open(image_path)
-        thumbnail_path = save_thumbnail(img)
-
-        # Add the new thumbnail path at the beginning of the history list
-        history_images.insert(0, thumbnail_path)  # Prepend the new thumbnail
-        
-        # Return the generated image and updated history
-        return image_path, history_images
-
-    # Run the generate button click action
     run_button.click(
-        fn=handle_generate_and_history,
+        fn=generate,
         inputs=[prompt],
-        outputs=[result_image, history_images_output],
+        outputs=[result_image],
     )
 
 demo.launch()