hotdog

app.py

@@ -1,6 +1,7 @@
 import gradio as gr
 from diffusers import AutoPipelineForText2Image
 import torch
+import random
 
 if torch.backends.mps.is_available():
     device = "mps"
@@ -30,27 +31,76 @@ def infer(prompt):
 
     return image
 
+# Lists for random prompt generation
+subjects = [
+    "a cute red panda", "a robot", "a steampunk owl", "a magical crystal", 
+    "a floating island", "a cybernetic dolphin", "a time-traveling historian",
+    "a ghost pianist", "a rainbow dragon", "a space explorer", "a majestic tiger",
+    "a giant mushroom", "a neon cityscape", "a cosmic jellyfish", "a dreamy unicorn",
+    "a celestial mermaid", "a mechanical spider", "a mystical forest", "a futuristic city",
+    "a whimsical fairy", "a mythical phoenix", "a cosmic nebula", "a magical castle",
+    "a cyberpunk samurai", "a time-traveling astronaut", "a crystal cavern",
+]
+
+contexts = [
+    "in an ancient library", "during a neon sunset", "floating in space",
+    "deep underwater", "in a floating market", "on top of a giant mushroom",
+    "inside a clockwork machine", "in a crystal cave", "during a meteor shower",
+    "in a bamboo forest", "in a futuristic cityscape", "on a magical island",
+    "in a cyberpunk alleyway", "in a steampunk workshop",
+    "in a post-apocalyptic wasteland", "in a dreamy cloud kingdom",
+]
+
+styles = [
+    "cyberpunk style", "watercolor painting", "digital art", "oil painting",
+    "studio ghibli style", "synthwave aesthetics", "detailed pencil sketch",
+    "photorealistic", "vaporwave style", "low poly art", "lo-fi aesthetics",
+    "grainy film photography", "comic book style", "minimalist design",
+]
 
-examples = [
-    "A cinematic shot of a baby racoon wearing an intricate kungfu master robe.",
-    "A cartoonish drawing of a tiger with a rainbow mane.",
-    "A realistic painting of a futuristic cityscape with flying cars.",
-    "A watercolor painting of a whimsical fairy in a mystical forest.",
+image_qualities = [
+    "highly detailed", "8K resolution", "dramatic lighting",
+    "professional photography", "cinematic composition", "hyperrealistic",
+    "atmospheric", "stunning", "award-winning", "masterpiece",
+    "low quality", "grainy", "blurry", "abstract", "surreal",
 ]
 
-demo = gr.Interface(
-    fn=infer,
-    inputs=gr.Textbox(
-            label="Prompt",
-            placeholder="Enter your prompt",
-            lines=3,
-        ),
-    outputs=gr.Image(label="Result", type="numpy"),
-    title="Text-to-Image",
-    description="Generate images from text prompts.",
-    theme="compact",
-    examples=examples,
-)
+def generate_not_hot_dog_prompt():
+    subject = random.choice(subjects)
+    context = random.choice(contexts)
+    style = random.choice(styles)
+    quality = random.choice(image_qualities)
+    return f"{subject} {context}, {style}, {quality}"
+
+hot_dog_prompt = "A cinematic shot of a gourmet hotdog in extreme close-up, sitting in a rustic brioche bun, garnished with perfectly drizzled mustard and ketchup. The hotdog glistens under dramatic studio lighting with a slight overhead angle. Shallow depth of field with professional food photography styling. The background is dark and moody with subtle bokeh effects. Shot with a high-end DSLR camera, f/2.8 aperture, warm color grading reminiscent of a Wes Anderson film. Photorealistic quality, 8K resolution."
+
+
+def generate_hot_dog():
+    return infer(hot_dog_prompt)
+
+def generate_not_hot_dog():
+    return infer(generate_not_hot_dog_prompt())
+
+with gr.Blocks(theme="compact") as demo:
+    gr.Markdown("# What Do You Want To Create?")
+    
+    with gr.Row():
+        hot_dog_btn = gr.Button("🌭 Hot Dog", variant="primary")
+        not_hot_dog_btn = gr.Button("❌ Not Hot Dog", variant="primary")
+    
+    output_image = gr.Image(label="Generated Image", type="numpy")
+    
+    hot_dog_btn.click(
+        fn=generate_hot_dog,
+        inputs=[],
+        outputs=output_image
+    )
+    
+    not_hot_dog_btn.click(
+        fn=generate_not_hot_dog,
+        inputs=[],
+        outputs=output_image
+    )
 
 if __name__ == "__main__":
     demo.launch()