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Byte Dream - Gradio Web Interface
Interactive web UI for image generation
"""
import gradio as gr
from bytedream.generator import ByteDreamGenerator
import torch
import os
# Initialize generator
print("Loading Byte Dream model...")
# Check if we should load from Hugging Face
HF_REPO_ID = os.getenv("HF_REPO_ID", None)
MODEL_PATH = os.getenv("MODEL_PATH", "./models/bytedream")
try:
if HF_REPO_ID:
print(f"Loading model from Hugging Face: {HF_REPO_ID}...")
generator = ByteDreamGenerator(
hf_repo_id=HF_REPO_ID,
config_path="config.yaml",
device="cpu",
)
else:
print(f"Loading model from local path: {MODEL_PATH}...")
generator = ByteDreamGenerator(
model_path=MODEL_PATH,
config_path="config.yaml",
device="cpu",
)
print("β Model loaded successfully!")
except Exception as e:
print(f"β Warning: Could not load model: {e}")
print(" Please train the model first using: python train.py")
print(" Or download pretrained weights from Hugging Face.")
print("")
print(" To use a model from Hugging Face, set environment variable:")
print(" HF_REPO_ID=username/repo_name")
print("")
print("Starting in demo mode...")
generator = None
def generate_image(
prompt,
negative_prompt,
width,
height,
num_steps,
guidance_scale,
seed,
):
"""Generate image from prompt"""
if generator is None:
return None, "Error: Model not loaded. Please train or download model weights."
# Convert seed to None if -1
seed_value = None if seed == -1 else seed
try:
# Generate image
image = generator.generate(
prompt=prompt,
negative_prompt=negative_prompt if negative_prompt else None,
width=int(width),
height=int(height),
num_inference_steps=int(num_steps),
guidance_scale=float(guidance_scale),
seed=seed_value,
)
return image, "Success! β"
except Exception as e:
print(f"Error generating image: {e}")
import traceback
traceback.print_exc()
return None, f"Error: {str(e)}"
# Create Gradio interface
with gr.Blocks(
title="Byte Dream - AI Image Generator",
css="""
.gradio-container {
max-width: 1400px !important;
}
#main-heading {
text-align: center;
margin-bottom: 20px;
}
.description {
text-align: center;
margin-bottom: 30px;
}
"""
) as demo:
gr.Markdown("""
# π¨ Byte Dream - AI Image Generator
### Transform your imagination into reality with advanced AI
Powered by state-of-the-art latent diffusion models, optimized for CPU inference.
""")
with gr.Row():
with gr.Column(scale=1):
gr.Markdown("### π Create Your Prompt")
prompt_input = gr.Textbox(
label="Positive Prompt",
placeholder="Describe the image you want to create...",
lines=3,
value="A beautiful sunset over mountains, digital art, highly detailed, vibrant colors",
)
negative_prompt_input = gr.Textbox(
label="Negative Prompt (Optional)",
placeholder="What to avoid in the image...",
lines=2,
value="ugly, blurry, low quality, distorted, deformed",
)
gr.Markdown("### βοΈ Settings")
with gr.Row():
width_slider = gr.Slider(
minimum=256,
maximum=1024,
step=64,
value=512,
label="Width (px)",
info="Image width - multiples of 64"
)
height_slider = gr.Slider(
minimum=256,
maximum=1024,
step=64,
value=512,
label="Height (px)",
info="Image height - multiples of 64"
)
with gr.Row():
steps_slider = gr.Slider(
minimum=10,
maximum=150,
step=5,
value=50,
label="Inference Steps",
info="More steps = better quality but slower"
)
guidance_slider = gr.Slider(
minimum=1.0,
maximum=20.0,
step=0.5,
value=7.5,
label="Guidance Scale",
info="Higher = closer to prompt, Lower = more creative"
)
seed_input = gr.Number(
label="Seed",
value=-1,
precision=0,
info="-1 for random, any number for reproducibility",
)
generate_btn = gr.Button(
"π¨ Generate Image",
variant="primary",
size="lg",
)
with gr.Column(scale=1):
gr.Markdown("### πΌοΈ Result")
output_image = gr.Image(
label="Generated Image",
type="pil",
height=512,
)
status_text = gr.Textbox(
label="Status",
interactive=False,
)
download_btn = gr.File(
label="Download",
visible=True,
)
# Tips section
with gr.Accordion("π‘ Tips for Better Results", open=False):
gr.Markdown("""
**Writing Effective Prompts:**
- Be specific and descriptive
- Include art style references (e.g., "digital art", "oil painting", "watercolor")
- Mention lighting ("dramatic lighting", "soft sunlight", "neon lights")
- Add quality modifiers ("highly detailed", "4K", "masterpiece")
- Specify mood and atmosphere ("peaceful", "dramatic", "mysterious")
**Using Negative Prompts:**
- Remove unwanted elements ("no people", "no text")
- Avoid quality issues ("no blur", "no distortion")
- Fix common problems ("bad anatomy", "extra limbs")
**Parameter Guide:**
- **Steps**: 20-30 for quick previews, 50-75 for final images, 100+ for best quality
- **Guidance**: 5-7 for creative freedom, 7-9 for balanced, 9-12 for strict prompt following
- **Resolution**: Higher = more detail but slower. Start with 512x512, increase if needed
""")
# Examples section
gr.Markdown("### π‘ Example Prompts")
with gr.Row():
example_btn1 = gr.Button(
"π Cyberpunk City",
size="sm",
elem_id="example_btn1",
)
example_btn2 = gr.Button(
"π Fantasy Dragon",
size="sm",
elem_id="example_btn2",
)
example_btn3 = gr.Button(
"ποΈ Peaceful Landscape",
size="sm",
elem_id="example_btn3",
)
with gr.Row():
example_btn4 = gr.Button(
"π€ Character Portrait",
size="sm",
elem_id="example_btn4",
)
example_btn5 = gr.Button(
"π Underwater Scene",
size="sm",
elem_id="example_btn5",
)
example_btn6 = gr.Button(
"π¨ Abstract Art",
size="sm",
elem_id="example_btn6",
)
# Example prompt values
example_prompts = {
"example_btn1": (
"A cyberpunk city at night with neon lights, futuristic architecture, flying cars, rain-slicked streets, highly detailed, digital art, cinematic lighting",
"ugly, blurry, low quality, distorted, dark, gloomy"
),
"example_btn2": (
"A majestic dragon breathing fire, fantasy art, dramatic lighting, epic scene, scales gleaming, powerful wings, mountain landscape background",
"ugly, deformed, blurry, low quality, cartoonish"
),
"example_btn3": (
"A peaceful cottage in a meadow, wildflowers, sunny day, blue sky, studio ghibli style, serene atmosphere, pastoral landscape",
"people, animals, buildings, urban, dark, stormy"
),
"example_btn4": (
"Portrait of a warrior princess, ornate armor, fantasy setting, intricate details, character design, dramatic lighting, confident expression, long flowing hair",
"ugly, deformed, asymmetrical, blurry, low quality, bad anatomy"
),
"example_btn5": (
"Underwater coral reef, tropical fish, sunlight filtering through water, photorealistic, vibrant colors, marine life, crystal clear water",
"polluted, murky, dark, blurry, low quality"
),
"example_btn6": (
"Abstract geometric art, colorful shapes, dynamic composition, modern art, bold patterns, artistic expression, vivid colors",
"representational, realistic, boring, dull colors, simple"
),
}
# Connect example buttons
def set_example(prompt, negative):
return prompt, negative, "Click Generate to create!"
# Map button names to their variables
button_map = {
"example_btn1": example_btn1,
"example_btn2": example_btn2,
"example_btn3": example_btn3,
"example_btn4": example_btn4,
"example_btn5": example_btn5,
"example_btn6": example_btn6,
}
for btn_name, (prompt, negative) in example_prompts.items():
button_map[btn_name].click(
fn=set_example,
inputs=[gr.State(prompt), gr.State(negative)],
outputs=[prompt_input, negative_prompt_input, status_text],
)
# Connect generate button
generate_btn.click(
fn=generate_image,
inputs=[
prompt_input,
negative_prompt_input,
width_slider,
height_slider,
steps_slider,
guidance_slider,
seed_input,
],
outputs=[output_image, status_text],
)
# Footer
gr.Markdown("""
---
**Byte Dream** v1.0.0 | Powered by Latent Diffusion Models | Optimized for CPU Inference
Created with β€οΈ using PyTorch and Hugging Face Diffusers
""")
if __name__ == "__main__":
print("\n" + "="*60)
print("Starting Byte Dream Web Interface")
print("="*60)
print("\nOpening browser...")
print("Press Ctrl+C to close\n")
demo.launch(
server_name="0.0.0.0",
server_port=7860,
share=False,
show_error=True,
theme=gr.themes.Soft(),
)
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