import gradio as gr
from PIL import Image
# Text to Image function with thinking option and hyperparameters
def text_to_image(prompt, show_thinking=False, cfg_text_scale=4.0, cfg_interval=0.4,
timestep_shift=3.0, num_timesteps=50,
cfg_renorm_min=1.0, cfg_renorm_type="global",
max_think_token_n=1024, do_sample=False, text_temperature=0.3,
seed=0, image_ratio="1:1"):
yield None, None
# Image Understanding function with thinking option and hyperparameters
def image_understanding(image: Image.Image, prompt: str, show_thinking=False,
do_sample=False, text_temperature=0.3, max_new_tokens=512):
yield None
# Image Editing function with thinking option and hyperparameters
def edit_image(image: Image.Image, prompt: str, show_thinking=False, cfg_text_scale=4.0,
cfg_img_scale=2.0, cfg_interval=0.0,
timestep_shift=3.0, num_timesteps=50, cfg_renorm_min=1.0,
cfg_renorm_type="text_channel", max_think_token_n=1024,
do_sample=False, text_temperature=0.3, seed=0):
yield (image, image), None
# Helper function to load example images
def load_example_image(image_path):
try:
return Image.open(image_path)
except Exception as e:
print(f"Error loading example image: {e}")
return None
# Gradio UI
with gr.Blocks() as demo:
gr.Markdown("""
""")
with gr.Tab("📝 Text to Image"):
txt_input = gr.Textbox(
label="Prompt",
value="A female cosplayer portraying an ethereal fairy or elf, wearing a flowing dress made of delicate fabrics in soft, mystical colors like emerald green and silver. She has pointed ears, a gentle, enchanting expression, and her outfit is adorned with sparkling jewels and intricate patterns. The background is a magical forest with glowing plants, mystical creatures, and a serene atmosphere."
)
with gr.Row():
show_thinking = gr.Checkbox(label="Thinking", value=False)
# Add hyperparameter controls in an accordion
with gr.Accordion("Inference Hyperparameters", open=False):
# 参数一排两个布局
with gr.Group():
with gr.Row():
seed = gr.Slider(minimum=0, maximum=1000000, value=0, step=1,
label="Seed", info="0 for random seed, positive for reproducible results")
image_ratio = gr.Dropdown(choices=["1:1", "4:3", "3:4", "16:9", "9:16"],
value="1:1", label="Image Ratio",
info="The longer size is fixed to 1024")
with gr.Row():
cfg_text_scale = gr.Slider(minimum=1.0, maximum=8.0, value=4.0, step=0.1, interactive=True,
label="CFG Text Scale", info="Controls how strongly the model follows the text prompt (4.0-8.0)")
cfg_interval = gr.Slider(minimum=0.0, maximum=1.0, value=0.4, step=0.1,
label="CFG Interval", info="Start of CFG application interval (end is fixed at 1.0)")
with gr.Row():
cfg_renorm_type = gr.Dropdown(choices=["global", "local", "text_channel"],
value="global", label="CFG Renorm Type",
info="If the genrated image is blurry, use 'global'")
cfg_renorm_min = gr.Slider(minimum=0.0, maximum=1.0, value=0.0, step=0.1, interactive=True,
label="CFG Renorm Min", info="1.0 disables CFG-Renorm")
with gr.Row():
num_timesteps = gr.Slider(minimum=10, maximum=100, value=50, step=5, interactive=True,
label="Timesteps", info="Total denoising steps")
timestep_shift = gr.Slider(minimum=1.0, maximum=5.0, value=3.0, step=0.5, interactive=True,
label="Timestep Shift", info="Higher values for layout, lower for details")
# Thinking parameters in a single row
thinking_params = gr.Group(visible=False)
with thinking_params:
with gr.Row():
do_sample = gr.Checkbox(label="Sampling", value=False, info="Enable sampling for text generation")
max_think_token_n = gr.Slider(minimum=64, maximum=4006, value=1024, step=64, interactive=True,
label="Max Think Tokens", info="Maximum number of tokens for thinking")
text_temperature = gr.Slider(minimum=0.1, maximum=1.0, value=0.3, step=0.1, interactive=True,
label="Temperature", info="Controls randomness in text generation")
thinking_output = gr.Textbox(label="Thinking Process", visible=False)
img_output = gr.Image(label="Generated Image")
gen_btn = gr.Button("Generate", variant="primary")
# Dynamically show/hide thinking process box and parameters
def update_thinking_visibility(show):
return gr.update(visible=show), gr.update(visible=show)
show_thinking.change(
fn=update_thinking_visibility,
inputs=[show_thinking],
outputs=[thinking_output, thinking_params]
)
gr.on(
triggers=[gen_btn.click, txt_input.submit],
fn=text_to_image,
inputs=[
txt_input, show_thinking, cfg_text_scale,
cfg_interval, timestep_shift,
num_timesteps, cfg_renorm_min, cfg_renorm_type,
max_think_token_n, do_sample, text_temperature, seed, image_ratio
],
outputs=[img_output, thinking_output]
)
with gr.Tab("🖌️ Image Edit"):
with gr.Row():
with gr.Column(scale=1):
edit_image_input = gr.Image(label="Input Image", value=load_example_image('test_images/women.jpg'))
edit_prompt = gr.Textbox(
label="Prompt",
value="She boards a modern subway, quietly reading a folded newspaper, wearing the same clothes."
)
with gr.Column(scale=1):
edit_image_output = gr.ImageSlider(label="Result")
edit_thinking_output = gr.Textbox(label="Thinking Process", visible=False)
with gr.Row():
edit_show_thinking = gr.Checkbox(label="Thinking", value=False)
# Add hyperparameter controls in an accordion
with gr.Accordion("Inference Hyperparameters", open=False):
with gr.Group():
with gr.Row():
edit_seed = gr.Slider(minimum=0, maximum=1000000, value=0, step=1, interactive=True,
label="Seed", info="0 for random seed, positive for reproducible results")
edit_cfg_text_scale = gr.Slider(minimum=1.0, maximum=8.0, value=4.0, step=0.1, interactive=True,
label="CFG Text Scale", info="Controls how strongly the model follows the text prompt")
with gr.Row():
edit_cfg_img_scale = gr.Slider(minimum=1.0, maximum=4.0, value=2.0, step=0.1, interactive=True,
label="CFG Image Scale", info="Controls how much the model preserves input image details")
edit_cfg_interval = gr.Slider(minimum=0.0, maximum=1.0, value=0.0, step=0.1, interactive=True,
label="CFG Interval", info="Start of CFG application interval (end is fixed at 1.0)")
with gr.Row():
edit_cfg_renorm_type = gr.Dropdown(choices=["global", "local", "text_channel"],
value="text_channel", label="CFG Renorm Type",
info="If the genrated image is blurry, use 'global")
edit_cfg_renorm_min = gr.Slider(minimum=0.0, maximum=1.0, value=0.0, step=0.1, interactive=True,
label="CFG Renorm Min", info="1.0 disables CFG-Renorm")
with gr.Row():
edit_num_timesteps = gr.Slider(minimum=10, maximum=100, value=50, step=5, interactive=True,
label="Timesteps", info="Total denoising steps")
edit_timestep_shift = gr.Slider(minimum=1.0, maximum=10.0, value=3.0, step=0.5, interactive=True,
label="Timestep Shift", info="Higher values for layout, lower for details")
# Thinking parameters in a single row
edit_thinking_params = gr.Group(visible=False)
with edit_thinking_params:
with gr.Row():
edit_do_sample = gr.Checkbox(label="Sampling", value=False, info="Enable sampling for text generation")
edit_max_think_token_n = gr.Slider(minimum=64, maximum=4006, value=1024, step=64, interactive=True,
label="Max Think Tokens", info="Maximum number of tokens for thinking")
edit_text_temperature = gr.Slider(minimum=0.1, maximum=1.0, value=0.3, step=0.1, interactive=True,
label="Temperature", info="Controls randomness in text generation")
edit_btn = gr.Button("Submit", variant="primary")
# Dynamically show/hide thinking process box for editing
def update_edit_thinking_visibility(show):
return gr.update(visible=show), gr.update(visible=show)
edit_show_thinking.change(
fn=update_edit_thinking_visibility,
inputs=[edit_show_thinking],
outputs=[edit_thinking_output, edit_thinking_params]
)
gr.on(
triggers=[edit_btn.click, edit_prompt.submit],
fn=edit_image,
inputs=[
edit_image_input, edit_prompt, edit_show_thinking,
edit_cfg_text_scale, edit_cfg_img_scale, edit_cfg_interval,
edit_timestep_shift, edit_num_timesteps,
edit_cfg_renorm_min, edit_cfg_renorm_type,
edit_max_think_token_n, edit_do_sample, edit_text_temperature, edit_seed
],
outputs=[edit_image_output, edit_thinking_output]
)
with gr.Tab("🖼️ Image Understanding"):
with gr.Row():
with gr.Column(scale=1):
img_input = gr.Image(label="Input Image", value=load_example_image('test_images/meme.jpg'))
understand_prompt = gr.Textbox(
label="Prompt",
value="Can someone explain what's funny about this meme??"
)
with gr.Column(scale=1):
txt_output = gr.Textbox(label="Result", lines=20)
with gr.Row():
understand_show_thinking = gr.Checkbox(label="Thinking", value=False)
# Add hyperparameter controls in an accordion
with gr.Accordion("Inference Hyperparameters", open=False):
with gr.Row():
understand_do_sample = gr.Checkbox(label="Sampling", value=False, info="Enable sampling for text generation")
understand_text_temperature = gr.Slider(minimum=0.0, maximum=1.0, value=0.3, step=0.05, interactive=True,
label="Temperature", info="Controls randomness in text generation (0=deterministic, 1=creative)")
understand_max_new_tokens = gr.Slider(minimum=64, maximum=4096, value=512, step=64, interactive=True,
label="Max New Tokens", info="Maximum length of generated text, including potential thinking")
img_understand_btn = gr.Button("Submit", variant="primary")
gr.on(
triggers=[img_understand_btn.click, understand_prompt.submit],
fn=image_understanding,
inputs=[
img_input, understand_prompt, understand_show_thinking,
understand_do_sample, understand_text_temperature, understand_max_new_tokens
],
outputs=txt_output
)
gr.Markdown("""
""")
demo.launch()
