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import replicate
import gradio as gr
from io import BytesIO
import base64
import os
illuse = replicate.Client(api_token=os.getenv('REPLICATE'))
model_name = "andreasjansson/illusion:75d51a73fce3c00de31ed9ab4358c73e8fc0f627dc8ce975818e653317cb919b"
example_image = "https://replicate.delivery/pbxt/hHJNV9QteKX8DK2ckkUeXsqbEIKNGFXU1fN0MJoizz3iPlOjA/output-0.png"
def generate(prompt, negative_prompt, qr_content, pattern_image, num_inference_steps, guidance_scale, width, height, seed, num_outputs, controlnet_conditioning_scale, border, qrcode_background):
try:
inputs = {
'prompt': prompt,
'negative_prompt': negative_prompt,
'qr_code_content': qr_content,
'num_inference_steps': num_inference_steps,
'guidance_scale': guidance_scale,
'width': width,
'height': height,
'seed': seed,
'num_outputs': num_outputs,
'controlnet_conditioning_scale': controlnet_conditioning_scale,
'border': border,
'qrcode_background': qrcode_background
}
if pattern_image is not None:
inputs['image'] = open(pattern_image, 'rb')
result = illuse.run(
model_name,
input=inputs
)
return result
except Exception as e:
print(e)
gr.Error(str(e))
return
with gr.Blocks() as demo:
gr.Markdown("""
# Illusion Diffusion Fast demo
## powered by replicate
""")
with gr.Row():
with gr.Column():
prompt = gr.Textbox(label="Prompt")
negative_prompt = gr.Textbox(label="Negative")
with gr.Row():
qr_content = gr.Textbox(label="QR Code Content", placeholder="https://youtube.com/")
pattern_input = gr.Image(label="Pattern Image(if used QR Code Content wont be used)", type="filepath")
with gr.Accordion("Additional Settings", open=False):
with gr.Row():
num_inference_steps = gr.Slider(label="num_inference_steps", minimum=20, maximum=100, step=1, value=50)
guidance_scale = gr.Slider(label="guidance_scale", minimum=0.1, maximum=30, step=0.01, value=7.5)
with gr.Row():
width = gr.Slider(label='width', minimum=128, maximum=1024, step=8, value=768)
height = gr.Slider(label='height', minimum=128, maximum=1024, step=8, value=768)
with gr.Row():
seed = gr.Number(label='seed', value=-1)
num_outputs = gr.Slider(label="num_outputs", minimum=1, maximum=4, step=1)
with gr.Row():
controlnet_conditioning_scale = gr.Slider(label="controlnet_conditioning_scale", minimum=0, maximum=4, step=1, value=1)
border = gr.Slider(label="border", minimum=0, maximum=4, step=1, value=4)
qrcode_background = gr.Dropdown(label="qrcode_background", choices=['gray', 'white'], value='white')
run_btn = gr.Button("Run", variant="primary")
output = gr.Gallery([example_image])
generation_event = run_btn.click(generate, inputs=[prompt, negative_prompt, qr_content, pattern_input,
num_inference_steps, guidance_scale, width, height, seed,
num_outputs, controlnet_conditioning_scale, border,
qrcode_background], outputs=output)
demo.launch(show_api=False)
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