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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) | |