import gradio as gr from stablepy import Model_Diffusers # Define the function to generate images def generate_image(prompt, num_steps, guidance_scale, sampler, img_width, img_height, upscaler_model_path, upscaler_increases_size, hires_steps, base_model_id): model = Model_Diffusers( base_model_id=base_model_id, task_name='txt2img', ) image, info_image = model( prompt=prompt, num_steps=num_steps, guidance_scale=guidance_scale, sampler=sampler, img_width=img_width, img_height=img_height, upscaler_model_path=upscaler_model_path, upscaler_increases_size=upscaler_increases_size, hires_steps=hires_steps, ) return image[0] # Create the Gradio Blocks UI with gr.Blocks(gr.themes.Ocean(), title="StablePY") as demo: gr.Markdown("# StablePY") moelpah = gr.Textbox(label="model", placeholder="user/repo") with gr.Row(): prompt = gr.Textbox(label="Prompt", value="highly detailed portrait of an underwater city, with towering spires and domes rising up from the ocean floor") with gr.Row(): num_steps = gr.Slider(label="Number of Steps", minimum=1, maximum=100, value=30) guidance_scale = gr.Slider(label="Guidance Scale", minimum=1.0, maximum=20.0, value=7.5) sampler = gr.Dropdown(label="Sampler", choices=["DPM++ 2M", "DDIM", "Euler A"], value="DPM++ 2M") with gr.Row(): img_width = gr.Number(label="Image Width", value=1024) img_height = gr.Number(label="Image Height", value=1024) with gr.Row(): upscaler_model_path = gr.Textbox(label="Upscaler Model Path", value="./upscaler/RealESRGAN_x4plus_anime_6B.pth", visible=False) upscaler_increases_size = gr.Number(label="Upscaler Increase Size", value=1.5) hires_steps = gr.Number(label="Hires Steps", value=25) with gr.Row(): generate_button = gr.Button("Generate") with gr.Row(): output_image = gr.Image(label="Generated Image") # Link the button to the generation function generate_button.click( generate_image, inputs=[moelpah, prompt, num_steps, guidance_scale, sampler, img_width, img_height, upscaler_model_path, upscaler_increases_size, hires_steps], outputs=[output_image] ) # Launch the app demo.launch()