""" Original code by Zenafey @zenafey """ import gradio as gr from engine import generate_sd, generate_sdxl, transform_sd, controlnet_sd, image_upscale, get_models from const import CMODELS, CMODULES, SAMPLER_LIST, SDXL_MODEL_LIST with gr.Blocks() as demo: gr.Markdown("""

Prodia Studio

powered by Prodia Stable Diffusion API

""") with gr.Tab("/sdxl/generate [BETA]"): with gr.Row(): with gr.Column(scale=6, min_width=600): prompt = gr.Textbox("puppies in a cloud, 4k", placeholder="Prompt", show_label=False, lines=3) negative_prompt = gr.Textbox(placeholder="Negative Prompt", show_label=False, lines=3) with gr.Row(): with gr.Column(): sampler = gr.Dropdown(value="Euler a", show_label=True, label="Sampling Method", choices=SAMPLER_LIST) model = gr.Dropdown( interactive=True, value="sd_xl_base_1.0.safetensors [be9edd61]", show_label=True, label="Stable Diffusion XL Checkpoint", choices=SDXL_MODEL_LIST ) seed = gr.Number(label="Seed", value=-1) with gr.Column(): steps = gr.Slider(label="Sampling Steps", minimum=1, maximum=50, value=25, step=1) cfg_scale = gr.Slider(label="CFG Scale", minimum=1, maximum=20, value=7, step=1) text_button = gr.Button("Generate", variant='primary') with gr.Column(scale=7): image_output = gr.Image() text_button.click(generate_sdxl, inputs=[prompt, negative_prompt, model, steps, sampler, cfg_scale, seed], outputs=image_output) with gr.Tab("/sd/generate"): with gr.Row(): with gr.Column(scale=6, min_width=600): prompt = gr.Textbox("puppies in a cloud, 4k", placeholder="Prompt", show_label=False, lines=3) negative_prompt = gr.Textbox(placeholder="Negative Prompt", show_label=False, lines=3) with gr.Row(): with gr.Column(): sampler = gr.Dropdown(value="Euler a", show_label=True, label="Sampling Method", choices=SAMPLER_LIST) model = gr.Dropdown( interactive=True, value=get_models()[1], show_label=True, label="Stable Diffusion Checkpoint", choices=get_models() ) upscale = gr.Checkbox(label="Upscale", value=True) seed = gr.Number(label="Seed", value=-1) with gr.Column(): width = gr.Slider(label="Width", maximum=1024, value=512, step=8) height = gr.Slider(label="Height", maximum=1024, value=512, step=8) steps = gr.Slider(label="Sampling Steps", minimum=1, maximum=50, value=25, step=1) cfg_scale = gr.Slider(label="CFG Scale", minimum=1, maximum=20, value=7, step=1) text_button = gr.Button("Generate", variant='primary') with gr.Column(scale=7): image_output = gr.Image() text_button.click(generate_sd, inputs=[prompt, negative_prompt, model, steps, sampler, cfg_scale, width, height, seed, upscale], outputs=image_output) with gr.Tab("/sd/transform"): with gr.Row(): with gr.Row(): with gr.Column(scale=6, min_width=600): with gr.Row(): with gr.Column(): image_input = gr.Image(type='filepath') with gr.Column(): prompt = gr.Textbox("puppies in a cloud, 4k", label='Prompt', placeholder="Prompt", lines=3) negative_prompt = gr.Textbox(placeholder="badly drawn", label='Negative Prompt', lines=3) with gr.Row(): with gr.Column(): sampler = gr.Dropdown(value="Euler a", show_label=True, label="Sampling Method", choices=SAMPLER_LIST) model = gr.Dropdown( interactive=True, value=get_models()[1], show_label=True, label="Stable Diffusion Checkpoint", choices=get_models() ) upscale = gr.Checkbox(label="Upscale", value=True) seed = gr.Number(label="Seed", value=-1) with gr.Column(): steps = gr.Slider(label="Sampling Steps", minimum=1, maximum=30, value=25, step=1) cfg_scale = gr.Slider(label="CFG Scale", minimum=1, maximum=20, value=7, step=1) denoising_strength = gr.Slider(label="Denoising Strength", minimum=0.1, maximum=1.0, value=0.7, step=0.1) text_button = gr.Button("Generate", variant='primary') with gr.Column(scale=7): image_output = gr.Image() text_button.click(transform_sd, inputs=[image_input, model, prompt, denoising_strength, negative_prompt, steps, cfg_scale, seed, upscale, sampler ], outputs=image_output) with gr.Tab("/sd/controlnet"): with gr.Row(): with gr.Row(): with gr.Column(scale=6, min_width=600): with gr.Row(): with gr.Column(): image_input = gr.Image(type='filepath') with gr.Column(): prompt = gr.Textbox("puppies in a cloud, 4k", label='Prompt', placeholder="Prompt", lines=3) negative_prompt = gr.Textbox(placeholder="badly drawn", label='Negative Prompt', lines=3) with gr.Row(): with gr.Column(): sampler = gr.Dropdown(value="Euler a", show_label=True, label="Sampling Method", choices=SAMPLER_LIST) model = gr.Dropdown( interactive=True, value="control_v11p_sd15_canny [d14c016b]", show_label=True, label="ControlNet Model", choices=CMODELS ) module = gr.Dropdown( interactive=True, value="none", show_label=True, label="ControlNet Module", choices=CMODULES ) seed = gr.Number(label="Seed", value=-1) with gr.Column(): width = gr.Slider(label="Width", maximum=1024, value=512, step=8) height = gr.Slider(label="Height", maximum=1024, value=512, step=8) steps = gr.Slider(label="Sampling Steps", minimum=1, maximum=30, value=25, step=1) cfg_scale = gr.Slider(label="CFG Scale", minimum=1, maximum=20, value=7, step=1) resize_mode = gr.Dropdown(label='resize_mode', value="0", choices=["0", "1", "2"]) with gr.Row(): threshold_a = gr.Number(label="threshold_a", value=100) threshold_b = gr.Number(label="threshold_b", value=200) text_button = gr.Button("Generate", variant='primary') with gr.Column(scale=7): image_output = gr.Image() text_button.click(controlnet_sd, inputs=[image_input, model, module, threshold_a, threshold_b, resize_mode, prompt, negative_prompt, steps, cfg_scale, seed, sampler, width, height], outputs=image_output) with gr.Tab("/upscale"): with gr.Row(): with gr.Column(): image_input = gr.Image(type='filepath') scale_by = gr.Radio(['2', '4'], label="Scale by") upscale_btn = gr.Button("Upscale!", variant='primary') with gr.Column(): image_output = gr.Image() upscale_btn.click(image_upscale, inputs=[image_input, scale_by], outputs=image_output) demo.launch(show_api=False)