| """ | |
| 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(""" | |
| <h1><center>Prodia Studio</center></h> | |
| <h2><center>powered by Prodia Stable Diffusion API</center></h2>""") | |
| with gr.Tab("/sdxl/generate [BETA]"): | |
| with gr.Row(): | |
| with gr.Column(scale=6, min_width=600): | |
| prompt = gr.Textbox("space warrior, beautiful, female, ultrarealistic, soft lighting, 8k", placeholder="Prompt", show_label=False, lines=3) | |
| negative_prompt = gr.Textbox("3d, cartoon, anime, (deformed eyes, nose, ears, nose), bad anatomy, ugly", 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("space warrior, beautiful, female, ultrarealistic, soft lighting, 8k", placeholder="Prompt", show_label=False, lines=3) | |
| negative_prompt = gr.Textbox("3d, cartoon, anime, (deformed eyes, nose, ears, nose), bad anatomy, ugly", placeholder="Negative Prompt", show_label=False, lines=3) | |
| with gr.Row(): | |
| with gr.Column(): | |
| sampler = gr.Dropdown(value="DPM++ 2M Karras", show_label=True, label="Sampling Method", | |
| choices=SAMPLER_LIST) | |
| model = gr.Dropdown( | |
| interactive=True, | |
| value=get_models()[1], | |
| show_label=True, | |
| label="absolutereality_v181.safetensors [3d9d4d2b]", | |
| 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) | |