Spaces:
Runtime error
Runtime error
File size: 7,728 Bytes
3911a99 82fe494 3911a99 82fe494 2204ef0 82fe494 2204ef0 9f0d168 2204ef0 3101ed2 2204ef0 3101ed2 2204ef0 3911a99 82fe494 3911a99 82fe494 3101ed2 3911a99 2204ef0 3911a99 2204ef0 3911a99 2204ef0 3911a99 2204ef0 3911a99 9ae63a0 3911a99 9ae63a0 3911a99 da178ec 82fe494 3911a99 82fe494 3911a99 da178ec 82fe494 3911a99 82fe494 3f7d745 3911a99 da178ec 82fe494 3911a99 82fe494 3f7d745 3911a99 da178ec 82fe494 3911a99 82fe494 3f7d745 3911a99 da178ec 82fe494 3911a99 82fe494 3f7d745 3911a99 da178ec 82fe494 3911a99 82fe494 3f7d745 3911a99 da178ec 82fe494 3911a99 82fe494 739cb0d 82fe494 3911a99 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 |
from diffusion_webui.controlnet.controlnet_canny import stable_diffusion_controlnet_canny_app, stable_diffusion_controlnet_canny
from diffusion_webui.controlnet.controlnet_depth import stable_diffusion_controlnet_depth_app, stable_diffusion_controlnet_depth
from diffusion_webui.controlnet.controlnet_hed import stable_diffusion_controlnet_hed_app, stable_diffusion_controlnet_hed
from diffusion_webui.controlnet.controlnet_mlsd import stable_diffusion_controlnet_mlsd_app, stable_diffusion_controlnet_mlsd
from diffusion_webui.controlnet.controlnet_pose import stable_diffusion_controlnet_pose_app, stable_diffusion_controlnet_pose
from diffusion_webui.controlnet.controlnet_scribble import stable_diffusion_controlnet_scribble_app, stable_diffusion_controlnet_scribble
from diffusion_webui.controlnet.controlnet_seg import stable_diffusion_controlnet_seg_app, stable_diffusion_controlnet_seg
from diffusion_webui.stable_diffusion.text2img_app import stable_diffusion_text2img_app, stable_diffusion_text2img
from diffusion_webui.stable_diffusion.img2img_app import stable_diffusion_img2img_app, stable_diffusion_img2img
from diffusion_webui.stable_diffusion.inpaint_app import stable_diffusion_inpaint_app, stable_diffusion_inpaint
import gradio as gr
app = gr.Blocks()
with app:
gr.Markdown("# **<h1 align='center'>Stable Diffusion + ControlNet WebUI<h1>**")
gr.Markdown(
"""
<h4 style='text-align: center'>
Follow me for more!
<a href='https://twitter.com/kadirnar_ai' target='_blank'>Twitter</a> | <a href='https://github.com/kadirnar' target='_blank'>Github</a> | <a href='https://www.linkedin.com/in/kadir-nar/' target='_blank'>Linkedin</a>
</h4>
"""
)
with gr.Row():
with gr.Column():
text2image_app = stable_diffusion_text2img_app()
img2img_app = stable_diffusion_img2img_app()
inpaint_app = stable_diffusion_inpaint_app()
with gr.Tab('ControlNet'):
controlnet_canny_app = stable_diffusion_controlnet_canny_app()
controlnet_hed_app = stable_diffusion_controlnet_hed_app()
controlnet_mlsd_app = stable_diffusion_controlnet_mlsd_app()
controlnet_depth_app = stable_diffusion_controlnet_depth_app()
controlnet_pose_app = stable_diffusion_controlnet_pose_app()
controlnet_scribble_app = stable_diffusion_controlnet_scribble_app()
controlnet_seg_app = stable_diffusion_controlnet_seg_app()
with gr.Tab('Output'):
with gr.Column():
output_image = gr.Image(label='Image')
text2image_app['predict'].click(
fn = stable_diffusion_text2img,
inputs = [
text2image_app['model_path'],
text2image_app['prompt'],
text2image_app['negative_prompt'],
text2image_app['guidance_scale'],
text2image_app['num_inference_step'],
text2image_app['height'],
text2image_app['width'],
],
outputs = [output_image],
)
img2img_app['predict'].click(
fn = stable_diffusion_img2img,
inputs = [
img2img_app['image_path'],
img2img_app['model_path'],
img2img_app['prompt'],
img2img_app['negative_prompt'],
img2img_app['guidance_scale'],
img2img_app['num_inference_step'],
],
outputs = [output_image],
)
inpaint_app['predict'].click(
fn = stable_diffusion_inpaint,
inputs = [
inpaint_app['image_path'],
inpaint_app['model_path'],
inpaint_app['prompt'],
inpaint_app['negative_prompt'],
inpaint_app['guidance_scale'],
inpaint_app['num_inference_step'],
],
outputs = [output_image],
)
controlnet_canny_app['predict'].click(
fn = stable_diffusion_controlnet_canny,
inputs = [
controlnet_canny_app['image_path'],
controlnet_canny_app['model_path'],
controlnet_canny_app['prompt'],
controlnet_canny_app['negative_prompt'],
controlnet_canny_app['guidance_scale'],
controlnet_canny_app['num_inference_step'],
],
outputs = [output_image],
)
controlnet_hed_app['predict'].click(
fn = stable_diffusion_controlnet_hed,
inputs = [
controlnet_hed_app['image_path'],
controlnet_hed_app['model_path'],
controlnet_hed_app['prompt'],
controlnet_hed_app['negative_prompt'],
controlnet_hed_app['guidance_scale'],
controlnet_hed_app['num_inference_step'],
],
outputs = [output_image],
)
controlnet_mlsd_app['predict'].click(
fn = stable_diffusion_controlnet_mlsd,
inputs = [
controlnet_mlsd_app['image_path'],
controlnet_mlsd_app['model_path'],
controlnet_mlsd_app['prompt'],
controlnet_mlsd_app['negative_prompt'],
controlnet_mlsd_app['guidance_scale'],
controlnet_mlsd_app['num_inference_step'],
],
outputs = [output_image],
)
controlnet_depth_app['predict'].click(
fn = stable_diffusion_controlnet_seg,
inputs = [
controlnet_depth_app['image_path'],
controlnet_depth_app['model_path'],
controlnet_depth_app['prompt'],
controlnet_depth_app['negative_prompt'],
controlnet_depth_app['guidance_scale'],
controlnet_depth_app['num_inference_step'],
],
outputs = [output_image],
)
controlnet_pose_app['predict'].click(
fn = stable_diffusion_controlnet_depth,
inputs = [
controlnet_pose_app['image_path'],
controlnet_pose_app['model_path'],
controlnet_pose_app['prompt'],
controlnet_pose_app['negative_prompt'],
controlnet_pose_app['guidance_scale'],
controlnet_pose_app['num_inference_step'],
],
outputs = [output_image],
)
controlnet_scribble_app['predict'].click(
fn = stable_diffusion_controlnet_scribble,
inputs = [
controlnet_scribble_app['image_path'],
controlnet_scribble_app['model_path'],
controlnet_scribble_app['prompt'],
controlnet_scribble_app['negative_prompt'],
controlnet_scribble_app['guidance_scale'],
controlnet_scribble_app['num_inference_step'],
],
outputs = [output_image],
)
controlnet_seg_app['predict'].click(
fn = stable_diffusion_controlnet_pose,
inputs = [
controlnet_seg_app['image_path'],
controlnet_seg_app['model_path'],
controlnet_seg_app['prompt'],
controlnet_seg_app['negative_prompt'],
controlnet_seg_app['guidance_scale'],
controlnet_seg_app['num_inference_step'],
],
outputs = [output_image],
)
app.launch(debug=True) |