Upload 8 files

app.py

@@ -3,13 +3,13 @@ from utils.image2image import stable_diffusion_img2img
 from utils.text2image import stable_diffusion_text2img
 from utils.inpaint import stable_diffusion_inpaint
 
-from controlnet.controlnet_canny import stable_diffusion_controlnet_img2img
-from controlnet.controlnet_depth import stable_diffusion_controlnet_img2img
-from controlnet.controlnet_hed import stable_diffusion_controlnet_img2img
-from controlnet.controlnet_mlsd import stable_diffusion_controlnet_img2img
-from controlnet.controlnet_pose import stable_diffusion_controlnet_img2img
-from controlnet.controlnet_scribble import stable_diffusion_controlnet_img2img
-from controlnet.controlnet_seg import stable_diffusion_controlnet_img2img
+from controlnet.controlnet_canny import stable_diffusion_controlnet_canny
+from controlnet.controlnet_depth import stable_diffusion_controlnet_depth
+from controlnet.controlnet_hed import stable_diffusion_controlnet_hed
+from controlnet.controlnet_mlsd import stable_diffusion_controlnet_mlsd
+from controlnet.controlnet_pose import stable_diffusion_controlnet_pose
+from controlnet.controlnet_scribble import stable_diffusion_controlnet_scribble
+from controlnet.controlnet_seg import stable_diffusion_controlnet_seg
 
 
 import gradio as gr
@@ -39,7 +39,7 @@ stable_negative_prompt_list = [
     ]
 app = gr.Blocks()
 with app:
-    gr.Markdown("# **<h2 align='center'>Stable Diffusion + ControlNet WebUI<h2>**")
+    gr.Markdown("# **<h2 align='center'>Stable Diffusion WebUI<h2>**")
     gr.Markdown(
         """
         <h5 style='text-align: center'>
@@ -190,7 +190,6 @@ with app:
 
                 inpaint_predict = gr.Button(value='Generator')
 
-
             with gr.Tab('ControlNet'):
                 with gr.Tab('Canny'):
                     controlnet_canny_image_file = gr.Image(label='Image')
@@ -236,14 +235,14 @@ with app:
                     controlnet_hed_image_file = gr.Image(label='Image')
 
                     controlnet_hed_model_id = gr.Dropdown(
-                        choices=stable_prompt_list, 
-                        value=stable_prompt_list[0], 
+                        choices=stable_model_list, 
+                        value=stable_model_list[0], 
                         label='Stable Model Id'
                     )
 
                     controlnet_hed_prompt = gr.Textbox(
                         lines=1, 
-                        value=stable_prompt_list[0], 
+                        value=stable_model_list[0], 
                         label='Prompt'
                     )
 
@@ -276,8 +275,8 @@ with app:
                     controlnet_mlsd_image_file = gr.Image(label='Image')
 
                     controlnet_mlsd_model_id = gr.Dropdown(
-                        choices=stable_prompt_list, 
-                        value=stable_prompt_list[0], 
+                        choices=stable_model_list, 
+                        value=stable_model_list[0], 
                         label='Stable Model Id'
                     )
 
@@ -316,8 +315,8 @@ with app:
                     controlnet_seg_image_file = gr.Image(label='Image')
 
                     controlnet_seg_model_id = gr.Dropdown(
-                        choices=stable_prompt_list, 
-                        value=stable_prompt_list[0], 
+                        choices=stable_model_list, 
+                        value=stable_model_list[0], 
                         label='Stable Model Id'
                     )
 
@@ -356,8 +355,8 @@ with app:
                     controlnet_depth_image_file = gr.Image(label='Image')
 
                     controlnet_depth_model_id = gr.Dropdown(
-                        choices=stable_prompt_list, 
-                        value=stable_prompt_list[0], 
+                        choices=stable_model_list, 
+                        value=stable_model_list[0], 
                         label='Stable Model Id'
                     )
 
@@ -396,8 +395,8 @@ with app:
                     controlnet_scribble_image_file = gr.Image(label='Image')
 
                     controlnet_scribble_model_id = gr.Dropdown(
-                        choices=stable_prompt_list, 
-                        value=stable_prompt_list[0], 
+                        choices=stable_model_list, 
+                        value=stable_model_list[0], 
                         label='Stable Model Id'
                     )
 
@@ -436,8 +435,8 @@ with app:
                     controlnet_pose_image_file = gr.Image(label='Image')
 
                     controlnet_pose_model_id = gr.Dropdown(
-                        choices=stable_prompt_list, 
-                        value=stable_prompt_list[0], 
+                        choices=stable_model_list, 
+                        value=stable_model_list[0], 
                         label='Stable Model Id'
                     )
 
@@ -516,9 +515,8 @@ with app:
             outputs = [output_image],
         )  
 
-
         controlnet_canny_predict.click(
-            fn = stable_diffusion_controlnet_img2img,
+            fn = stable_diffusion_controlnet_canny,
             inputs = [
                 controlnet_canny_image_file,
                 controlnet_canny_model_id, 
@@ -531,7 +529,7 @@ with app:
         )  
 
         controlnet_hed_predict.click(
-            fn = stable_diffusion_controlnet_img2img,
+            fn = stable_diffusion_controlnet_hed,
             inputs = [
                 controlnet_hed_image_file,
                 controlnet_hed_model_id, 
@@ -544,7 +542,7 @@ with app:
         )  
         
         controlnet_mlsd_predict.click(
-            fn = stable_diffusion_controlnet_img2img,
+            fn = stable_diffusion_controlnet_mlsd,
             inputs = [
                 controlnet_mlsd_image_file,
                 controlnet_mlsd_model_id, 
@@ -557,7 +555,7 @@ with app:
         )  
         
         controlnet_seg_predict.click(
-            fn = stable_diffusion_controlnet_img2img,
+            fn = stable_diffusion_controlnet_seg,
             inputs = [
                 controlnet_seg_image_file,
                 controlnet_seg_model_id, 
@@ -570,7 +568,7 @@ with app:
         )  
         
         controlnet_depth_predict.click(
-            fn = stable_diffusion_controlnet_img2img,
+            fn = stable_diffusion_controlnet_depth,
             inputs = [
                 controlnet_depth_image_file,
                 controlnet_depth_model_id, 
@@ -583,7 +581,7 @@ with app:
         )  
         
         controlnet_scribble_predict.click(
-            fn = stable_diffusion_controlnet_img2img,
+            fn = stable_diffusion_controlnet_scribble,
             inputs = [
                 controlnet_scribble_image_file,
                 controlnet_scribble_model_id, 
@@ -596,7 +594,7 @@ with app:
         )  
         
         controlnet_pose_predict.click(
-            fn = stable_diffusion_controlnet_img2img,
+            fn = stable_diffusion_controlnet_pose,
             inputs = [
                 controlnet_pose_image_file,
                 controlnet_pose_model_id, 

controlnet/controlnet_canny.py

@@ -27,7 +27,7 @@ def controlnet_canny(
     return controlnet, image
 
 
-def stable_diffusion_controlnet_img2img(
+def stable_diffusion_controlnet_canny(
     stable_model_path:str,
     image_path:str,
     prompt:str,

controlnet/controlnet_depth.py

@@ -24,7 +24,7 @@ def controlnet_depth(image_path:str):
 
     return controlnet, image
 
-def stable_diffusion_controlnet_img2img(
+def stable_diffusion_controlnet_depth(
     stable_model_path:str,
     image_path:str,
     prompt:str,

controlnet/controlnet_hed.py

@@ -1,12 +1,9 @@
 from diffusers import ( StableDiffusionControlNetPipeline, 
-                       ControlNetModel, UniPCMultistepScheduler,
-                       DDIMScheduler)
+                       ControlNetModel, UniPCMultistepScheduler)
 
 from controlnet_aux import HEDdetector
 from PIL import Image
-import numpy as np
 import torch
-import cv2
 
 
 def controlnet_hed(image_path:str):
@@ -22,7 +19,7 @@ def controlnet_hed(image_path:str):
     return controlnet, image
 
 
-def stable_diffusion_controlnet_img2img(
+def stable_diffusion_controlnet_hed(
     stable_model_path:str,
     image_path:str,
     prompt:str,

controlnet/controlnet_mlsd.py

@@ -1,12 +1,9 @@
 from diffusers import ( StableDiffusionControlNetPipeline, 
-                       ControlNetModel, UniPCMultistepScheduler,
-                       DDIMScheduler)
+                       ControlNetModel, UniPCMultistepScheduler)
 
 from controlnet_aux import MLSDdetector
 from PIL import Image
-import numpy as np
 import torch
-import cv2
 
 
 def controlnet_mlsd(image_path:str):
@@ -22,7 +19,7 @@ def controlnet_mlsd(image_path:str):
 
     return controlnet, image
 
-def stable_diffusion_controlnet_img2img(
+def stable_diffusion_controlnet_mlsd(
     stable_model_path:str,
     image_path:str,
     prompt:str,

controlnet/controlnet_pose.py

@@ -20,7 +20,7 @@ def controlnet_pose(image_path:str):
 
     return controlnet, image
 
-def stable_diffusion_controlnet_img2img(
+def stable_diffusion_controlnet_pose(
     stable_model_path:str,
     image_path:str,
     prompt:str,

controlnet/controlnet_scribble.py

@@ -1,6 +1,5 @@
 from diffusers import ( StableDiffusionControlNetPipeline, 
-                       ControlNetModel, UniPCMultistepScheduler,
-                       DDIMScheduler)
+                       ControlNetModel, UniPCMultistepScheduler)
 
 from controlnet_aux import HEDdetector
 
@@ -20,7 +19,7 @@ def controlnet_scribble(image_path:str):
 
     return controlnet, image
 
-def stable_diffusion_controlnet_img2img(
+def stable_diffusion_controlnet_scribble(
     stable_model_path:str,
     image_path:str,
     prompt:str,

controlnet/controlnet_seg.py

@@ -78,7 +78,7 @@ def controlnet_mlsd(image_path:str):
     return controlnet, image
 
 
-def stable_diffusion_controlnet_img2img(
+def stable_diffusion_controlnet_seg(
     stable_model_path:str,
     image_path:str,
     prompt:str,