Upload 16 files

app.py

@@ -33,169 +33,30 @@ with app:
     )
     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('Text2Img'):
+                stable_diffusion_text2img_app()
+            with gr.Tab('Img2Img'):
+                stable_diffusion_img2img_app()
+            with gr.Tab('Inpaint'): 
+                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('Canny'):
+                    stable_diffusion_controlnet_canny_app()
+                with gr.Tab('Depth'):
+                    stable_diffusion_controlnet_depth_app()
+                with gr.Tab('HED'):
+                    stable_diffusion_controlnet_hed_app()
+                with gr.Tab('MLSD'):
+                    stable_diffusion_controlnet_mlsd_app()
+                with gr.Tab('Pose'):
+                    stable_diffusion_controlnet_pose_app()
+                with gr.Tab('Seg'): 
+                    stable_diffusion_controlnet_seg_app()
+                with gr.Tab('Scribble'):
+                    stable_diffusion_controlnet_scribble_app()
             
-            keras_diffusion_app = keras_stable_diffusion_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],
-    )
-    
-    keras_diffusion_app['predict'].click(
-        fn = keras_stable_diffusion,
-        inputs = [
-            keras_diffusion_app['model_path'],
-            keras_diffusion_app['prompt'],
-            keras_diffusion_app['negative_prompt'],
-            keras_diffusion_app['guidance_scale'],
-            keras_diffusion_app['num_inference_step'],
-            keras_diffusion_app['height'],
-            keras_diffusion_app['width'],
-        ],
-        outputs = [gr.Gallery(label="Outputs")],
-    )
-
+            with gr.Tab('Keras Diffusion'):       
+                keras_diffusion_app = keras_stable_diffusion_app()
 
 app.launch(debug=True)   

diffusion_webui/controlnet/controlnet_canny.py

@@ -16,10 +16,7 @@ stable_model_list = [
     "stabilityai/stable-diffusion-2-1-base"
 ]
 
-stable_inpiant_model_list = [
-    "stabilityai/stable-diffusion-2-inpainting",
-    "runwayml/stable-diffusion-inpainting"
-]
+
 
 stable_prompt_list = [
         "a photo of a man.",
@@ -82,57 +79,63 @@ def stable_diffusion_controlnet_canny(
 
 
 def stable_diffusion_controlnet_canny_app():
-    with gr.Tab('Canny'):
-        controlnet_canny_image_file = gr.Image(
-            type='filepath', 
-            label='Image'
-        )
-
-        controlnet_canny_model_id = gr.Dropdown(
-            choices=stable_model_list, 
-            value=stable_model_list[0], 
-            label='Stable Model Id'
-        )
-
-        controlnet_canny_prompt = gr.Textbox(
-            lines=1, 
-            value=stable_prompt_list[0], 
-            label='Prompt'
+    with gr.Blocks():
+        with gr.Row():
+            with gr.Column():
+                controlnet_canny_image_file = gr.Image(
+                    type='filepath', 
+                    label='Image'
+                )
+
+                controlnet_canny_model_id = gr.Dropdown(
+                    choices=stable_model_list, 
+                    value=stable_model_list[0], 
+                    label='Stable Model Id'
+                )
+
+                controlnet_canny_prompt = gr.Textbox(
+                    lines=1, 
+                    value=stable_prompt_list[0], 
+                    label='Prompt'
+                )
+
+                controlnet_canny_negative_prompt = gr.Textbox(
+                    lines=1, 
+                    value=stable_negative_prompt_list[0], 
+                    label='Negative Prompt'
+                )
+
+                with gr.Accordion("Advanced Options", open=False):
+                    controlnet_canny_guidance_scale = gr.Slider(
+                        minimum=0.1, 
+                        maximum=15, 
+                        step=0.1, 
+                        value=7.5, 
+                        label='Guidance Scale'
+                    )
+
+                    controlnet_canny_num_inference_step = gr.Slider(
+                        minimum=1, 
+                        maximum=100, 
+                        step=1, 
+                        value=50, 
+                        label='Num Inference Step'
+                    )
+
+                controlnet_canny_predict = gr.Button(value='Generator')
+                
+            with gr.Column():
+                output_image = gr.Image(label='Output')
+                    
+        controlnet_canny_predict.click(
+            fn=stable_diffusion_controlnet_canny,
+            inputs=[
+                controlnet_canny_image_file,
+                controlnet_canny_model_id,
+                controlnet_canny_prompt,
+                controlnet_canny_negative_prompt,
+                controlnet_canny_guidance_scale,
+                controlnet_canny_num_inference_step,
+            ],
+            outputs=[output_image],
         )
-
-        controlnet_canny_negative_prompt = gr.Textbox(
-            lines=1, 
-            value=stable_negative_prompt_list[0], 
-            label='Negative Prompt'
-        )
-
-        with gr.Accordion("Advanced Options", open=False):
-            controlnet_canny_guidance_scale = gr.Slider(
-                minimum=0.1, 
-                maximum=15, 
-                step=0.1, 
-                value=7.5, 
-                label='Guidance Scale'
-            )
-
-            controlnet_canny_num_inference_step = gr.Slider(
-                minimum=1, 
-                maximum=100, 
-                step=1, 
-                value=50, 
-                label='Num Inference Step'
-            )
-
-        controlnet_canny_predict = gr.Button(value='Generator')
-    
-    variables = {
-        'image_path': controlnet_canny_image_file,
-        'model_path': controlnet_canny_model_id,
-        'prompt': controlnet_canny_prompt,
-        'negative_prompt': controlnet_canny_negative_prompt,
-        'guidance_scale': controlnet_canny_guidance_scale,
-        'num_inference_step': controlnet_canny_num_inference_step,
-        'predict': controlnet_canny_predict        
-    }
-    
-    return variables

diffusion_webui/controlnet/controlnet_depth.py

@@ -15,10 +15,6 @@ stable_model_list = [
     "stabilityai/stable-diffusion-2-1-base"
 ]
 
-stable_inpiant_model_list = [
-    "stabilityai/stable-diffusion-2-inpainting",
-    "runwayml/stable-diffusion-inpainting"
-]
 
 stable_prompt_list = [
         "a photo of a man.",
@@ -81,57 +77,63 @@ def stable_diffusion_controlnet_depth(
 
 
 def stable_diffusion_controlnet_depth_app():
-    with gr.Tab('Depth'):
-        controlnet_depth_image_file = gr.Image(
-            type='filepath', 
-            label='Image'
-        )
-
-        controlnet_depth_model_id = gr.Dropdown(
-            choices=stable_model_list, 
-            value=stable_model_list[0], 
-            label='Stable Model Id'
-        )
-
-        controlnet_depth_prompt = gr.Textbox(
-            lines=1, 
-            value=stable_prompt_list[0], 
-            label='Prompt'
-        )
-
-        controlnet_depth_negative_prompt = gr.Textbox(
-            lines=1, 
-            value=stable_negative_prompt_list[0], 
-            label='Negative Prompt'
+    with gr.Blocks():
+        with gr.Row():
+            with gr.Column():
+                controlnet_depth_image_file = gr.Image(
+                    type='filepath', 
+                    label='Image'
+                )
+
+                controlnet_depth_model_id = gr.Dropdown(
+                    choices=stable_model_list, 
+                    value=stable_model_list[0], 
+                    label='Stable Model Id'
+                )
+
+                controlnet_depth_prompt = gr.Textbox(
+                    lines=1, 
+                    value=stable_prompt_list[0], 
+                    label='Prompt'
+                )
+
+                controlnet_depth_negative_prompt = gr.Textbox(
+                    lines=1, 
+                    value=stable_negative_prompt_list[0], 
+                    label='Negative Prompt'
+                )
+
+                with gr.Accordion("Advanced Options", open=False):
+                    controlnet_depth_guidance_scale = gr.Slider(
+                        minimum=0.1, 
+                        maximum=15, 
+                        step=0.1, 
+                        value=7.5, 
+                        label='Guidance Scale'
+                    )
+
+                    controlnet_depth_num_inference_step = gr.Slider(
+                        minimum=1, 
+                        maximum=100, 
+                        step=1, 
+                        value=50, 
+                        label='Num Inference Step'
+                    )
+
+                controlnet_depth_predict = gr.Button(value='Generator')
+            
+            with gr.Column():
+                output_image = gr.Image(label='Output')
+        
+        controlnet_depth_predict.click(
+            fn=stable_diffusion_controlnet_depth,
+            inputs=[
+                controlnet_depth_image_file,
+                controlnet_depth_model_id,
+                controlnet_depth_prompt,
+                controlnet_depth_negative_prompt,
+                controlnet_depth_guidance_scale,
+                controlnet_depth_num_inference_step,
+            ],
+            outputs=output_image
         )
-
-        with gr.Accordion("Advanced Options", open=False):
-            controlnet_depth_guidance_scale = gr.Slider(
-                minimum=0.1, 
-                maximum=15, 
-                step=0.1, 
-                value=7.5, 
-                label='Guidance Scale'
-            )
-
-            controlnet_depth_num_inference_step = gr.Slider(
-                minimum=1, 
-                maximum=100, 
-                step=1, 
-                value=50, 
-                label='Num Inference Step'
-            )
-
-        controlnet_depth_predict = gr.Button(value='Generator')
-
-    variables = {
-        'image_path': controlnet_depth_image_file,
-        'model_path': controlnet_depth_model_id,
-        'prompt': controlnet_depth_prompt,
-        'negative_prompt': controlnet_depth_negative_prompt,
-        'guidance_scale': controlnet_depth_guidance_scale,
-        'num_inference_step': controlnet_depth_num_inference_step,
-        'predict': controlnet_depth_predict
-    }
-    
-    return variables

diffusion_webui/controlnet/controlnet_hed.py

@@ -14,11 +14,6 @@ stable_model_list = [
     "stabilityai/stable-diffusion-2-1-base"
 ]
 
-stable_inpiant_model_list = [
-    "stabilityai/stable-diffusion-2-inpainting",
-    "runwayml/stable-diffusion-inpainting"
-]
-
 stable_prompt_list = [
         "a photo of a man.",
         "a photo of a girl."
@@ -76,57 +71,65 @@ def stable_diffusion_controlnet_hed(
     return output[0]
 
 def stable_diffusion_controlnet_hed_app():
-    with gr.Tab('Hed'):
-        controlnet_hed_image_file = gr.Image(
-            type='filepath', 
-            label='Image'
+    with gr.Blocks():
+        with gr.Row():
+            with gr.Column():
+                controlnet_hed_image_file = gr.Image(
+                    type='filepath', 
+                    label='Image'
+                )
+
+                controlnet_hed_model_id = gr.Dropdown(
+                    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], 
+                    label='Prompt'
+                )
+
+                controlnet_hed_negative_prompt = gr.Textbox(
+                    lines=1, 
+                    value=stable_negative_prompt_list[0], 
+                    label='Negative Prompt'
+                )
+
+                with gr.Accordion("Advanced Options", open=False):
+                    controlnet_hed_guidance_scale = gr.Slider(
+                        minimum=0.1, 
+                        maximum=15, 
+                        step=0.1, 
+                        value=7.5, 
+                        label='Guidance Scale'
+                    )
+
+                    controlnet_hed_num_inference_step = gr.Slider(
+                        minimum=1, 
+                        maximum=100, 
+                        step=1, 
+                        value=50, 
+                        label='Num Inference Step'
+                    )
+
+                controlnet_hed_predict = gr.Button(value='Generator')
+            
+        
+            with gr.Column():
+                output_image = gr.Image(label='Output')
+        
+        controlnet_hed_predict.click(
+            fn=stable_diffusion_controlnet_hed,
+            inputs=[
+                controlnet_hed_image_file,
+                controlnet_hed_model_id,
+                controlnet_hed_prompt,
+                controlnet_hed_negative_prompt,
+                controlnet_hed_guidance_scale,
+                controlnet_hed_num_inference_step,
+            ],
+            outputs=[output_image]
         )
-
-        controlnet_hed_model_id = gr.Dropdown(
-            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], 
-            label='Prompt'
-        )
-
-        controlnet_hed_negative_prompt = gr.Textbox(
-            lines=1, 
-            value=stable_negative_prompt_list[0], 
-            label='Negative Prompt'
-        )
-
-        with gr.Accordion("Advanced Options", open=False):
-            controlnet_hed_guidance_scale = gr.Slider(
-                minimum=0.1, 
-                maximum=15, 
-                step=0.1, 
-                value=7.5, 
-                label='Guidance Scale'
-            )
-
-            controlnet_hed_num_inference_step = gr.Slider(
-                minimum=1, 
-                maximum=100, 
-                step=1, 
-                value=50, 
-                label='Num Inference Step'
-            )
-
-        controlnet_hed_predict = gr.Button(value='Generator')
-    
-    variables = {
-        'image_path': controlnet_hed_image_file,
-        'model_path': controlnet_hed_model_id,
-        'prompt': controlnet_hed_prompt,
-        'negative_prompt': controlnet_hed_negative_prompt,
-        'guidance_scale': controlnet_hed_guidance_scale,
-        'num_inference_step': controlnet_hed_num_inference_step,
-        'predict': controlnet_hed_predict
-    }
-
-    return variables
+        

diffusion_webui/controlnet/controlnet_mlsd.py

@@ -14,11 +14,6 @@ stable_model_list = [
     "stabilityai/stable-diffusion-2-1-base"
 ]
 
-stable_inpiant_model_list = [
-    "stabilityai/stable-diffusion-2-inpainting",
-    "runwayml/stable-diffusion-inpainting"
-]
-
 stable_prompt_list = [
         "a photo of a man.",
         "a photo of a girl."
@@ -76,58 +71,63 @@ def stable_diffusion_controlnet_mlsd(
     return output[0]
 
 def stable_diffusion_controlnet_mlsd_app():
-    with gr.Tab('MLSD line'):
-        controlnet_mlsd_image_file = gr.Image(
-            type='filepath', 
-            label='Image'
+    with gr.Blocks():
+        with gr.Row():
+            with gr.Column():
+                controlnet_mlsd_image_file = gr.Image(
+                    type='filepath', 
+                    label='Image'
+                )
+
+                controlnet_mlsd_model_id = gr.Dropdown(
+                    choices=stable_model_list, 
+                    value=stable_model_list[0], 
+                    label='Stable Model Id'
+                )
+
+                controlnet_mlsd_prompt = gr.Textbox(
+                    lines=1, 
+                    value=stable_prompt_list[0], 
+                    label='Prompt'
+                )
+
+                controlnet_mlsd_negative_prompt = gr.Textbox(
+                    lines=1, 
+                    value=stable_negative_prompt_list[0], 
+                    label='Negative Prompt'
+                )
+
+                with gr.Accordion("Advanced Options", open=False):
+                    controlnet_mlsd_guidance_scale = gr.Slider(
+                        minimum=0.1, 
+                        maximum=15, 
+                        step=0.1, 
+                        value=7.5, 
+                        label='Guidance Scale'
+                    )
+
+                    controlnet_mlsd_num_inference_step = gr.Slider(
+                        minimum=1, 
+                        maximum=100, 
+                        step=1, 
+                        value=50, 
+                        label='Num Inference Step'
+                    )
+
+                controlnet_mlsd_predict = gr.Button(value='Generator')
+
+            with gr.Column():
+                output_image = gr.Image(label='Output')
+        
+        controlnet_mlsd_predict.click(
+            fn=stable_diffusion_controlnet_mlsd,
+            inputs=[
+                controlnet_mlsd_image_file,
+                controlnet_mlsd_model_id,
+                controlnet_mlsd_prompt,
+                controlnet_mlsd_negative_prompt,
+                controlnet_mlsd_guidance_scale,
+                controlnet_mlsd_num_inference_step
+            ],
+            outputs=output_image
         )
-
-        controlnet_mlsd_model_id = gr.Dropdown(
-            choices=stable_model_list, 
-            value=stable_model_list[0], 
-            label='Stable Model Id'
-        )
-
-        controlnet_mlsd_prompt = gr.Textbox(
-            lines=1, 
-            value=stable_prompt_list[0], 
-            label='Prompt'
-        )
-
-        controlnet_mlsd_negative_prompt = gr.Textbox(
-            lines=1, 
-            value=stable_negative_prompt_list[0], 
-            label='Negative Prompt'
-        )
-
-        with gr.Accordion("Advanced Options", open=False):
-            controlnet_mlsd_guidance_scale = gr.Slider(
-                minimum=0.1, 
-                maximum=15, 
-                step=0.1, 
-                value=7.5, 
-                label='Guidance Scale'
-            )
-
-            controlnet_mlsd_num_inference_step = gr.Slider(
-                minimum=1, 
-                maximum=100, 
-                step=1, 
-                value=50, 
-                label='Num Inference Step'
-            )
-
-        controlnet_mlsd_predict = gr.Button(value='Generator')
-
-    variables = {
-        'image_path': controlnet_mlsd_image_file,
-        'model_path': controlnet_mlsd_model_id,
-        'prompt': controlnet_mlsd_prompt,
-        'negative_prompt': controlnet_mlsd_negative_prompt,
-        'guidance_scale': controlnet_mlsd_guidance_scale,
-        'num_inference_step': controlnet_mlsd_num_inference_step,
-        'predict': controlnet_mlsd_predict
-    }
-
-    return variables
-    

diffusion_webui/controlnet/controlnet_pose.py

@@ -15,11 +15,6 @@ stable_model_list = [
     "stabilityai/stable-diffusion-2-1-base"
 ]
 
-stable_inpiant_model_list = [
-    "stabilityai/stable-diffusion-2-inpainting",
-    "runwayml/stable-diffusion-inpainting"
-]
-
 stable_prompt_list = [
         "a photo of a man.",
         "a photo of a girl."
@@ -78,57 +73,63 @@ def stable_diffusion_controlnet_pose(
 
 
 def stable_diffusion_controlnet_pose_app():
-    with gr.Tab('Pose'):
-        controlnet_pose_image_file = gr.Image(
-            type='filepath', 
-            label='Image'
+    with gr.Blocks():
+        with gr.Row():
+            with gr.Column():
+                controlnet_pose_image_file = gr.Image(
+                    type='filepath', 
+                    label='Image'
+                )
+
+                controlnet_pose_model_id = gr.Dropdown(
+                    choices=stable_model_list, 
+                    value=stable_model_list[0], 
+                    label='Stable Model Id'
+                )
+
+                controlnet_pose_prompt = gr.Textbox(
+                    lines=1, 
+                    value=stable_prompt_list[0], 
+                    label='Prompt'
+                )
+
+                controlnet_pose_negative_prompt = gr.Textbox(
+                    lines=1, 
+                    value=stable_negative_prompt_list[0], 
+                    label='Negative Prompt'
+                )
+
+                with gr.Accordion("Advanced Options", open=False):
+                    controlnet_pose_guidance_scale = gr.Slider(
+                        minimum=0.1, 
+                        maximum=15, 
+                        step=0.1, 
+                        value=7.5, 
+                        label='Guidance Scale'
+                    )
+
+                    controlnet_pose_num_inference_step = gr.Slider(
+                        minimum=1, 
+                        maximum=100, 
+                        step=1, 
+                        value=50, 
+                        label='Num Inference Step'
+                    )
+
+                controlnet_pose_predict = gr.Button(value='Generator')
+
+            with gr.Column():
+                output_image = gr.Image(label='Output')
+        
+        controlnet_pose_predict.click(
+            fn=stable_diffusion_controlnet_pose,
+            inputs=[
+                controlnet_pose_image_file,
+                controlnet_pose_model_id,
+                controlnet_pose_prompt,
+                controlnet_pose_negative_prompt,
+                controlnet_pose_guidance_scale,
+                controlnet_pose_num_inference_step,
+            ],
+            outputs=output_image
         )
-
-        controlnet_pose_model_id = gr.Dropdown(
-            choices=stable_model_list, 
-            value=stable_model_list[0], 
-            label='Stable Model Id'
-        )
-
-        controlnet_pose_prompt = gr.Textbox(
-            lines=1, 
-            value=stable_prompt_list[0], 
-            label='Prompt'
-        )
-
-        controlnet_pose_negative_prompt = gr.Textbox(
-            lines=1, 
-            value=stable_negative_prompt_list[0], 
-            label='Negative Prompt'
-        )
-
-        with gr.Accordion("Advanced Options", open=False):
-            controlnet_pose_guidance_scale = gr.Slider(
-                minimum=0.1, 
-                maximum=15, 
-                step=0.1, 
-                value=7.5, 
-                label='Guidance Scale'
-            )
-
-            controlnet_pose_num_inference_step = gr.Slider(
-                minimum=1, 
-                maximum=100, 
-                step=1, 
-                value=50, 
-                label='Num Inference Step'
-            )
-
-        controlnet_pose_predict = gr.Button(value='Generator')
-
-    variables = {
-        'image_path': controlnet_pose_image_file,
-        'model_path': controlnet_pose_model_id,
-        'prompt': controlnet_pose_prompt,
-        'negative_prompt': controlnet_pose_negative_prompt,
-        'guidance_scale': controlnet_pose_guidance_scale,
-        'num_inference_step': controlnet_pose_num_inference_step,
-        'predict': controlnet_pose_predict
-    }
-    
-    return variables

diffusion_webui/controlnet/controlnet_scribble.py

@@ -15,11 +15,6 @@ stable_model_list = [
     "stabilityai/stable-diffusion-2-1-base"
 ]
 
-stable_inpiant_model_list = [
-    "stabilityai/stable-diffusion-2-inpainting",
-    "runwayml/stable-diffusion-inpainting"
-]
-
 stable_prompt_list = [
         "a photo of a man.",
         "a photo of a girl."
@@ -76,57 +71,63 @@ def stable_diffusion_controlnet_scribble(
     return output[0]
 
 def stable_diffusion_controlnet_scribble_app():
-    with gr.Tab('Scribble'):
-        controlnet_scribble_image_file = gr.Image(
-            type='filepath', 
-            label='Image'
+    with gr.Blocks():
+        with gr.Row():
+            with gr.Column():
+                controlnet_scribble_image_file = gr.Image(
+                    type='filepath', 
+                    label='Image'
+                )
+
+                controlnet_scribble_model_id = gr.Dropdown(
+                    choices=stable_model_list, 
+                    value=stable_model_list[0], 
+                    label='Stable Model Id'
+                )
+
+                controlnet_scribble_prompt = gr.Textbox(
+                    lines=1, 
+                    value=stable_prompt_list[0], 
+                    label='Prompt'
+                )
+
+                controlnet_scribble_negative_prompt = gr.Textbox(
+                    lines=1, 
+                    value=stable_negative_prompt_list[0], 
+                    label='Negative Prompt'
+                )
+
+                with gr.Accordion("Advanced Options", open=False):
+                    controlnet_scribble_guidance_scale = gr.Slider(
+                        minimum=0.1, 
+                        maximum=15, 
+                        step=0.1, 
+                        value=7.5, 
+                        label='Guidance Scale'
+                    )
+
+                    controlnet_scribble_num_inference_step = gr.Slider(
+                        minimum=1, 
+                        maximum=100, 
+                        step=1, 
+                        value=50, 
+                        label='Num Inference Step'
+                    )
+
+                controlnet_scribble_predict = gr.Button(value='Generator')
+
+            with gr.Column():
+                output_image = gr.Image(label='Output')
+        
+        controlnet_scribble_predict.click(
+            fn=stable_diffusion_controlnet_scribble,
+            inputs=[
+                controlnet_scribble_image_file,
+                controlnet_scribble_model_id,
+                controlnet_scribble_prompt,
+                controlnet_scribble_negative_prompt,
+                controlnet_scribble_guidance_scale,
+                controlnet_scribble_num_inference_step,
+            ],
+            outputs=output_image
         )
-
-        controlnet_scribble_model_id = gr.Dropdown(
-            choices=stable_model_list, 
-            value=stable_model_list[0], 
-            label='Stable Model Id'
-        )
-
-        controlnet_scribble_prompt = gr.Textbox(
-            lines=1, 
-            value=stable_prompt_list[0], 
-            label='Prompt'
-        )
-
-        controlnet_scribble_negative_prompt = gr.Textbox(
-            lines=1, 
-            value=stable_negative_prompt_list[0], 
-            label='Negative Prompt'
-        )
-
-        with gr.Accordion("Advanced Options", open=False):
-            controlnet_scribble_guidance_scale = gr.Slider(
-                minimum=0.1, 
-                maximum=15, 
-                step=0.1, 
-                value=7.5, 
-                label='Guidance Scale'
-            )
-
-            controlnet_scribble_num_inference_step = gr.Slider(
-                minimum=1, 
-                maximum=100, 
-                step=1, 
-                value=50, 
-                label='Num Inference Step'
-            )
-
-        controlnet_scribble_predict = gr.Button(value='Generator')
-
-    variables = {
-        'image_path': controlnet_scribble_image_file,
-        'model_path': controlnet_scribble_model_id,
-        'prompt': controlnet_scribble_prompt,
-        'negative_prompt': controlnet_scribble_negative_prompt,
-        'guidance_scale': controlnet_scribble_guidance_scale,
-        'num_inference_step': controlnet_scribble_num_inference_step,
-        'predict': controlnet_scribble_predict
-    }
-    
-    return variables

diffusion_webui/controlnet/controlnet_seg.py

@@ -17,11 +17,6 @@ stable_model_list = [
     "stabilityai/stable-diffusion-2-1-base"
 ]
 
-stable_inpiant_model_list = [
-    "stabilityai/stable-diffusion-2-inpainting",
-    "runwayml/stable-diffusion-inpainting"
-]
-
 stable_prompt_list = [
         "a photo of a man.",
         "a photo of a girl."
@@ -135,57 +130,64 @@ def stable_diffusion_controlnet_seg(
     return output[0]
 
 def stable_diffusion_controlnet_seg_app():
-    with gr.Tab('Segmentation'):
-        controlnet_seg_image_file = gr.Image(
-            type='filepath', 
-            label='Image'
+    with gr.Blocks():
+        with gr.Row():
+            with gr.Column():
+                controlnet_seg_image_file = gr.Image(
+                    type='filepath', 
+                    label='Image'
+                )
+
+                controlnet_seg_model_id = gr.Dropdown(
+                    choices=stable_model_list, 
+                    value=stable_model_list[0], 
+                    label='Stable Model Id'
+                )
+
+                controlnet_seg_prompt = gr.Textbox(
+                    lines=1, 
+                    value=stable_prompt_list[0], 
+                    label='Prompt'
+                )
+
+                controlnet_seg_negative_prompt = gr.Textbox(
+                    lines=1, 
+                    value=stable_negative_prompt_list[0], 
+                    label='Negative Prompt'
+                )
+
+                with gr.Accordion("Advanced Options", open=False):
+                    controlnet_seg_guidance_scale = gr.Slider(
+                        minimum=0.1, 
+                        maximum=15, 
+                        step=0.1, 
+                        value=7.5, 
+                        label='Guidance Scale'
+                    )
+
+                    controlnet_seg_num_inference_step = gr.Slider(
+                        minimum=1, 
+                        maximum=100, 
+                        step=1, 
+                        value=50, 
+                        label='Num Inference Step'
+                    )
+
+                controlnet_seg_predict = gr.Button(value='Generator')
+
+            with gr.Column():
+                output_image = gr.Image(label='Output')
+        
+        controlnet_seg_predict.click(
+            fn=stable_diffusion_controlnet_seg,
+            inputs=[
+                controlnet_seg_image_file,
+                controlnet_seg_model_id,
+                controlnet_seg_prompt,
+                controlnet_seg_negative_prompt,
+                controlnet_seg_guidance_scale,
+                controlnet_seg_num_inference_step,
+            ],
+            outputs=[output_image],
         )
-
-        controlnet_seg_model_id = gr.Dropdown(
-            choices=stable_model_list, 
-            value=stable_model_list[0], 
-            label='Stable Model Id'
-        )
-
-        controlnet_seg_prompt = gr.Textbox(
-            lines=1, 
-            value=stable_prompt_list[0], 
-            label='Prompt'
-        )
-
-        controlnet_seg_negative_prompt = gr.Textbox(
-            lines=1, 
-            value=stable_negative_prompt_list[0], 
-            label='Negative Prompt'
-        )
-
-        with gr.Accordion("Advanced Options", open=False):
-            controlnet_seg_guidance_scale = gr.Slider(
-                minimum=0.1, 
-                maximum=15, 
-                step=0.1, 
-                value=7.5, 
-                label='Guidance Scale'
-            )
-
-            controlnet_seg_num_inference_step = gr.Slider(
-                minimum=1, 
-                maximum=100, 
-                step=1, 
-                value=50, 
-                label='Num Inference Step'
-            )
-
-        controlnet_seg_predict = gr.Button(value='Generator')
-
-    variables = {
-        'image_path': controlnet_seg_image_file,
-        'model_path': controlnet_seg_model_id,
-        'prompt': controlnet_seg_prompt,
-        'negative_prompt': controlnet_seg_negative_prompt,
-        'guidance_scale': controlnet_seg_guidance_scale,
-        'num_inference_step': controlnet_seg_num_inference_step,
-        'predict': controlnet_seg_predict,
-    }
-    
-    return variables
+            

diffusion_webui/stable_diffusion/img2img_app.py

@@ -60,57 +60,63 @@ def stable_diffusion_img2img(
 
 
 def stable_diffusion_img2img_app():
-    with gr.Tab('Image2Image'):
-        image2image2_image_file = gr.Image(
-            type='filepath', 
-            label='Image'
+    with gr.Blocks():
+        with gr.Row():
+            with gr.Column():
+                image2image2_image_file = gr.Image(
+                    type='filepath', 
+                    label='Image'
+                )
+
+                image2image_model_path = gr.Dropdown(
+                    choices=stable_model_list, 
+                    value=stable_model_list[0], 
+                    label='Image-Image Model Id'
+                )
+
+                image2image_prompt = gr.Textbox(
+                    lines=1, 
+                    value=stable_prompt_list[0], 
+                    label='Prompt'
+                )
+
+                image2image_negative_prompt = gr.Textbox(
+                    lines=1, 
+                    value=stable_negative_prompt_list[0], 
+                    label='Negative Prompt'
+                )
+
+                with gr.Accordion("Advanced Options", open=False):
+                    image2image_guidance_scale = gr.Slider(
+                        minimum=0.1, 
+                        maximum=15, 
+                        step=0.1, 
+                        value=7.5, 
+                        label='Guidance Scale'
+                    )
+
+                    image2image_num_inference_step = gr.Slider(
+                        minimum=1, 
+                        maximum=100, 
+                        step=1, 
+                        value=50, 
+                        label='Num Inference Step'
+                    )
+
+                image2image_predict = gr.Button(value='Generator')
+
+            with gr.Column():
+                output_image = gr.Image(label='Output')
+                    
+        image2image_predict.click(
+            fn=stable_diffusion_img2img,
+            inputs=[
+                image2image2_image_file,
+                image2image_model_path,
+                image2image_prompt,
+                image2image_negative_prompt,
+                image2image_guidance_scale,
+                image2image_num_inference_step,
+            ],  
+            outputs=[output_image],
         )
-
-        image2image_model_path = gr.Dropdown(
-            choices=stable_model_list, 
-            value=stable_model_list[0], 
-            label='Image-Image Model Id'
-        )
-
-        image2image_prompt = gr.Textbox(
-            lines=1, 
-            value=stable_prompt_list[0], 
-            label='Prompt'
-        )
-
-        image2image_negative_prompt = gr.Textbox(
-            lines=1, 
-            value=stable_negative_prompt_list[0], 
-            label='Negative Prompt'
-        )
-
-        with gr.Accordion("Advanced Options", open=False):
-            image2image_guidance_scale = gr.Slider(
-                minimum=0.1, 
-                maximum=15, 
-                step=0.1, 
-                value=7.5, 
-                label='Guidance Scale'
-            )
-
-            image2image_num_inference_step = gr.Slider(
-                minimum=1, 
-                maximum=100, 
-                step=1, 
-                value=50, 
-                label='Num Inference Step'
-            )
-
-        image2image_predict = gr.Button(value='Generator')
-
-    variables = {
-        'image_path': image2image2_image_file,
-        'model_path': image2image_model_path,
-        'prompt': image2image_prompt,
-        'negative_prompt': image2image_negative_prompt,
-        'guidance_scale': image2image_guidance_scale,
-        'num_inference_step': image2image_num_inference_step,
-        'predict': image2image_predict
-    }
-
-    return variables

diffusion_webui/stable_diffusion/inpaint_app.py

@@ -62,60 +62,68 @@ def stable_diffusion_inpaint(
 
 
 def stable_diffusion_inpaint_app():
-    with gr.Tab('Inpaint'):
-        inpaint_image_file = gr.Image(
-            source='upload', 
-            tool='sketch', 
-            elem_id="image_upload", 
-            type="pil", 
-            label="Upload"
-        ).style(height=400)
-
-        inpaint_model_id = gr.Dropdown(
-            choices=stable_inpiant_model_list, 
-            value=stable_inpiant_model_list[0], 
-            label='Inpaint Model Id'
+    with gr.Blocks():
+        with gr.Row():
+            with gr.Column():
+                inpaint_image_file = gr.Image(
+                    source='upload', 
+                    tool='sketch', 
+                    elem_id="image_upload", 
+                    type="pil", 
+                    label="Upload"
+                ).style(height=400)
+
+                inpaint_model_id = gr.Dropdown(
+                    choices=stable_inpiant_model_list, 
+                    value=stable_inpiant_model_list[0], 
+                    label='Inpaint Model Id'
+                )
+
+                inpaint_prompt = gr.Textbox(
+                    lines=1, 
+                    value=stable_prompt_list[0], 
+                    label='Prompt'
+                )
+
+                inpaint_negative_prompt = gr.Textbox(
+                    lines=1, 
+                    value=stable_negative_prompt_list[0], 
+                    label='Negative Prompt'
+                )
+
+                with gr.Accordion("Advanced Options", open=False):
+                    inpaint_guidance_scale = gr.Slider(
+                        minimum=0.1, 
+                        maximum=15, 
+                        step=0.1, 
+                        value=7.5, 
+                        label='Guidance Scale'
+                    )
+
+                    inpaint_num_inference_step = gr.Slider(
+                        minimum=1, 
+                        maximum=100, 
+                        step=1, 
+                        value=50, 
+                        label='Num Inference Step'
+                    )
+
+                inpaint_predict = gr.Button(value='Generator')
+
+            
+            with gr.Column():
+                output_image = gr.Gallery(label="Outputs")
+            
+        inpaint_predict.click(
+            fn=stable_diffusion_inpaint,
+            inputs=[
+                inpaint_image_file,
+                inpaint_model_id,
+                inpaint_prompt,
+                inpaint_negative_prompt,
+                inpaint_guidance_scale,
+                inpaint_num_inference_step,
+            ],
+            outputs=output_image
         )
-
-        inpaint_prompt = gr.Textbox(
-            lines=1, 
-            value=stable_prompt_list[0], 
-            label='Prompt'
-        )
-
-        inpaint_negative_prompt = gr.Textbox(
-            lines=1, 
-            value=stable_negative_prompt_list[0], 
-            label='Negative Prompt'
-        )
-
-        with gr.Accordion("Advanced Options", open=False):
-            inpaint_guidance_scale = gr.Slider(
-                minimum=0.1, 
-                maximum=15, 
-                step=0.1, 
-                value=7.5, 
-                label='Guidance Scale'
-            )
-
-            inpaint_num_inference_step = gr.Slider(
-                minimum=1, 
-                maximum=100, 
-                step=1, 
-                value=50, 
-                label='Num Inference Step'
-            )
-
-        inpaint_predict = gr.Button(value='Generator')
-    
-    variables = {
-        "image_path": inpaint_image_file,
-        "model_path": inpaint_model_id,
-        "prompt": inpaint_prompt,
-        "negative_prompt": inpaint_negative_prompt,
-        "guidance_scale": inpaint_guidance_scale,
-        "num_inference_step": inpaint_num_inference_step,
-        "predict": inpaint_predict
-    }
-
-    return variables
+                

diffusion_webui/stable_diffusion/keras_txt2img.py

@@ -48,69 +48,75 @@ def keras_stable_diffusion(
     return generated_images
 
 def keras_stable_diffusion_app():
-    with gr.Tab('Keras Diffusion'):
-        keras_text2image_model_path = gr.Dropdown(
-            choices=stable_model_list, 
-            value=stable_model_list[0], 
-            label='Text-Image Model Id'
-        )
-
-        keras_text2image_prompt = gr.Textbox(
-            lines=1, 
-            value=stable_prompt_list[0], 
-            label='Prompt'
-        )
-
-        keras_text2image_negative_prompt = gr.Textbox(
-            lines=1, 
-            value=stable_negative_prompt_list[0], 
-            label='Negative Prompt'
-        )
-
-        with gr.Accordion("Advanced Options", open=False):
-            keras_text2image_guidance_scale = gr.Slider(
-                minimum=0.1, 
-                maximum=15, 
-                step=0.1, 
-                value=7.5, 
-                label='Guidance Scale'
-            )
-
-            keras_text2image_num_inference_step = gr.Slider(
-                minimum=1, 
-                maximum=100, 
-                step=1, 
-                value=50, 
-                label='Num Inference Step'
-            )
-
-            keras_text2image_height = gr.Slider(
-                minimum=128, 
-                maximum=1280, 
-                step=32, 
-                value=512, 
-                label='Image Height'
-            )
-
-            keras_text2image_width = gr.Slider(
-                minimum=128, 
-                maximum=1280, 
-                step=32, 
-                value=768, 
-                label='Image Height'
-            )
-
-        keras_text2image_predict = gr.Button(value='Generator')
+    with gr.Blocks():
+        with gr.Row():
+            with gr.Column():
+                keras_text2image_model_path = gr.Dropdown(
+                    choices=stable_model_list, 
+                    value=stable_model_list[0], 
+                    label='Text-Image Model Id'
+                )
+
+                keras_text2image_prompt = gr.Textbox(
+                    lines=1, 
+                    value=stable_prompt_list[0], 
+                    label='Prompt'
+                )
+
+                keras_text2image_negative_prompt = gr.Textbox(
+                    lines=1, 
+                    value=stable_negative_prompt_list[0], 
+                    label='Negative Prompt'
+                )
+
+                with gr.Accordion("Advanced Options", open=False):
+                    keras_text2image_guidance_scale = gr.Slider(
+                        minimum=0.1, 
+                        maximum=15, 
+                        step=0.1, 
+                        value=7.5, 
+                        label='Guidance Scale'
+                    )
+
+                    keras_text2image_num_inference_step = gr.Slider(
+                        minimum=1, 
+                        maximum=100, 
+                        step=1, 
+                        value=50, 
+                        label='Num Inference Step'
+                    )
+
+                    keras_text2image_height = gr.Slider(
+                        minimum=128, 
+                        maximum=1280, 
+                        step=32, 
+                        value=512, 
+                        label='Image Height'
+                    )
+
+                    keras_text2image_width = gr.Slider(
+                        minimum=128, 
+                        maximum=1280, 
+                        step=32, 
+                        value=768, 
+                        label='Image Height'
+                    )
+
+                keras_text2image_predict = gr.Button(value='Generator')
     
-    variables = {
-        "model_path": keras_text2image_model_path,
-        "prompt": keras_text2image_prompt,
-        "negative_prompt": keras_text2image_negative_prompt,
-        "guidance_scale": keras_text2image_guidance_scale,
-        "num_inference_step": keras_text2image_num_inference_step,
-        "height": keras_text2image_height,
-        "width": keras_text2image_width,
-        "predict": keras_text2image_predict
-    }
-
-    return variables 
+            with gr.Column():
+                output_image = gr.Image(label='Output')
+                        
+        keras_text2image_predict.click(
+            fn=keras_stable_diffusion,
+            inputs=[
+                keras_text2image_model_path,
+                keras_text2image_prompt,
+                keras_text2image_negative_prompt,
+                keras_text2image_guidance_scale,
+                keras_text2image_num_inference_step,
+                keras_text2image_height,
+                keras_text2image_width
+            ],
+            outputs=output_image
+        )

diffusion_webui/stable_diffusion/text2img_app.py

@@ -10,11 +10,6 @@ stable_model_list = [
     "stabilityai/stable-diffusion-2-1-base"
 ]
 
-stable_inpiant_model_list = [
-    "stabilityai/stable-diffusion-2-inpainting",
-    "runwayml/stable-diffusion-inpainting"
-]
-
 stable_prompt_list = [
         "a photo of a man.",
         "a photo of a girl."
@@ -56,70 +51,76 @@ def stable_diffusion_text2img(
     return images[0]
 
 def stable_diffusion_text2img_app():
-    with gr.Tab('Text2Image'):
-        text2image_model_path = gr.Dropdown(
-            choices=stable_model_list, 
-            value=stable_model_list[0], 
-            label='Text-Image Model Id'
-        )
-
-        text2image_prompt = gr.Textbox(
-            lines=1, 
-            value=stable_prompt_list[0], 
-            label='Prompt'
+    with gr.Blocks():
+        with gr.Row():
+            with gr.Column():
+                text2image_model_path = gr.Dropdown(
+                    choices=stable_model_list, 
+                    value=stable_model_list[0], 
+                    label='Text-Image Model Id'
+                )
+
+                text2image_prompt = gr.Textbox(
+                    lines=1, 
+                    value=stable_prompt_list[0], 
+                    label='Prompt'
+                )
+
+                text2image_negative_prompt = gr.Textbox(
+                    lines=1, 
+                    value=stable_negative_prompt_list[0], 
+                    label='Negative Prompt'
+                )
+
+                with gr.Accordion("Advanced Options", open=False):
+                    text2image_guidance_scale = gr.Slider(
+                        minimum=0.1, 
+                        maximum=15, 
+                        step=0.1, 
+                        value=7.5, 
+                        label='Guidance Scale'
+                    )
+
+                    text2image_num_inference_step = gr.Slider(
+                        minimum=1, 
+                        maximum=100, 
+                        step=1, 
+                        value=50, 
+                        label='Num Inference Step'
+                    )
+
+                    text2image_height = gr.Slider(
+                        minimum=128, 
+                        maximum=1280, 
+                        step=32, 
+                        value=512, 
+                        label='Image Height'
+                    )
+
+                    text2image_width = gr.Slider(
+                        minimum=128, 
+                        maximum=1280, 
+                        step=32, 
+                        value=768, 
+                        label='Image Height'
+                    )
+
+                text2image_predict = gr.Button(value='Generator')
+        
+            with gr.Column():
+                output_image = gr.Image(label='Output')
+                    
+        
+        text2image_predict.click(
+            fn=stable_diffusion_text2img,
+            inputs=[
+                text2image_model_path,
+                text2image_prompt,
+                text2image_negative_prompt,
+                text2image_guidance_scale,
+                text2image_num_inference_step,
+                text2image_height,
+                text2image_width,
+            ],
+            outputs=output_image
         )
-
-        text2image_negative_prompt = gr.Textbox(
-            lines=1, 
-            value=stable_negative_prompt_list[0], 
-            label='Negative Prompt'
-        )
-
-        with gr.Accordion("Advanced Options", open=False):
-            text2image_guidance_scale = gr.Slider(
-                minimum=0.1, 
-                maximum=15, 
-                step=0.1, 
-                value=7.5, 
-                label='Guidance Scale'
-            )
-
-            text2image_num_inference_step = gr.Slider(
-                minimum=1, 
-                maximum=100, 
-                step=1, 
-                value=50, 
-                label='Num Inference Step'
-            )
-
-            text2image_height = gr.Slider(
-                minimum=128, 
-                maximum=1280, 
-                step=32, 
-                value=512, 
-                label='Image Height'
-            )
-
-            text2image_width = gr.Slider(
-                minimum=128, 
-                maximum=1280, 
-                step=32, 
-                value=768, 
-                label='Image Height'
-            )
-
-        text2image_predict = gr.Button(value='Generator')
-    
-    variables = {
-        "model_path": text2image_model_path,
-        "prompt": text2image_prompt,
-        "negative_prompt": text2image_negative_prompt,
-        "guidance_scale": text2image_guidance_scale,
-        "num_inference_step": text2image_num_inference_step,
-        "height": text2image_height,
-        "width": text2image_width,
-        "predict": text2image_predict
-    }
-
-    return variables 
-