Fixed bug with num inference steps slider and disabled progress bar

app.py

@@ -50,6 +50,7 @@ def InitializeOutpainting():
                                                                 #safety_checker=lambda images, **kwargs: (images, False))
     
     outpaintPipeline.scheduler = DPMSolverMultistepScheduler.from_config(outpaintPipeline.scheduler.config)
+    outpaintPipeline.set_progress_bar_config(disable=True)
 
 # Based on: https://discuss.pytorch.org/t/help-regarding-slerp-function-for-generative-model-sampling/32475/4
 # Further optimized to trade a divide operation for a multiply
@@ -121,9 +122,9 @@ with gradio.Blocks(live=True) as ux:
             mask = gradio.Image(label="Mask", type="pil", value=defaultMask)
             prompt = gradio.Textbox(label="Prompt", info=promptDesc, placeholder="A person in a room with colored hair", lines=3)
             negativePrompt = gradio.Textbox(label="Negative Prompt", info=negPromptDesc, placeholder="Facial hair", lines=3)
-            guidanceScale = gradio.Slider(label="Guidance Scale", info="A higher value causes the generation to be more relative to the text prompt conditioning.", maximum=100, minimum=1, value=7.5)
-            numInferenceSteps = gradio.Slider(label="Number of Inference Steps", info=numInfStepsDesc, maximum=100, minimum=1, value=20)
-            generatorSeed = gradio.Slider(label="Generator Seed", info=generatorSeedDesc, maximum=10000, value=lastSeed)
+            guidanceScale = gradio.Slider(label="Guidance Scale", info="A higher value causes the generation to be more relative to the text prompt conditioning.", maximum=100, minimum=1, value=7.5, step= 0.1)
+            numInferenceSteps = gradio.Slider(label="Number of Inference Steps", info=numInfStepsDesc, maximum=100, minimum=1, value=20, step=1)
+            generatorSeed = gradio.Slider(label="Generator Seed", info=generatorSeedDesc, maximum=10000, minimum=1, value=lastSeed, step=1)
             #modelIndex = gradio.Dropdown(modelNames, label="Model", value="runwayml/stable-diffusion-inpainting")
             inputImage.style(full_width=True)