Added default prompts and fixed inference pause control

app.py

@@ -65,7 +65,7 @@ def Slerp(start, end, alpha):
     second = torch.sin(alpha*omega)/sinOmega
     return first.unsqueeze(1)*start + second.unsqueeze(1)*end
 
-def Diffuse(latentWalk, generatorSeed, inputImage, mask, prompt, negativePrompt, guidanceScale, numInferenceSteps):
+def Diffuse(latentWalk, generatorSeed, inputImage, mask, prompt, negativePrompt, guidanceScale, numInferenceSteps, pauseInference):
     global lastImage, lastSeed, generator, oldLatentWalk, activeLatents
 
     if mask is None or pauseInference is True:
@@ -130,8 +130,8 @@ with gradio.Blocks(live=True) as ux:
             #staticLatents = gradio.Checkbox(label="Static Latents", info=staticLatentsDesc, value=True, interactive=True)
             inputImage = gradio.Image(label="Input Feed", source="webcam", shape=[512,512], streaming=True)
             mask = gradio.Image(label="Mask", type="pil", value=defaultMask)
-            prompt = gradio.Textbox(label="Prompt", info=promptDesc, placeholder=examplePrompt1, lines=3)
-            negativePrompt = gradio.Textbox(label="Negative Prompt", info=negPromptDesc, placeholder="Facial hair", lines=3)
+            prompt = gradio.Textbox(label="Prompt", info=promptDesc, placeholder=examplePrompt1, value="A person", lines=3)
+            negativePrompt = gradio.Textbox(label="Negative Prompt", info=negPromptDesc, placeholder="Facial hair", value="Text, words", 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, 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)
@@ -145,7 +145,7 @@ with gradio.Blocks(live=True) as ux:
             outputImage = gradio.Image(label="Extrapolated Field of View")
             pauseInference = gradio.Checkbox(label="Pause Inference", value=False)
 
-    inferenceInputs = [latentWalk, generatorSeed, inputImage, mask, prompt, negativePrompt, guidanceScale, numInferenceSteps]
+    inferenceInputs = [latentWalk, generatorSeed, inputImage, mask, prompt, negativePrompt, guidanceScale, numInferenceSteps, pauseInference]
     generateLatents.click(GenerateNewLatentsForInference, outputs=latentWalk)
     inputImage.change(fn=Diffuse, inputs=inferenceInputs, outputs=outputImage, show_progress=False)
 
@@ -165,4 +165,4 @@ with gradio.Blocks(live=True) as ux:
 #ux = gradio.Interface(fn=diffuse, title="View Diffusion", article=article, description=description, inputs=inputs, outputs=outputImage, examples=inputExamples, live=True)
 
 print("Launching Demo")
-ux.launch()
+ux.launch() #debug=True)