First release!

app.py

@@ -28,15 +28,15 @@ else:
     pipeline = StableDiffusionInpaintPipeline.from_pretrained("runwayml/stable-diffusion-inpainting")
                                                               #safety_checker=lambda images, **kwargs: (images, False))
 
-GenerateNewLatentsForInference()
-
 imageSize = (512, 512)
 lastImage = Image.new(mode="RGB", size=imageSize)
 
-lastSeed = 512
-generator = torch.Generator(device).manual_seed(512)
+lastSeed = 4096
+generator = torch.Generator(device).manual_seed(lastSeed)
+
+GenerateNewLatentsForInference()
 
-def diffuse(staticLatents, inputImage, mask, pauseInference, prompt, negativePrompt, guidanceScale, numInferenceSteps, seed):
+def diffuse(staticLatents, generatorSeed, inputImage, mask, pauseInference, prompt, negativePrompt, guidanceScale, numInferenceSteps):
     global latents, lastSeed, generator, deviceStr, lastImage
 
     if mask is None or pauseInference is True:
@@ -45,9 +45,9 @@ def diffuse(staticLatents, inputImage, mask, pauseInference, prompt, negativePro
     if staticLatents is False:
         GenerateNewLatentsForInference()
     
-    if lastSeed != seed:
-        generator = torch.Generator(device).manual_seed(seed)
-        lastSeed = seed
+    if lastSeed != generatorSeed:
+        generator = torch.Generator(device).manual_seed(generatorSeed)
+        lastSeed = generatorSeed
         
     newImage = pipeline(prompt=prompt,
                     negative_prompt=negativePrompt,
@@ -71,12 +71,10 @@ mask = gradio.Image(label="Mask", type="pil", value=defaultMask)
 outputImage = gradio.Image(label="Extrapolated Field of View")
 guidanceScale = gradio.Slider(label="Guidance Scale", maximum=1, value=0.75)
 numInferenceSteps = gradio.Slider(label="Number of Inference Steps", maximum=100, value=25)
-seed = gradio.Slider(label="Generator Seed", maximum=10000, value=4096)
+generatorSeed = gradio.Slider(label="Generator Seed", maximum=10000, value=lastSeed)
 staticLatents =gradio.Checkbox(label="Static Latents", value=True)
 pauseInference = gradio.Checkbox(label="Pause Inference", value=False)
-#generateNewLatents = gradio.Button(label="Generate New Latents")
-#generateNewLatents.click(GenerateNewLatentsForInference)
 
-inputs=[staticLatents, inputImage, mask, pauseInference, prompt, negativePrompt, guidanceScale, numInferenceSteps, seed]
+inputs=[staticLatents, generatorSeed, inputImage, mask, pauseInference, prompt, negativePrompt, guidanceScale, numInferenceSteps]
 ux = gradio.Interface(fn=diffuse, title="View Diffusion", inputs=inputs, outputs=outputImage, live=True)
 ux.launch()