Spaces:
Running
on
Zero
Running
on
Zero
Update app.py
Browse files
app.py
CHANGED
@@ -1,6 +1,7 @@
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import os
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import einops
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import gradio as gr
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import numpy as np
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import torch
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import random
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@@ -116,8 +117,14 @@ def inference(input_image, prompt, a_prompt, n_prompt, denoise_steps, upscale, a
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except Exception as e:
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print(e)
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image = Image.new(mode="RGB", size=(512, 512))
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-
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title = "Pixel-Aware Stable Diffusion for Real-ISR"
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description = "Gradio Demo for PASD Real-ISR. To use it, simply upload your image, or click one of the examples to load them."
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@@ -135,7 +142,7 @@ demo = gr.Interface(
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gr.Slider(label="Conditioning Scale", minimum=0.5, maximum=1.5, value=1.1, step=0.1),
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gr.Slider(label="Classier-free Guidance", minimum=0.1, maximum=10.0, value=7.5, step=0.1),
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gr.Slider(label="Seed", minimum=-1, maximum=2147483647, step=1, randomize=True)],
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outputs=gr.Image(type="pil"),
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title=title,
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description=description,
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article=article).queue()
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import os
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import einops
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import gradio as gr
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from gradio_imageslider import ImageSlider
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import numpy as np
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import torch
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import random
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except Exception as e:
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print(e)
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image = Image.new(mode="RGB", size=(512, 512))
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# Convert and save the image as JPEG
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image.save('result.jpg', 'JPEG')
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# Convert and save the image as JPEG
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input_image.save('input.jpg', 'JPEG')
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return image, ("input.jpg", "result.jpg")
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title = "Pixel-Aware Stable Diffusion for Real-ISR"
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description = "Gradio Demo for PASD Real-ISR. To use it, simply upload your image, or click one of the examples to load them."
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gr.Slider(label="Conditioning Scale", minimum=0.5, maximum=1.5, value=1.1, step=0.1),
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gr.Slider(label="Classier-free Guidance", minimum=0.1, maximum=10.0, value=7.5, step=0.1),
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gr.Slider(label="Seed", minimum=-1, maximum=2147483647, step=1, randomize=True)],
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outputs=[gr.Image(type="pil"), ImageSlider(position=0.5)],
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title=title,
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description=description,
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article=article).queue()
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