Spaces:
Running
on
Zero
Running
on
Zero
reedmayhew
commited on
Commit
•
7129683
1
Parent(s):
9fbd930
Update app.py
Browse files
app.py
CHANGED
@@ -4,6 +4,7 @@ import numpy as np
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from transformers import AutoImageProcessor, Swin2SRForImageSuperResolution
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import gradio as gr
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import spaces
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def resize_image(image, max_size=2048):
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width, height = image.size
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@@ -44,11 +45,11 @@ def upscale_chunk(chunk, model, processor, device):
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return Image.fromarray(output_image)
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@spaces.GPU
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def main(image, model_choice, save_as_jpg=True, use_tiling=True
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# Resize the input image
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image = resize_image(image)
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device = torch.device("cuda" if torch.cuda.is_available()
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model_paths = {
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"Pixel Perfect": "caidas/swin2SR-classical-sr-x4-64",
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@@ -77,16 +78,22 @@ def main(image, model_choice, save_as_jpg=True, use_tiling=True, auto_cpu=True):
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# Process the entire image at once
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upscaled_image = upscale_chunk(image, model, processor, device)
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if save_as_jpg:
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-
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else:
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-
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-
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def gradio_interface(image, model_choice, save_as_jpg, use_tiling
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try:
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result = main(image, model_choice, save_as_jpg, use_tiling
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return result, None
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except Exception as e:
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return None, str(e)
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@@ -102,14 +109,13 @@ interface = gr.Interface(
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),
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gr.Checkbox(value=True, label="Save as JPEG"),
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gr.Checkbox(value=True, label="Use Tiling"),
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gr.Checkbox(value=True, label="Auto CPU"),
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],
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outputs=[
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gr.File(label="Download Upscaled Image"),
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gr.Textbox(label="Error Message", visible=True)
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],
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title="Image Upscaler",
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description="Upload an image, select a model, and upscale it. Images larger than 2048x2048 will be resized while maintaining aspect ratio. Use tiling for efficient processing of large images.
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)
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interface.launch()
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from transformers import AutoImageProcessor, Swin2SRForImageSuperResolution
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import gradio as gr
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import spaces
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import os
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def resize_image(image, max_size=2048):
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width, height = image.size
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return Image.fromarray(output_image)
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@spaces.GPU
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def main(image, model_choice, save_as_jpg=True, use_tiling=True):
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# Resize the input image
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image = resize_image(image)
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device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
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model_paths = {
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"Pixel Perfect": "caidas/swin2SR-classical-sr-x4-64",
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# Process the entire image at once
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upscaled_image = upscale_chunk(image, model, processor, device)
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# Generate output filename
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original_filename = os.path.splitext(image.filename)[0] if image.filename else "image"
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output_filename = f"{original_filename}_upscaled"
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if save_as_jpg:
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output_filename += ".jpg"
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upscaled_image.save(output_filename, quality=95)
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else:
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output_filename += ".png"
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upscaled_image.save(output_filename)
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return output_filename
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def gradio_interface(image, model_choice, save_as_jpg, use_tiling):
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try:
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result = main(image, model_choice, save_as_jpg, use_tiling)
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return result, None
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except Exception as e:
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return None, str(e)
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),
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gr.Checkbox(value=True, label="Save as JPEG"),
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gr.Checkbox(value=True, label="Use Tiling"),
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],
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outputs=[
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gr.File(label="Download Upscaled Image"),
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gr.Textbox(label="Error Message", visible=True)
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],
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title="Image Upscaler",
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description="Upload an image, select a model, and upscale it. Images larger than 2048x2048 will be resized while maintaining aspect ratio. Use tiling for efficient processing of large images.",
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)
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interface.launch()
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