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Browse files- app.py +7 -3
- examples/tiles/2000-04-28-18-21-24_L5_rgb-0.jpg +0 -0
- examples/tiles/2000-04-28-18-21-24_L5_rgb-1.jpg +0 -0
- examples/tiles/2000-08-02-18-23-18_L5_rgb-0.jpg +0 -0
- examples/tiles/2000-08-02-18-23-18_L5_rgb-1.jpg +0 -0
- examples/tiles/2000-08-18-18-23-46_L5_rgb-0.jpg +0 -0
- examples/tiles/2000-08-18-18-23-46_L5_rgb-1.jpg +0 -0
- examples/tiles/2000-09-19-18-24-18_L5_rgb-0.jpg +0 -0
- examples/tiles/2000-09-19-18-24-18_L5_rgb-1.jpg +0 -0
- examples/tiles/2000-10-21-18-24-43_L5_rgb-0.jpg +0 -0
- examples/tiles/2000-10-21-18-24-43_L5_rgb-1.jpg +0 -0
app.py
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@@ -1,6 +1,7 @@
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import tensorflow as tf
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import numpy as np
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from PIL import Image
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from tensorflow.keras.preprocessing.image import img_to_array
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from huggingface_hub import from_pretrained_keras
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@@ -11,7 +12,8 @@ model.summary()
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def infer(image):
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img = Image.fromarray(image)
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img = img.resize((100,100))
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ycbcr = img.convert("YCbCr")
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y, cb, cr = ycbcr.split()
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y = img_to_array(y)
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@@ -39,14 +41,16 @@ article = "<p style='text-align: center'><a href='https://arxiv.org/abs/1609.051
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examples = [['examples/2000-04-28-18-21-24_L5_rgb.jpg'],['examples/2000-08-02-18-23-18_L5_rgb.jpg'],
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['examples/2000-08-18-18-23-46_L5_rgb.jpg'],['examples/2000-09-19-18-24-18_L5_rgb.jpg'],['examples/2000-10-21-18-24-43_L5_rgb.jpg']]
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iface = gr.Interface(
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fn=infer,
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title = " Satellite Super-resolution",
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description = "This space is a demo of the keras tutorial 'Image Super-Resolution using an Efficient Sub-Pixel CNN' based on the paper 'Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network' π",
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article = article,
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inputs=gr.inputs.Image(label="Input Image"),
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outputs=[gr.outputs.Image(label="
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gr.outputs.Image(label="Super-resolution
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],
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examples=examples,
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).launch()
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import tensorflow as tf
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import numpy as np
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from PIL import Image
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from glob import glob
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from tensorflow.keras.preprocessing.image import img_to_array
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from huggingface_hub import from_pretrained_keras
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def infer(image):
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img = Image.fromarray(image)
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# img = img.resize((100,100))
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img = img.crop((0,100,0,100))
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ycbcr = img.convert("YCbCr")
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y, cb, cr = ycbcr.split()
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y = img_to_array(y)
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examples = [['examples/2000-04-28-18-21-24_L5_rgb.jpg'],['examples/2000-08-02-18-23-18_L5_rgb.jpg'],
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['examples/2000-08-18-18-23-46_L5_rgb.jpg'],['examples/2000-09-19-18-24-18_L5_rgb.jpg'],['examples/2000-10-21-18-24-43_L5_rgb.jpg']]
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examples= [[l] for l in glob('examples/tiles/*.jpg')]
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iface = gr.Interface(
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fn=infer,
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title = " Satellite Super-resolution",
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description = "This space is a demo of the keras tutorial 'Image Super-Resolution using an Efficient Sub-Pixel CNN' based on the paper 'Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network' π",
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article = article,
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inputs=gr.inputs.Image(label="Input Image"),
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outputs=[gr.outputs.Image(label="Cropped input image"),
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gr.outputs.Image(label="Super-resolution x3 image")
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],
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examples=examples,
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).launch()
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examples/tiles/2000-04-28-18-21-24_L5_rgb-0.jpg
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examples/tiles/2000-04-28-18-21-24_L5_rgb-1.jpg
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examples/tiles/2000-08-02-18-23-18_L5_rgb-0.jpg
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examples/tiles/2000-08-02-18-23-18_L5_rgb-1.jpg
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examples/tiles/2000-08-18-18-23-46_L5_rgb-0.jpg
ADDED
examples/tiles/2000-08-18-18-23-46_L5_rgb-1.jpg
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examples/tiles/2000-09-19-18-24-18_L5_rgb-0.jpg
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examples/tiles/2000-09-19-18-24-18_L5_rgb-1.jpg
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examples/tiles/2000-10-21-18-24-43_L5_rgb-0.jpg
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examples/tiles/2000-10-21-18-24-43_L5_rgb-1.jpg
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