Add application file

app.py

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+import gradio as gr
+import torch
+
+torch.hub.download_url_to_file('https://github.com/kargaranamir/visual-clutter/raw/main/tests/test.jpg', 'test.jpg')
+torch.hub.download_url_to_file('https://github.com/kargaranamir/visual-clutter/raw/main/tests/test2.jpg', 'test2.jpg')
+
+
+def inference(img):
+    clt = Vlc(img.name, numlevels=3, contrast_filt_sigma=1, contrast_pool_sigma=3, color_pool_sigma=3, prefix='test')
+    # get Feature Congestion clutter of a test map:
+    clutter_scalar_fc, clutter_map_fc = clt.getClutter_FC(p=1, pix=1)
+    # get Subband Entropy clutter of the test map:
+    # clutter_scalar_se = clt.getClutter_SE(wlevels=3, wght_chrom=0.0625)
+    return ['test_collapsed combine map.png']
+
+title = 'Visual Clutter'
+description = 'Compute two measures of visual clutter (Feature Congestion and Subband Entropy)'
+article = "<p style='text-align: center'></p>"
+examples = [['test.jpg'],['test2.jpg']]
+css = ".output_image, .input_image {height: 40rem !important; width: 100% !important;}"
+
+gr.Interface(
+    inference,
+    [gr.inputs.Image(type='file', label='Input')],
+    [gr.outputs.Image(type='file', label='Output')],
+    title=title,
+    description=description,
+    article=article,
+    examples=examples,
+    css=css,
+    enable_queue=True
+    ).launch(debug=True)

requirements.txt

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+torch
+gradio
+visual-clutter==1.0