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import gradio as gr | |
import torch | |
from visual_clutter import Vlc | |
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', str(clutter_scalar_fc), str(clutter_scalar_se)] | |
title = 'Visual Clutter' | |
description = 'Compute two measures of visual clutter (Feature Congestion and Subband Entropy), see the code at https://github.com/kargaranamir/visual-clutter' | |
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='Feature Congestion Output Image'), gr.outputs.Textbox(type="str", label="Feature Congestion"), gr.outputs.Textbox(type="str", label="Subband Entorpy")], | |
title=title, | |
description=description, | |
article=article, | |
examples=examples, | |
css=css, | |
).launch(debug=True, enable_queue=True) |