Created
November 6, 2015 21:23
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| def rank_fn(): | |
| inp = net['input'].input_var | |
| outp = lasagne.layers.get_output(net['rank'], deterministic=True) | |
| return theano.function([inp], outp) | |
| def sorted_by_attr(images, base_path, rank_fun): | |
| results = [] | |
| for im in images: | |
| im_path = os.path.join(base_path, im) | |
| _, a = prepare_image(im_path) | |
| res = rank_fun(a) | |
| results += [(res, im)] | |
| results = sorted(results, key=lambda x: x[0]) | |
| return [r[1] for r in results] | |
| imagePairs = ['Boots/Ankle/Camper/7231825.361448.jpg', 'Boots/Ankle/Jumping Jacks Kids/7995630.362624.jpg', \ | |
| 'Sandals/Heel/Spring Step/7639878.3561.jpg', 'Shoes/Flats/Frye/7970521.332565.jpg', \ | |
| 'Shoes/Heels/Nine West/7490059.1781.jpg', 'Shoes/Loafers/Patagonia/7495020.79745.jpg', \ | |
| 'Shoes/Oxfords/Timberland/7912777.3.jpg', 'Slippers/Slipper Flats/Spenco/8004085.1430.jpg'] | |
| print sorted_by_attr(imagePairs, 'Zappos', rank_fn()) |
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