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https://github.com/Laurent2916/REVA-QCAV.git
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47 lines
1.3 KiB
Python
47 lines
1.3 KiB
Python
#
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# load.py : utils on generators / lists of ids to transform from strings to
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# cropped images and masks
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import os
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import numpy as np
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from PIL import Image
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from .utils import resize_and_crop, get_square, normalize, hwc_to_chw
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def get_ids(dir):
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"""Returns a list of the ids in the directory"""
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return (f[:-4] for f in os.listdir(dir))
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def split_ids(ids, n=2):
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"""Split each id in n, creating n tuples (id, k) for each id"""
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return ((id, i) for id in ids for i in range(n))
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def to_cropped_imgs(ids, dir, suffix, scale):
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"""From a list of tuples, returns the correct cropped img"""
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for id, pos in ids:
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im = resize_and_crop(Image.open(dir + id + suffix), scale=scale)
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yield get_square(im, pos)
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def get_imgs_and_masks(ids, dir_img, dir_mask, scale):
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"""Return all the couples (img, mask)"""
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imgs = to_cropped_imgs(ids, dir_img, '.jpg', scale)
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# need to transform from HWC to CHW
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imgs_switched = map(hwc_to_chw, imgs)
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imgs_normalized = map(normalize, imgs_switched)
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masks = to_cropped_imgs(ids, dir_mask, '_mask.gif', scale)
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return zip(imgs_normalized, masks)
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def get_full_img_and_mask(id, dir_img, dir_mask):
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im = Image.open(dir_img + id + '.jpg')
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mask = Image.open(dir_mask + id + '_mask.gif')
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return np.array(im), np.array(mask)
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