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import numpy as np |
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import data.thinplate as tps |
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import cv2 |
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import random |
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import math |
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def tps_transform(img, dshape=None): |
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while True: |
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point1 = round(random.uniform(0.3, 0.7), 2) |
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point2 = round(random.uniform(0.3, 0.7), 2) |
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range_1 = round(random.uniform(-0.25, 0.25), 2) |
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range_2 = round(random.uniform(-0.25, 0.25), 2) |
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if math.isclose(point1 + range_1, point2 + range_2): |
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continue |
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else: |
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break |
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c_src = np.array([ |
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[0.0, 0.0], |
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[1., 0], |
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[1, 1], |
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[0, 1], |
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[point1, point1], |
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[point2, point2], |
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]) |
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c_dst = np.array([ |
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[0., 0], |
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[1., 0], |
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[1, 1], |
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[0, 1], |
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[point1 + range_1, point1 + range_1], |
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[point2 + range_2, point2 + range_2], |
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]) |
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dshape = dshape or img.shape |
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theta = tps.tps_theta_from_points(c_src, c_dst, reduced=True) |
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grid = tps.tps_grid(theta, c_dst, dshape) |
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mapx, mapy = tps.tps_grid_to_remap(grid, img.shape) |
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return cv2.remap(img, mapx, mapy, cv2.INTER_CUBIC) |
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