Last active
February 9, 2018 16:14
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Script that cuts a line into small pieces
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import numpy as np | |
import cv2 | |
import matplotlib.pyplot as plt | |
def linear_transform(x, src_range=(360, 719), dest_range=(16, 60)): | |
src_width, dest_width = src_range[1] - src_range[0], dest_range[1] - dest_range[0] | |
return dest_range[1] - (src_range[1] - x) / src_width * dest_width | |
def norm2(x): | |
return np.linalg.norm(x, ord=2) | |
def cut(start, end, intensity=1, min_y=360): | |
xy_delta = np.array([end[0] - start[0], end[1] - start[1]]) | |
dir_vec = (end - start) / norm2(end - start) | |
dest_range = (linear_transform(end[1]), linear_transform(start[1])) | |
dest_width = dest_range[1] - dest_range[0] | |
moves = [] | |
cur_pt = start.copy().astype(np.float_) | |
centers = np.array([]).reshape(-1, 2) | |
centers = np.vstack((centers, cur_pt.reshape(-1, 2))) | |
for i in range(25): | |
step_pix = (dest_range[1] - norm2(cur_pt - start) / norm2(xy_delta) * dest_width) | |
moves.append(step_pix) | |
cur_pt += dir_vec * step_pix / intensity | |
centers = np.vstack((centers, cur_pt.reshape(-1, 2))) | |
if cur_pt[1] <= min_y: | |
break | |
step_pix = (dest_range[1] - norm2(cur_pt - start) / norm2(xy_delta) * dest_width) | |
moves.append(step_pix) | |
return centers, moves | |
def test_cutter(): | |
start, end = np.array([400, 700]), np.array([640, 360]) | |
centers, moves = cut(start, end, intensity=1) | |
im = np.zeros((720, 1280, 3)) | |
cv2.line(im, tuple(start), tuple(end), (0, 0, 255), 1) | |
for c, m in zip(centers, moves): | |
piece = [c[0] - m / 2, c[1] - m / 2, c[0] + m / 2, c[1] + m / 2] | |
cv2.rectangle(im, (int(piece[0]), int(piece[1])), (int(piece[2]), int(piece[3])), (0, 255, 0), 1) | |
plt.imshow(im, interpolation='bilinear'); | |
plt.show() |
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