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@@ -0,0 +1,72 @@
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+import math
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+from pathlib import Path
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+import cv2 as cv
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+import numpy as np
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+
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+
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+def find_parallel(lines) -> []:
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+ """Find parallel lines and return their index."""
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+ parallel_lines = []
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+ # TODO Can probably be done using cross-product/zip
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+ for i in range(len(lines)):
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+ for j in range(len(lines)):
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+ if i == j:
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+ # Every line is parallel to itself. We don't want all lines...
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+ continue
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+ if abs(lines[i][0][1] - lines[j][0][1]) == 0:
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+ parallel_lines.append(i)
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+ return parallel_lines
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+
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+
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+def rail_finder_algo_one(filename: str) -> None:
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+ """Create image with the lines laid over."""
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+ # TODO Don't load image twice
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+ source_color_image = cv.imread(cv.samples.findFile(filename), cv.IMREAD_COLOR)
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+ source_greyscale_image = cv.imread(cv.samples.findFile(filename), cv.IMREAD_GRAYSCALE)
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+ edge_detected_image = cv.Canny(source_greyscale_image, 50, 200, None, 3)
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+ # edge_detected_image_color_format = cv.cvtColor(edge_detected_image, cv.COLOR_GRAY2BGR)
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+ detected_lines = cv.HoughLinesP(edge_detected_image, 1, np.pi / 180, 150, None, 250, 0)
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+ # if detected_lines is not None:
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+ # for i in range(0, len(detected_lines)):
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+ # l = detected_lines[i][0]
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+ # cv.line(edge_detected_image_color_format, (l[0], l[1]), (l[2], l[3]), (0, 0, 255), 6, cv.LINE_AA)
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+ parallel_line_indices = find_parallel(detected_lines)
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+ # Color found lines red
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+ for detected_line in detected_lines:
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+ x1, y1, x2, y2 = detected_line[0]
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+ cv.line(source_color_image, (x1, y1), (x2, y2), (0, 0, 255), 6, cv.LINE_AA)
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+ # Color parallel lines green
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+ for parallel_line_index in parallel_line_indices:
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+ x1, y1, x2, y2 = detected_lines[parallel_line_index][0]
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+ cv.line(source_color_image, (x1, y1), (x2, y2), (0, 255, 0), 6, cv.LINE_AA)
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+ cv.imshow("Probabilistic Line Transform", source_color_image)
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+
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+
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+def rail_finder_algo_two(filename):
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+ source_greyscale_image = cv.imread(cv.samples.findFile(filename), cv.IMREAD_GRAYSCALE)
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+ dst = cv.Canny(source_greyscale_image, 50, 200, None, 3)
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+ cdst = cv.cvtColor(dst, cv.COLOR_GRAY2BGR)
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+ lines = cv.HoughLines(dst, 1, np.pi / 180, 450, None, 0, 0)
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+ if lines is not None:
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+ for i in range(0, len(lines)):
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+ rho = lines[i][0][0]
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+ theta = lines[i][0][1]
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+ a = math.cos(theta)
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+ b = math.sin(theta)
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+ x0 = a * rho
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+ y0 = b * rho
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+ pt1 = (int(x0 + 1000 * (-b)), int(y0 + 1000 * (a)))
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+ pt2 = (int(x0 - 1000 * (-b)), int(y0 - 1000 * (a)))
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+ cv.line(cdst, pt1, pt2, (0, 0, 255), 3, cv.LINE_AA)
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+ cv.imshow("Standard Hough Line", cdst)
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+
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+
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+def main():
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+ filename = str(Path(__file__).parent.parent / Path("tests/octiva") / Path("rails_0.jpg"))
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+ rail_finder_algo_one(filename)
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+ # rail_finder_algo_two(filename)
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+ cv.waitKey()
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+
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+
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+if __name__ == "__main__":
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+ main()
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