3 and 4

3/hough.py

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+#! /usr/bin/env python
+# -*- coding: utf-8 -*-
+# vim:fenc=utf-8
+#
+# Copyright © 2018 pavle <pavle.portic@tilda.center>
+#
+# Distributed under terms of the MIT license.
+
+"""
+@file hough_lines.py
+@brief This program demonstrates line finding with the Hough transform
+"""
+import sys
+import math
+import cv2 as cv
+import numpy as np
+def main(argv):
+	default_file =  "set/A6.png"
+	filename = argv[0] if len(argv) > 0 else default_file
+	# Loads an image
+	src = cv.imread(filename, cv.IMREAD_GRAYSCALE)
+	# Check if image is loaded fine
+	if src is None:
+		print ('Error opening image!')
+		print ('Usage: hough_lines.py [image_name -- default ' + default_file + '] \n')
+		return -1
+
+	dst = cv.Canny(src, 50, 200, None, 3)
+
+	# Copy edges to the images that will display the results in BGR
+	cdst = cv.cvtColor(dst, cv.COLOR_GRAY2BGR)
+	lines = cv.HoughLines(dst, 1, np.pi / 180, 150, None, 0, 0)
+
+	if lines is not None:
+		#  for i in range(0, len(lines)):
+		for i in [ 0 ]:
+			rho = lines[i][0][0]
+			theta = lines[i][0][1]
+			a = math.cos(theta)
+			b = math.sin(theta)
+			x0 = a * rho
+			y0 = b * rho
+			pt1 = (int(x0 + 1000*(-b)), int(y0 + 1000*(a)))
+			pt2 = (int(x0 - 1000*(-b)), int(y0 - 1000*(a)))
+			cv.line(cdst, pt1, pt2, (0,0,255), 3, cv.LINE_AA)
+	print type(lines)
+
+	cv.imshow("Source", src)
+	cv.imshow("Detected Lines (in red) - Standard Hough Line Transform", cdst)
+	cv.waitKey()
+	return 0
+
+if __name__ == "__main__":
+	main(sys.argv[1:])

3/inputs/A1.txt

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+@@DATASET_DIR@@\A1.png

3/inputs/A10.txt

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+@@DATASET_DIR@@\A10.png

3/inputs/A2.txt

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+@@DATASET_DIR@@\A2.png

3/inputs/A3.txt

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+@@DATASET_DIR@@\A3.png

3/inputs/A4.txt

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+@@DATASET_DIR@@\A4.png

3/inputs/A5.txt

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+@@DATASET_DIR@@\A5.png

3/inputs/A6.txt

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+@@DATASET_DIR@@\A6.png

3/inputs/A7.txt

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+@@DATASET_DIR@@\A7.png

3/inputs/A8.txt

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+@@DATASET_DIR@@\A8.png

3/inputs/A9.txt

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+@@DATASET_DIR@@\A9.png

3/outputs/1.out

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+475G

3/outputs/10.out

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+622G

3/outputs/2.out

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+684G

3/outputs/3.out

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+683G

3/outputs/4.out

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+56GG

3/outputs/5.out

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+151G

3/outputs/6.out

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+473G

3/outputs/7.out

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+564G

3/outputs/8.out

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+184G

3/outputs/9.out

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+153G

3/proba.py

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+import cv2 as cv
+import numpy as np
+
+images = ['set/A1.png','set/A2.png','set/A3.png','set/A4.png','set/A5.png','set/A6.png','set/A7.png','set/A8.png','set/A9.png','set/A10.png']
+
+
+def main():
+	i = images[4]
+	img = cv.imread(i, 0)
+
+	kernel = np.ones((5,5),np.uint8)
+	closing = cv.morphologyEx(img, cv.MORPH_CLOSE, kernel)
+
+	cv.imshow("Closing", closing)
+	cv.imshow("Source", img)
+	cv.waitKey()
+
+
+def rotateImage(image, angle):
+	image_center = tuple(np.array(image.shape)/2)
+	rot_mat = cv.getRotationMatrix2D(image_center,angle,1.0)
+	result = cv.warpAffine(image, rot_mat, image.shape,flags=cv.INTER_LINEAR)
+	return result
+
+
+if __name__ == "__main__":
+	main()
+

4/hough_circle.py

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+# -*- coding: utf-8 -*-
+# vim:fenc=utf-8
+#
+# Copyright © 2018 pavle <pavle.portic@tilda.center>
+#
+# Distributed under terms of the MIT license.
+# set/example_
+
+import cv2 as cv
+import numpy as np
+import os
+
+def main():
+	root = raw_input()
+	filename = [f for f in os.listdir(root) if os.path.isfile(os.path.join(root, f))]
+	filename.sort()
+	filename = filename[0]
+	detect_circle(os.path.join(root, filename))
+
+
+def detect_circle(filename):
+	src = cv.imread(filename, cv.IMREAD_COLOR)
+
+	gray = cv.cvtColor(src, cv.COLOR_BGR2GRAY)
+	rows = gray.shape[0]
+	circles = cv.HoughCircles(gray, cv.HOUGH_GRADIENT, 1, rows/16, 100, 100, 30, 1, 50)
+
+	if circles is not None:
+		circles = np.uint16(np.around(circles))
+		print circles[0][0][0], circles[0][0][1], 0, 0, 0, 0, 0
+
+
+if __name__ == "__main__":
+	main()
+

4/hough_line.py

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+#! /usr/bin/env python
+# -*- coding: utf-8 -*-
+# vim:fenc=utf-8
+#
+# Copyright © 2018 pavle <pavle.portic@tilda.center>
+#
+# Distributed under terms of the MIT license.
+"""
+@file hough_lines.py
+@brief This program demonstrates line finding with the Hough transform
+"""
+import sys
+import math
+import cv2 as cv
+import numpy as np
+def main(argv):
+
+	default_file =  "set/example_2/frame_0001.png"
+	filename = argv[0] if len(argv) > 0 else default_file
+	# Loads an image
+	src = cv.imread(filename, cv.IMREAD_GRAYSCALE)
+	# Check if image is loaded fine
+	if src is None:
+		print ('Error opening image!')
+		print ('Usage: hough_lines.py [image_name -- default ' + default_file + '] \n')
+		return -1
+
+
+	dst = cv.Canny(src, 50, 200, None, 3)
+
+	# Copy edges to the images that will display the results in BGR
+	#  cdst = cv.cvtColor(dst, cv.COLOR_GRAY2BGR)
+	cdstP = cv.cvtColor(dst, cv.COLOR_GRAY2BGR)
+	#  cdstP = np.copy(cdst)
+
+	#  lines = cv.HoughLines(dst, 1, np.pi / 180, 150, None, 0, 0)
+
+	#  if lines is not None:
+		#  for i in range(0, len(lines)):
+			#  rho = lines[i][0][0]
+			#  theta = lines[i][0][1]
+			#  a = math.cos(theta)
+			#  b = math.sin(theta)
+			#  x0 = a * rho
+			#  y0 = b * rho
+			#  pt1 = (int(x0 + 1000*(-b)), int(y0 + 1000*(a)))
+			#  pt2 = (int(x0 - 1000*(-b)), int(y0 - 1000*(a)))
+			#  cv.line(cdst, pt1, pt2, (0,0,255), 3, cv.LINE_AA)
+
+	linesP = cv.HoughLinesP(dst, 1, np.pi / 180, 40, None, 40, 50)
+	print len(linesP)
+
+	if linesP is not None:
+		for i in range(0, len(linesP)):
+			l = linesP[i][0]
+			cv.line(cdstP, (l[0], l[1]), (l[2], l[3]), (0,0,255), 3, cv.LINE_AA)
+
+	cv.imshow("Source", src)
+	#  cv.imshow("Detected Lines (in red) - Standard Hough Line Transform", cdst)
+	cv.imshow("Detected Lines (in red) - Probabilistic Line Transform", cdstP)
+
+	cv.waitKey()
+	return 0
+
+if __name__ == "__main__":
+	main(sys.argv[1:])
+

4/inputs/example_1.txt

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+@@DATASET_DIR@@\example_1

4/inputs/example_10.txt

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+@@DATASET_DIR@@\example_10

4/inputs/example_2.txt

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+@@DATASET_DIR@@\example_2

4/inputs/example_3.txt

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+@@DATASET_DIR@@\example_3

4/inputs/example_4.txt

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+@@DATASET_DIR@@\example_4

4/inputs/example_5.txt

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+@@DATASET_DIR@@\example_5

4/inputs/example_6.txt

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+@@DATASET_DIR@@\example_6

4/inputs/example_7.txt

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+@@DATASET_DIR@@\example_7

4/inputs/example_8.txt

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+@@DATASET_DIR@@\example_8

4/inputs/example_9.txt

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+@@DATASET_DIR@@\example_9

4/outputs/1.out

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+186 99 7 2 116 1 28

4/outputs/10.out

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+209 175 8 3 119 15 26

4/outputs/2.out

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+135 138 9 4 164 1 28

4/outputs/3.out

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+153 195 11 5 125 10 29

4/outputs/4.out

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+154 172 8 0 73 2 13

4/outputs/5.out

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+208 227 8 0 102 6 22

4/outputs/6.out

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+208 126 7 2 157 8 25

4/outputs/7.out

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+146 150 9 5 99 1 16

4/outputs/8.out

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+137 141 9 0 65 16 23

4/outputs/9.out

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+127 188 9 0 63 25 33