103 lines
3.0 KiB
Python
103 lines
3.0 KiB
Python
"""
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usage: python morph_transform.py file.png
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finds lines present in an image using opencv's morph transform.
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"""
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import sys
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import time
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import cv2
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import numpy as np
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import matplotlib.pyplot as plt
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def timeit(func):
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def timed(*args, **kw):
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start = time.time()
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result = func(*args, **kw)
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end = time.time()
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print 'Function: %r took: %2.4f seconds' % (func.__name__, end - start)
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return result
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return timed
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def mt(imagename, scale=40):
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img = cv2.imread(imagename)
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gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
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threshold = cv2.adaptiveThreshold(np.invert(gray), 255, cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY, 15, -2)
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vertical = threshold
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horizontal = threshold
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verticalsize = vertical.shape[0] / scale
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horizontalsize = horizontal.shape[1] / scale
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ver = cv2.getStructuringElement(cv2.MORPH_RECT, (1, verticalsize))
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hor = cv2.getStructuringElement(cv2.MORPH_RECT, (horizontalsize, 1))
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vertical = cv2.erode(vertical, ver, (-1, -1))
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vertical = cv2.dilate(vertical, ver, (-1, -1))
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horizontal = cv2.erode(horizontal, hor, (-1, -1))
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horizontal = cv2.dilate(horizontal, hor, (-1, -1))
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mask = vertical + horizontal
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joints = np.bitwise_and(vertical, horizontal)
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contours, _ = cv2.findContours(mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
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contours = sorted(contours, key=cv2.contourArea, reverse=True)[:10]
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tables = {}
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for c in contours:
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x, y, w, h = cv2.boundingRect(c)
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x1, x2 = x, x + w
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y1, y2 = y, y + h
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# find number of non-zero values in joints using what boundingRect returns
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roi = joints[y:y+h, x:x+w]
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jc, _ = cv2.findContours(roi, cv2.RETR_CCOMP, cv2.CHAIN_APPROX_SIMPLE)
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if len(jc) <= 4: # remove contours with less than <=4 joints
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continue
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joint_coords = []
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for j in jc:
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jx, jy, jw, jh = cv2.boundingRect(j)
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c1, c2 = x + (2*jx + jw) / 2, y + (2*jy + jh) / 2
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joint_coords.append((c1, c2))
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tables[(x1, y2, x2, y1)] = joint_coords
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vcontours, _ = cv2.findContours(vertical, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
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for vc in vcontours:
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x, y, w, h = cv2.boundingRect(vc)
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x1, x2 = x, x + w
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y1, y2 = y, y + h
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plt.plot([(x1 + x2) / 2, (x1 + x2) / 2], [y2, y1])
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hcontours, _ = cv2.findContours(horizontal, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
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for hc in hcontours:
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x, y, w, h = cv2.boundingRect(hc)
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x1, x2 = x, x + w
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y1, y2 = y, y + h
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plt.plot([x1, x2], [(y1 + y2) / 2, (y1 + y2) / 2])
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x_coord = []
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y_coord = []
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for k in tables.keys():
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for coord in tables[k]:
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x_coord.append(coord[0])
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y_coord.append(coord[1])
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plt.plot(x_coord, y_coord, 'ro')
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plt.imshow(img)
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plt.show()
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return tables
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@timeit
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def main():
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t = mt(sys.argv[1])
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print 'tables found: ', len(t.keys())
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if __name__ == '__main__':
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if len(sys.argv) == 1:
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print __doc__
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else:
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main() |