eye-tracking/notebooks/Finding page corners for several images.ipynb

Finding corners, tested on several images¶

It turns out the cosine_threshold is quite tricky, maybe it should be searched for as the lowest or a reasonably low veresion such that exactly two lines are found per corner. Also, it might help to force overlap of two out ofthree points when clusting points that lie on one line.

In [8]:

import sys
sys.path.append('..')
from pagelocalizer import find_corner_circles, cluster_circles_per_corner, intersection_per_corner, separate_lines, find_line_coefficients_per_corner
import numpy
import glob
import cv2

%matplotlib inline
from matplotlib import pyplot, rcParams

rcParams['figure.figsize'] = (20, 16)
rcParams['figure.dpi'] = '100'

In [10]:

for filename in ['../images/img2.jpg', '../images/img4.jpg']:
    im = cv2.imread(filename, cv2.IMREAD_COLOR)
    pyplot.figure()
    pyplot.imshow(im)
    
    keypoints = find_corner_circles(im,
        area=(5000 / 4, 5000 * 4),
        color=None,
        convexity=0.9,
        circularity=0.7,
        inertia=None,
        thresholdstep=1
    )
    keypoints, corner_circles = cluster_circles_per_corner(keypoints, distance_factor=1.5)
    for corner in corner_circles:
        pyplot.plot(*zip(*[keypoints[i].pt for i in corner]), 'o', markersize=12, fillstyle='none', markeredgewidth=2)
    
    lines_per_corner = find_line_coefficients_per_corner(
        keypoints, corner_circles,
        cosine_threshold=0.00137046524)
    xx = numpy.arange(0, im.shape[1]-1,0.25)
    for (a, b), (c, d) in lines_per_corner:
        pyplot.plot(xx, a*xx + b, linewidth=4)
        pyplot.plot(xx, c*xx + d, linewidth=4)
    
    corners, order = intersection_per_corner(lines_per_corner)
    polygon_corners = numpy.array([corners[i] for i in order] + [corners[order[0]]])

    pyplot.plot(*polygon_corners.T, 'r-', linewidth=4)
    pyplot.imshow(im)
    pyplot.axis('off')