74 lines
2.0 KiB
Python
74 lines
2.0 KiB
Python
|
from scipy import ndimage
|
||
|
|
import math
|
||
|
|
import matplotlib.pyplot as plt
|
||
|
|
from skimage import filters
|
||
|
|
import numpy as np
|
||
|
|
from skimage import feature
|
||
|
|
|
||
|
|
img = ndimage.imread("/home/tpolgrabia/Pobrane/CSFID/tracks_cropped/00003.jpg")
|
||
|
|
otsu_lvl = filters.threshold_otsu(img)
|
||
|
|
img_mask = img >= otsu_lvl
|
||
|
|
img_mask_fil = True ^ ndimage.minimum_filter(img_mask, 3)
|
||
|
|
img_label, nb_labels = ndimage.label(img_mask_fil)
|
||
|
|
sizes = ndimage.sum(img_mask_fil, img_label, range(0, nb_labels+1))
|
||
|
|
remove_labels = sizes < 100
|
||
|
|
lbls = True & remove_labels
|
||
|
|
lbls[0] = False
|
||
|
|
|
||
|
|
print("Remove labels: {}".format(ndimage.sum(remove_labels)))
|
||
|
|
|
||
|
|
remove_mask = remove_labels[img_label]
|
||
|
|
img_label[remove_mask] = 0
|
||
|
|
|
||
|
|
idx = 0
|
||
|
|
n2 = nb_labels + 1 - np.sum(remove_labels)
|
||
|
|
centers = np.zeros((nb_labels+1,2))
|
||
|
|
(n,m) = img.shape
|
||
|
|
corners = np.zeros((n,m), dtype=np.bool)
|
||
|
|
|
||
|
|
for i in range(0, nb_labels+1):
|
||
|
|
if remove_labels[i]:
|
||
|
|
continue
|
||
|
|
|
||
|
|
seg = img_label == i
|
||
|
|
slice_y, slice_x = ndimage.find_objects(seg)[0]
|
||
|
|
seg_window = seg[slice_y, slice_x]
|
||
|
|
edge = feature.canny(seg_window)
|
||
|
|
plt.imshow(edge, cmap="Greys_r")
|
||
|
|
plt.show()
|
||
|
|
(en,em) = edge.shape
|
||
|
|
distances = np.zeros((en,em))
|
||
|
|
|
||
|
|
centers[idx,:] = ndimage.center_of_mass(seg)
|
||
|
|
for j in range(0, en):
|
||
|
|
for k in range(0, em):
|
||
|
|
if edge[j,k]:
|
||
|
|
diff = centers[i,:] - np.array([slice_y.start, slice_x.start])
|
||
|
|
dx = k - diff[1]
|
||
|
|
dy = j - diff[0]
|
||
|
|
d = math.sqrt(dx*dx+dy*dy)
|
||
|
|
distances[j,k] = d
|
||
|
|
# max_distances = ndimage.maximum_filter(distances, 20)
|
||
|
|
# t_corners = np.abs(max_distances - distances) < 1e-6
|
||
|
|
# print(t_corners)
|
||
|
|
# plt.imshow(t_corners, cmap="Greys_r")
|
||
|
|
# plt.show()
|
||
|
|
# corners[slice_y,slice_x] = corners[slice_y,slice_x] + edge
|
||
|
|
|
||
|
|
idx += 1
|
||
|
|
|
||
|
|
(n,m) = img.shape
|
||
|
|
|
||
|
|
mx = np.tile(np.arange(0,m),n).reshape((n,m))
|
||
|
|
my = np.tile(np.arange(0,n),m).reshape((m,n)).T
|
||
|
|
xs2 = mx[corners]
|
||
|
|
ys2 = my[corners]
|
||
|
|
|
||
|
|
xs = centers[:,1]
|
||
|
|
ys = centers[:,0]
|
||
|
|
|
||
|
|
plt.imshow(img_label, cmap="Greys_r")
|
||
|
|
# plt.plot(xs, ys, "r+")
|
||
|
|
plt.plot(xs2,ys2,"b+")
|
||
|
|
plt.show()
|