def generate_probe_loc_image(norm_projection, probe_locs, imsave):
"""Generate an annotated image showing the probe locations as crosses."""
probe_loc_image = grayscale_to_rgb(norm_projection.image_array)
for coords in probe_locs:
x, y = coords
c = random_rgb()
draw_cross(probe_loc_image, x, y, c)
imsave('probe_locations.png', probe_loc_image)
def hough_stuff(imsave):
"""Deprecated. Template matching works better."""
thresh = threshold_otsu(edges, mult=1.5)
hough_radii = np.arange(1, 3, 1)
hough_res = skimage.transform.hough_circle(thresh.image_array, hough_radii)
hough_data = hough_res[0] + hough_res[1]
#loc_array = peak_local_max(hough_data, min_distance=5, threshold_rel=0.5)
cloc_array = peak_local_max(hough_data, min_distance=5, threshold_rel=0.5, indices=False)
imsave('cloc.png', cloc_array)
connected_components, n_cc = skimage.measure.label(cloc_array, neighbors=8, return_num=True)
labels = np.unique(connected_components)
annot = np.zeros((512, 512, 3), dtype=np.uint8)
annot[:,:] = 255, 255, 255
annot[np.where(thresh.image_array)] = [0, 0, 0]
def draw_cross(x, y, c):
for xo in np.arange(-4, 5, 1):
annot[x+xo, y] = c
for yo in np.arange(-4, 5, 1):
annot[x,y+yo] = c
probe_locs = []
for label in labels:
coord_list = zip(*np.where(connected_components == label))
probe_locs.append(coord_list[0])
for coords in probe_locs:
x, y = coords
c = random_rgb()
draw_cross(x, y, c)
imsave('probe_locations.png', annot)
#print '\n'.join(thresh.history)
return probe_locs
