def showIm(ims, fig=1, title='', showz=False):
""" Show image with nearest neighbor interpolation and axis scaling """
plt.figure(fig)
plt.clf()
if showz:
pmatlab.imshowz(ims, interpolation='nearest')
else:
plt.imshow(ims, interpolation='nearest')
plt.axis('image')
plt.title(title)
def _onedotGetBlobs(fimg, fig=None):
""" Extract blobs for a 2D scan of a one-dot """
# thr=otsu(fimg)
thr = np.median(fimg)
x = np.percentile(fimg, 99.5)
thr = thr + (x - thr) * .5
bim = 30 * (fimg > thr).astype(np.uint8)
xx = detect_blobs_binary(bim)
if int(cv2.__version__[0]) >= 3:
# opencv 3
ww, contours, tmp = cv2.findContours(bim.copy(), cv2.RETR_EXTERNAL,
cv2.CHAIN_APPROX_SIMPLE)
else:
contours, tmp = cv2.findContours(bim.copy(), cv2.RETR_EXTERNAL,
cv2.CHAIN_APPROX_SIMPLE)
qq = []
for ii in range(len(contours)):
qq += [weightedCentroid(fimg, contours, contourIdx=ii, fig=None)]
xxw = np.array(qq)
if fig is not None:
plt.figure(fig)
plt.clf()
pgeometry.imshowz(fimg, interpolation='nearest')
plt.axis('image')
plt.colorbar()
# ax = plt.gca()
pgeometry.plotPoints(xx.T, '.g', markersize=16, label='blob centres')
plt.title('Reponse image with detected blobs')
plt.figure(fig + 1)
plt.clf()
pgeometry.imshowz(bim, interpolation='nearest')
plt.axis('image')
plt.colorbar()
# ax = plt.gca()
pgeometry.plotPoints(xxw.T, '.g', markersize=16, label='blob centres')
pgeometry.plotPoints(xx.T,
'.m',
markersize=12,
label='blob centres (alternative)')
plt.title('Binary blobs')
pgeometry.tilefigs([fig, fig + 1], [2, 2])
return xxw, (xx, contours)