def _evaluateImage(self):
signalImage = self._signalImage
contrastImage = self._signalImage if self._contrastImage is None else self._contrastImage
spot_size = contrastImage.shape[0] * _rel_spot_size
spots = detectSpots(contrastImage, spot_size).astype(float)
# Rescale the coordinates and radii of the spots since 'contrastImage' might have another resolution than 'signalImage'.
spots[:, 0] *= signalImage.shape[0] / contrastImage.shape[0]
spots[:, 1] *= signalImage.shape[1] / contrastImage.shape[1]
spots[:, 2] *= signalImage.shape[1] / contrastImage.shape[1]
spots = np.round(spots)
spots = spots.astype(int)
self._spots = spots
self._values = measure_raw(signalImage, self._spots)
def _evaluateImage(self): signalImage = self._signalImage contrastImage = self._signalImage if self._contrastImage is None else self._contrastImage spot_size = contrastImage.shape[0] * _rel_spot_size spots = detectSpots(contrastImage, spot_size).astype(float) # Rescale the coordinates and radii of the spots since 'contrastImage' might have another resolution than 'signalImage'. spots[:,0] *= signalImage.shape[0]/contrastImage.shape[0] spots[:,1] *= signalImage.shape[1]/contrastImage.shape[1] spots[:,2] *= signalImage.shape[1]/contrastImage.shape[1] spots = np.round(spots) spots = spots.astype(int) self._spots = spots self._values = measure_raw(signalImage, self._spots)
else:
if (not os.path.isfile(args["image"])):
print("not a file")
exit()
# read image as grayscale
image = imread(args["image"], as_grey=True)
#image = rescale(image, scale=0.5)
# remove noise
#image = gaussian_filter(image, 1)
inspectionMask = np.zeros(image.shape)
spot_size = image.shape[0] * 0.05
locations = detectSpots(image, spot_size)
rawValues = measure_raw(image, locations, inspectionMask=inspectionMask)
values = [v.mean for v in rawValues]
stdDevs = [v.std for v in rawValues]
print("raw measurement: ", rawValues)
# plot results
fig, ((ax1, ax2), (ax3, ax4)) = plt.subplots(2, 2, figsize=(8, 4.5))
ax1.imshow(image, cmap='gray')
ax1.set_title('Original')
ax2.imshow(image, cmap='gray')
else:
if(not os.path.isfile(args["image"])):
print("not a file")
exit()
# read image as grayscale
image = imread(args["image"], as_grey=True)
#image = rescale(image, scale=0.5)
# remove noise
#image = gaussian_filter(image, 1)
inspectionMask = np.zeros(image.shape)
spot_size=image.shape[0] * 0.05
locations = detectSpots(image, spot_size)
rawValues = measure_raw(image, locations, inspectionMask=inspectionMask)
values = [v.mean for v in rawValues]
stdDevs = [v.std for v in rawValues]
print("raw measurement: ", rawValues)
# plot results
fig, ((ax1, ax2), (ax3, ax4)) = plt.subplots(2, 2, figsize=(8, 4.5))
ax1.imshow(image, cmap='gray')
ax1.set_title('Original')
ax2.imshow(image, cmap='gray')
