def test_tif_series_2otsu_Y23(self):
frame_list = glob("./test_resources/Y23_0.4X_raw_tifs/*.tif")
for idx in range(400, 450):
frame = frame_list[idx]
self.image = np.array(Image.open(frame))
self.thresholds = otsu(self.image, nclasses=2)
if idx == 425:
# Plot intensity histogram and thresholds
plt.hist(self.image.flatten(), bins=256, log=True)
for t in self.thresholds:
plt.axvline(t, color='r')
plt.title('Y23 using class=2')
plt.draw()
plt.savefig('Y23_2-class.png', dpi=300)
plt.clf()
Image.open('Y23_2-class.png').show()
# Plot actual data and thresholded
edge = feature.canny(self.image > self.thresholds[0])
highlight = np.copy(self.image)
highlight[edge] = 2 * self.image.max() - self.image.min()
fig = plt.figure()
ax11 = fig.add_subplot(221)
ax12 = fig.add_subplot(222)
ax21 = fig.add_subplot(223)
ax22 = fig.add_subplot(224)
ax11.imshow(self.image)
ax12.imshow(self.image > self.thresholds[0])
ax21.imshow(highlight)
ax22.imshow(edge)
plt.show()
def test_tif_series_2otsu_Y23(self):
frame_list = glob("./test_resources/Y23_0.4X_raw_tifs/*.tif")
for idx in range(400,450):
frame = frame_list[idx]
self.image = np.array(Image.open(frame))
self.thresholds = otsu(self.image, nclasses=2)
if idx==425:
# Plot intensity histogram and thresholds
plt.hist(self.image.flatten(), bins=256, log=True)
for t in self.thresholds:
plt.axvline(t, color='r')
plt.title('Y23 using class=2')
plt.draw()
plt.savefig('Y23_2-class.png', dpi=300)
plt.clf()
Image.open('Y23_2-class.png').show()
# Plot actual data and thresholded
edge = feature.canny(self.image>self.thresholds[0])
highlight = np.copy(self.image)
highlight[edge] = 2*self.image.max() - self.image.min()
fig = plt.figure()
ax11 = fig.add_subplot(221)
ax12 = fig.add_subplot(222)
ax21 = fig.add_subplot(223)
ax22 = fig.add_subplot(224)
ax11.imshow(self.image)
ax12.imshow(self.image>self.thresholds[0])
ax21.imshow(highlight)
ax22.imshow(edge)
plt.show()
def test_three_class_otsu(self):
self.thresholds = otsu(self.image, nclasses=3)
logger.info("three-classes: {}".format(self.thresholds))
array2image(128 * (self.image > self.thresholds[0]) + 127 *
(self.image > self.thresholds[1])).show()
assert np.allclose(self.thresholds, (82.51953125, 145.01953125)), \
'Three-class Otsu threshold [{}] != {}'.format(
self.thresholds, (82.51953125, 145.01953125))
def test_two_class_otsu(self):
# run test one
self.thresholds = otsu(self.image)
logger.info("two-class: {}".format(self.thresholds))
array2image(255 * (self.image > self.thresholds[0])).show()
assert np.isclose(self.thresholds[0], 115.72265625), \
'Two-class Otsu threshold ({}) != {}'.format(
self.thresholds[0], 115.72265625)
def test_three_class_otsu(self):
self.thresholds = otsu(self.image, nclasses=3)
logger.info("three-classes: {}".format(self.thresholds))
array2image(128*(self.image > self.thresholds[0]) +
127*(self.image > self.thresholds[1])).show()
assert np.allclose(self.thresholds, (82.51953125, 145.01953125)), \
'Three-class Otsu threshold [{}] != {}'.format(
self.thresholds, (82.51953125, 145.01953125))
def test_two_class_otsu(self):
# run test one
self.thresholds = otsu(self.image)
logger.info("two-class: {}".format(self.thresholds))
array2image(255*(self.image > self.thresholds[0])).show()
assert np.isclose(self.thresholds[0], 115.72265625), \
'Two-class Otsu threshold ({}) != {}'.format(
self.thresholds[0], 115.72265625)
def test_four_class_otsu(self):
self.thresholds = otsu(self.image, nclasses=4)
logger.info("four-classes: {}".format(self.thresholds))
array2image(85 * (self.image > self.thresholds[0]) + 170 *
(self.image > self.thresholds[1]) + 255 *
(self.image > self.thresholds[2])).show()
assert np.allclose(self.thresholds, (68.84765625, 123.53515625, 168.45703125)), \
'Four-class Otsu threshold [{}] != {}'.format(
self.thresholds, (68.84765625, 123.53515625, 168.45703125))
def test_four_class_otsu(self):
self.thresholds = otsu(self.image, nclasses=4)
logger.info("four-classes: {}".format(self.thresholds))
array2image( 85*(self.image > self.thresholds[0]) +
170*(self.image > self.thresholds[1]) +
255*(self.image > self.thresholds[2])).show()
assert np.allclose(self.thresholds, (68.84765625, 123.53515625, 168.45703125)), \
'Four-class Otsu threshold [{}] != {}'.format(
self.thresholds, (68.84765625, 123.53515625, 168.45703125))
def test_tif_series_3otsu_M04(self):
frame_list = glob("./test_resources/M04_0.4X_raw_tifs/*.tif")
for idx in range(400, 450):
frame = frame_list[idx]
self.image = np.array(Image.open(frame))
self.thresholds = otsu(self.image, nclasses=3)
if idx == 425:
plt.hist(self.image.flatten(), bins=256, log=True)
for t in self.thresholds:
plt.axvline(t, color='r')
plt.title('M04 using class=3')
plt.draw()
plt.savefig('M04_3-class.png', dpi=300)
plt.clf()
Image.open('M04_3-class.png').show()
def test_tif_series_3otsu_M04(self):
frame_list = glob("./test_resources/M04_0.4X_raw_tifs/*.tif")
for idx in range(400,450):
frame = frame_list[idx]
self.image = np.array(Image.open(frame))
self.thresholds = otsu(self.image, nclasses=3)
if idx==425:
plt.hist(self.image.flatten(), bins=256, log=True)
for t in self.thresholds:
plt.axvline(t, color='r')
plt.title('M04 using class=3')
plt.draw()
plt.savefig('M04_3-class.png', dpi=300)
plt.clf()
Image.open('M04_3-class.png').show()