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reenabled tests that were accidentally disabled

This commit is contained in:
Guillaume Raffy 2020-03-12 17:09:03 +01:00
parent ac93fb411f
commit 76094378b9
1 changed files with 34 additions and 34 deletions
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68
tests/test0001.py
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@ -32,42 +32,42 @@ class TestLipase(unittest.TestCase):
print("uninitializing TestLipase instance")
self.catalog = None
# def test_estimate_white(self):
# sequence = self.catalog.sequences['res_soleil2018/GGH/GGH_2018_cin2_phiG_I_327_vis_-40_1/Pos2']
# white_estimator = WhiteEstimator(open_size=75, close_size=75, average_size=75)
# white_estimate = white_estimator.estimate_white([sequence], ['DM300_327-353_fluo'])
# # find_white_reference_image(white_estimate, sequence.get_white())
# print(white_estimate)
# IImageEngine.get_instance().debugger.on_image(white_estimate, 'white_estimate')
# # assert False, "hellooooo"
# print('end of test_estimate_white')
def test_estimate_white(self):
sequence = self.catalog.sequences['res_soleil2018/GGH/GGH_2018_cin2_phiG_I_327_vis_-40_1/Pos2']
white_estimator = WhiteEstimator(open_size=75, close_size=75, average_size=75)
white_estimate = white_estimator.estimate_white([sequence], ['DM300_327-353_fluo'])
# find_white_reference_image(white_estimate, sequence.get_white())
print(white_estimate)
IImageEngine.get_instance().debugger.on_image(white_estimate, 'white_estimate')
# assert False, "hellooooo"
print('end of test_estimate_white')
# def test_uniform_lighting_correction(self):
# non_uniform_sequence = self.catalog.sequences['res_soleil2018/GGH/GGH_2018_cin2_phiG_I_327_vis_-40_1/Pos0']
# uniform_sequence = correct_non_uniform_lighting(non_uniform_sequence, 'DM300_nofilter_vis', white_estimator=WhiteEstimator(open_size=75, close_size=75, average_size=75))
def test_uniform_lighting_correction(self):
non_uniform_sequence = self.catalog.sequences['res_soleil2018/GGH/GGH_2018_cin2_phiG_I_327_vis_-40_1/Pos0']
uniform_sequence = correct_non_uniform_lighting(non_uniform_sequence, 'DM300_nofilter_vis', white_estimator=WhiteEstimator(open_size=75, close_size=75, average_size=75)) # pylint: disable=unused-variable
# def test_template_matcher(self):
# sequence = self.catalog.sequences['res_soleil2018/GGH/GGH_2018_cin2_phiG_I_327_vis_-40_1/Pos0']
# stack = sequence.as_hyperstack(['DM300_nofilter_vis'], selected_frames=[0])
# first_image = stack.get_image(frame_index=0)
# x_min = 423
# x_max = 553
# y_min = 419
# y_max = 533
# template_trap_aabb = Aabb(x_min, y_min, x_max, y_max)
# template_trap_image = first_image.get_subimage(template_trap_aabb)
# for image in [first_image, template_trap_image]:
# print(image.get_pixel_type(), image.get_width(), image.get_height())
# # the typical value of peaks is -2.e10 and the value between peaks is below -8.0e10
# threshold = -3.0e10
# tolerance = 1.0e10
# maxima_finder = MaximaFinder(threshold, tolerance)
# template_matcher = TemplateMatcher(maxima_finder)
# matches = template_matcher.match_template(first_image, template_trap_image)
# num_traps = len(matches)
# print("number of traps found : %d" % num_traps)
# num_expected_traps = 13 # 13 traps are completely visible in the first image
# self.assertAlmostEqual(len(matches), num_expected_traps, delta=1.0)
def test_template_matcher(self):
sequence = self.catalog.sequences['res_soleil2018/GGH/GGH_2018_cin2_phiG_I_327_vis_-40_1/Pos0']
stack = sequence.as_hyperstack(['DM300_nofilter_vis'], selected_frames=[0])
first_image = stack.get_image(frame_index=0)
x_min = 423
x_max = 553
y_min = 419
y_max = 533
template_trap_aabb = Aabb(x_min, y_min, x_max, y_max)
template_trap_image = first_image.get_subimage(template_trap_aabb)
for image in [first_image, template_trap_image]:
print(image.get_pixel_type(), image.get_width(), image.get_height())
# the typical value of peaks is -2.e10 and the value between peaks is below -8.0e10
threshold = -3.0e10
tolerance = 1.0e10
maxima_finder = MaximaFinder(threshold, tolerance)
template_matcher = TemplateMatcher(maxima_finder)
matches = template_matcher.match_template(first_image, template_trap_image)
num_traps = len(matches)
print("number of traps found : %d" % num_traps)
num_expected_traps = 13 # 13 traps are completely visible in the first image
self.assertAlmostEqual(len(matches), num_expected_traps, delta=1.0)
def test_traps_detector(self):