def do_stage(self, image):
master_calibration_filename = self.get_calibration_filename(image)
if master_calibration_filename is None:
self.on_missing_master_calibration(image)
return image
master_calibration_image = FRAME_CLASS(
self.runtime_context, filename=master_calibration_filename)
try:
image_utils.check_image_homogeneity(
[image, master_calibration_image],
self.master_selection_criteria)
except image_utils.InhomogeneousSetException as e:
logger.error(
'Master calibration was not the same format as the input: {0}'.
format(e),
image=image,
extra_tags={
'master_calibration':
os.path.basename(master_calibration_filename)
})
return None
logger.info('Applying master calibration',
image=image,
extra_tags={
'master_calibration':
os.path.basename(master_calibration_filename)
})
return self.apply_master_calibration(image, master_calibration_image)
def throws_inhomogeneous_set_exception(image1,
image2,
keyword,
additional_group_by_attributes=None):
with pytest.raises(
image_utils.InhomogeneousSetException) as exception_info:
image_utils.check_image_homogeneity([image1, image2],
additional_group_by_attributes)
assert 'Images have different {0}s'.format(keyword) == str(
exception_info.value)
def do_stage(self, image):
master_calibration_filename = self.get_calibration_filename(image)
if master_calibration_filename is None:
self.on_missing_master_calibration(image)
return image
master_calibration_image = FRAME_CLASS(self.runtime_context, filename=master_calibration_filename)
try:
image_utils.check_image_homogeneity([image, master_calibration_image], self.master_selection_criteria)
except image_utils.InhomogeneousSetException:
logger.error(logs.format_exception(), image=image)
return None
return self.apply_master_calibration(image, master_calibration_image)
def do_stage(self, images):
if len(images) < self.min_images:
# Do nothing
self.logger.warning('Not enough images to combine.')
return []
else:
image_config = image_utils.check_image_homogeneity(images)
logging_tags = logs.image_config_to_tags(image_config, self.group_by_keywords)
return self.make_master_calibration_frame(images, image_config, logging_tags)
def do_stage(self, images):
if len(images) < self.min_images:
# Do nothing
self.logger.warning('Not enough images to combine.')
return []
else:
image_config = image_utils.check_image_homogeneity(images)
logging_tags = logs.image_config_to_tags(image_config, self.group_by_keywords)
return self.make_master_calibration_frame(images, image_config, logging_tags)
def do_stage(self, images):
try:
min_images = settings.CALIBRATION_MIN_FRAMES[self.calibration_type.upper()]
except KeyError:
msg = 'The minimum number of frames required to create a master calibration of type ' \
'{calibration_type} has not been specified in the settings.'
logger.error(msg.format(calibration_type=self.calibration_type.upper()))
return []
if len(images) < min_images:
# Do nothing
msg = 'Number of images less than minimum requirement of {min_images}, not combining'
logger.warning(msg.format(min_images=min_images))
return []
try:
image_utils.check_image_homogeneity(images, self.group_by_attributes())
except image_utils.InhomogeneousSetException:
logger.error(logs.format_exception())
return []
return [self.make_master_calibration_frame(images)]
def do_stage(self, images):
try:
min_images = settings.CALIBRATION_MIN_FRAMES[
self.calibration_type.upper()]
except KeyError:
msg = 'The minimum number of frames required to create a master calibration of type ' \
'{calibration_type} has not been specified in the settings.'
logger.error(
msg.format(calibration_type=self.calibration_type.upper()))
return []
if len(images) < min_images:
# Do nothing
msg = 'Number of images less than minimum requirement of {min_images}, not combining'
logger.warning(msg.format(min_images=min_images))
return []
try:
image_utils.check_image_homogeneity(images,
self.group_by_attributes())
except image_utils.InhomogeneousSetException:
logger.error(logs.format_exception())
return []
return [self.make_master_calibration_frame(images)]
def do_stage(self, images):
if len(images) == 0:
# Abort!
return []
else:
image_config = image_utils.check_image_homogeneity(images)
logging_tags = logs.image_config_to_tags(image_config, self.group_by_keywords)
master_calibration_filename = self.get_calibration_filename(images[0])
if master_calibration_filename is None:
self.logger.error('Master Calibration file does not exist for {stage}'.format(stage=self.stage_name),
extra=logging_tags)
raise MasterCalibrationDoesNotExist
master_calibration_image = Image(self.pipeline_context,
filename=master_calibration_filename)
return self.apply_master_calibration(images, master_calibration_image, logging_tags)
def do_stage(self, images):
if len(images) == 0:
# Abort!
return []
else:
image_config = image_utils.check_image_homogeneity(images)
logging_tags = logs.image_config_to_tags(image_config, self.group_by_keywords)
master_calibration_filename = self.get_calibration_filename(images[0])
if master_calibration_filename is None:
self.logger.error('Master Calibration file does not exist for {stage}'.format(stage=self.stage_name),
extra=logging_tags)
raise MasterCalibrationDoesNotExist
master_calibration_image = Image(self.pipeline_context,
filename=master_calibration_filename)
return self.apply_master_calibration(images, master_calibration_image, logging_tags)
def throws_inhomogeneous_set_exception(image1, image2, keyword, additional_group_by_attributes=None):
with pytest.raises(image_utils.InhomogeneousSetException) as exception_info:
image_utils.check_image_homogeneity([image1, image2], additional_group_by_attributes)
assert 'Images have different {0}s'.format(keyword) == str(exception_info.value)