def get_segmentation_mask_image(self, image_api=None):
if image_api is None:
image_api = ImageApi
segmentation_mask_image_file = self.get_segmentation_mask_image_file()
pixel_size = self.get_surface_2p_pixel_size_um()
segmentation_mask_image = mpimg.imread(segmentation_mask_image_file)
return ImageApi.serialize(segmentation_mask_image, [pixel_size / 1000., pixel_size / 1000.], 'mm')
def get_max_projection(self, image_api=None):
if image_api is None:
image_api = ImageApi
maxInt_a13_file = self.get_max_projection_file()
pixel_size = self.get_surface_2p_pixel_size_um()
max_projection = mpimg.imread(maxInt_a13_file)
return ImageApi.serialize(max_projection, [pixel_size / 1000., pixel_size / 1000.], 'mm')
def get_image(nwbfile: NWBFile, name: str, module: str) -> Image:
nwb_img = nwbfile.processing[module].get_data_interface('images')[name]
data = nwb_img.data
resolution = nwb_img.resolution # px/cm
spacing = [resolution * 10, resolution * 10]
img = ImageApi.serialize(data, spacing, 'mm')
img = ImageApi.deserialize(img=img)
return img
def get_average_projection(self, image_api=None):
if image_api is None:
image_api = ImageApi
avgint_a1X_file = (
self.extractor.get_average_intensity_projection_image_file())
pixel_size = self.extractor.get_surface_2p_pixel_size_um()
average_image = mpimg.imread(avgint_a1X_file)
return ImageApi.serialize(average_image, [pixel_size / 1000.,
pixel_size / 1000.], 'mm')
def get_image(self, name, module, image_api=None) -> sitk.Image:
if image_api is None:
image_api = ImageApi
nwb_img = self.nwbfile.modules[module].get_data_interface(
'images')[name]
data = nwb_img.data
resolution = nwb_img.resolution # px/cm
spacing = [resolution * 10, resolution * 10]
return ImageApi.serialize(data, spacing, 'mm')
def _from_filepath(filepath: str, pixel_size: float) -> Image:
"""
:param filepath
path to image
:param pixel_size
pixel size in um
"""
img = mpimg.imread(filepath)
img = ImageApi.serialize(img, [pixel_size / 1000., pixel_size / 1000.],
'mm')
img = ImageApi.deserialize(img=img)
return img
def get_max_projection(self):
return ImageApi.serialize(roi_1 + roi_2, [0.5, 1.], 'mm')
def get_segmentation_mask_image(self):
data = roi_1 #useless image data here
spacing = (1, 1)
unit = 'index'
return ImageApi.serialize(data, spacing, unit)
