def test_edge_and_corners(self):
blob = Blob(self.blob_img_path, self.config)
edge_and_corners = blob._extract_edges_and_corners()
assert isinstance(edge_and_corners, np.ndarray)
assert edge_and_corners.shape == (220, 446)
assert edge_and_corners.sum() == 16360
def test_apply_phasecong(self):
blob = Blob(self.blob_img_path, self.config)
M, m = blob._apply_phasecong()
Mm = M + m
assert isinstance(Mm, np.ndarray)
assert Mm.shape == (220, 446)
assert np.isclose(Mm.sum(), 4603.975603416737)
def test_apply_closing(self):
blob = Blob(self.blob_img_path, self.config)
blob_img = blob._extract_edges_and_corners()
dark_img = blob._apply_dark_thresholding()
blob_img = blob_img | dark_img
closed = blob._apply_closing(blob_img)
assert isinstance(closed, np.ndarray)
assert closed.shape == (220, 446)
assert closed.sum() == 22199
def test_add_properties(self):
blob = Blob(self.blob_img_path, self.config)
assert blob.area == 21987
assert np.isclose(blob.equivalent_diameter, 167.31622118041042)
assert np.isclose(blob.major_axis_length, 274.93638304044634)
assert np.isclose(blob.eccentricity, 0.8355355954192663)
def test_bytes_load(self):
record = self.zipped_image.to_record(2)
img_str = base64.b64decode(record['image'])
blob = Blob(img_str, self.config)
assert isinstance(blob.img, np.ndarray)
assert blob.img.sum() == 3359800
assert blob.img.shape == (138, 176)
def test_distmap_volume(self):
blob = Blob(self.blob_img_path, self.config)
volume, x = biovolume.calc_distmap_volume(blob.blob_img)
assert isinstance(volume, float)
assert np.isclose(volume, 1087116.7156675349)
assert isinstance(x, float)
assert np.isclose(x, 62.96125906574407)
def test_fill_and_remove_small_holes(self):
blob = Blob(self.blob_img_path, self.config)
img_dark = blob._apply_dark_thresholding()
img_blob = blob._extract_edges_and_corners()
img_blob = img_blob | img_dark
img_blob = blob._apply_closing(img_blob)
img_blob = blob._apply_dilation(img_blob)
thinned = blob._apply_morph_thinning(img_blob)
img = blob._fill_and_remove_holes(thinned)
assert isinstance(img, np.ndarray)
assert img.shape == (220, 446)
assert img.sum() == 21987
def test_apply_morph_thinning(self):
blob = Blob(self.blob_img_path, self.config)
img_dark = blob._apply_dark_thresholding()
img_blob = blob._extract_edges_and_corners()
img_blob = img_blob | img_dark
img_blob = blob._apply_closing(img_blob)
img_blob = blob._apply_dilation(img_blob)
thinned = blob._apply_morph_thinning(img_blob)
assert isinstance(thinned, np.ndarray)
assert thinned.shape == (220, 446)
assert thinned.sum() == 21013
def test_path_load(self):
blob = Blob(self.img_path, self.config)
assert isinstance(blob.img, np.ndarray)
assert blob.img.sum() == 3359800
assert blob.img.shape == (138, 176)
def test_blob(self):
blob = Blob(self.blob_img_path, self.config)
assert isinstance(blob.blob_img, np.ndarray)
assert blob.blob_img.shape == (220, 446)
assert blob.blob_img.sum() == 21987
def test_volume(self):
blob = Blob(self.blob_img_path, self.config)
volume = biovolume.calc_biovolume(blob)
assert isinstance(volume, float)
assert np.isclose(volume, 1087116.7156675349)
def test_sor_volume(self):
blob = Blob(self.blob_img_path, self.config)
sor_volume = biovolume.calc_sor_volume(blob.blob_img)
assert isinstance(sor_volume, float)
assert np.isclose(sor_volume, 2131048.325682015)