def test_save_cell_images(tmp_path):
cells = segment_cells(locate_module_and_cells(datasets.poly10x6(1)[0]))
save_images(tmp_path, cells)
for cell in cells:
p = tmp_path / "{}_row{:02d}_col{:02d}{}".format(
cell.path.stem, cell.row, cell.col, cell.path.suffix)
img_read = read_module_image(p, EL_IMAGE)
def _prepare_stitching_test_img():
image = datasets.poly10x6(1)[0].data.T[:, :1930]
height = image.shape[0]
width = image.shape[1]
img0 = Image(image[600:, 0:int(width * 2 // 3)])
img1 = Image(image[600:, int(width // 3):])
return img0, img1
def test_save_images_filename_hook(tmp_path: Path):
cells = segment_cells(locate_module_and_cells(datasets.poly10x6(1)[0]))
hook = lambda x: "{}_{:02d}{:02d}{}".format(x.path.stem, x.row, x.col, x.
path.suffix)
save_images(tmp_path, cells)
for cell in cells:
p = tmp_path / "{}_{:02d}{:02d}{}".format(cell.path.stem, cell.row,
cell.col, cell.path.suffix)
# try read
img_read = read_module_image(p, EL_IMAGE)
def test_single_segmentation():
# load images
img = datasets.poly10x6(N=1)[0]
# perform detection
module = locate_module_and_cells(img)
# check result
assert module.has_meta("transform")
# check that show result does not fail
module.show()
# perform segmentation into cells
cells = segment_cells(module)
# check
assert len(cells) == 60
def test_save_and_read_image(tmp_path):
img = datasets.poly10x6(1)[0]
save_image(tmp_path / "img.tif", img)
img_read = read_module_image(tmp_path / "img.tif", EL_IMAGE)
assert np.linalg.norm(img.data.flatten() - img_read.data.flatten()) == 0
def test_save_image_with_visualization(tmp_path: Path):
img = datasets.poly10x6(1)[0]
p = tmp_path / "img.pdf"
save_image(p, img, with_visusalization=True)
assert p.is_file()
def test_save_image_sequence(tmp_path):
seq = datasets.poly10x6(5)
save_images(tmp_path, seq)
for img in seq:
img_read = read_module_image(tmp_path / img.path.name, EL_IMAGE)
