steinbock.utils
matching
match_masks(mask1, mask2)
Source code in steinbock/utils/matching.py
def match_masks(mask1: np.ndarray, mask2: np.ndarray) -> pd.DataFrame:
nz1 = mask1 != 0
nz2 = mask2 != 0
object_ids1 = []
object_ids2 = []
for object_id1 in np.unique(mask1[nz1]):
for object_id2 in np.unique(mask2[nz2 & (mask1 == object_id1)]):
object_ids1.append(object_id1)
object_ids2.append(object_id2)
for object_id2 in np.unique(mask2[nz2]):
for object_id1 in np.unique(mask1[nz1 & (mask2 == object_id2)]):
object_ids1.append(object_id1)
object_ids2.append(object_id2)
df = pd.DataFrame(data={"Object1": object_ids1, "Object2": object_ids2})
df.drop_duplicates(inplace=True, ignore_index=True)
return df
try_match_masks_from_disk(mask_files1, mask_files2)
Source code in steinbock/utils/matching.py
def try_match_masks_from_disk(
mask_files1: Sequence[Union[str, PathLike]],
mask_files2: Sequence[Union[str, PathLike]],
) -> Generator[Tuple[Path, Path, pd.DataFrame], None, None]:
for mask_file1, mask_file2 in zip(mask_files1, mask_files2):
try:
df = match_masks(
io.read_mask(mask_file1), io.read_mask(mask_file2)
)
yield mask_file1, mask_file2, df
del df
except:
_logger.exception(f"Error matching masks {mask_file1, mask_file2}")
mosaics
TileInfo
try_extract_tiles_from_disk(img_files, tile_size)
Source code in steinbock/utils/mosaics.py
def try_extract_tiles_from_disk(
img_files: Sequence[Union[str, PathLike]], tile_size: int
) -> Generator[Tuple[Path, int, int, np.ndarray], None, None]:
for img_file in img_files:
try:
img = io.read_image(img_file, native_dtype=True)
for tile_x in range(0, img.shape[2], tile_size):
for tile_y in range(0, img.shape[1], tile_size):
tile = img[
:,
tile_y : (tile_y + tile_size),
tile_x : (tile_x + tile_size),
]
yield Path(img_file), tile_x, tile_y, tile
del tile
del img
except:
_logger.exception(f"Error extracting tiles: {img_file}")
try_stitch_tiles_from_disk(img_tile_infos)
Source code in steinbock/utils/mosaics.py
def try_stitch_tiles_from_disk(
img_tile_infos: Dict[str, Sequence[TileInfo]]
) -> Generator[Tuple[str, np.ndarray], None, None]:
for img_stem_name, tile_infos in img_tile_infos.items():
try:
tile_file, tile_x, tile_y, tile_width, tile_height = tile_infos[0]
tile = io.read_image(tile_file, native_dtype=True)
img = np.zeros(
(
tile.shape[0],
max(x + w for _, x, y, w, h in tile_infos),
max(y + h for _, x, y, w, h in tile_infos),
),
dtype=tile.dtype,
)
img[
:,
tile_y : (tile_y + tile_height),
tile_x : (tile_x + tile_width),
] = tile
for (
tile_file,
tile_x,
tile_y,
tile_width,
tile_height,
) in tile_infos[1:]:
img[
:,
tile_y : (tile_y + tile_height),
tile_x : (tile_x + tile_width),
] = io.read_image(tile_file, native_dtype=True)
yield img_stem_name, img
del img
except:
_logger.exception(f"Error stitching tiles: {img_stem_name}")