diff --git a/src/agora/io/metadata.py b/src/agora/io/metadata.py
index cc047cc6afc3f6ee0124a2989c5febf4aae4760e..025075024756d98ba907ddfbe753dc0946dad286 100644
--- a/src/agora/io/metadata.py
+++ b/src/agora/io/metadata.py
@@ -205,4 +205,47 @@ def dispatch_metadata_parser(filepath: t.Union[str, PosixPath]):
"""
parsed_meta = parse_swainlab_metadata(filepath)
+ if parsed_meta is None:
+ parsed_meta = dir_to_meta
+
return parsed_meta
+
+
+def dir_to_meta(path: PosixPath, suffix="tiff"):
+ filenames = list(path.glob(f"*.{suffix}"))
+
+ try:
+ # Deduct order from filenames
+ dimorder = "".join(
+ map(lambda x: x[0], filenames[0].stem.split("_")[1:])
+ )
+
+ dim_value = list(
+ map(
+ lambda f: filename_to_dict_indices(f.stem),
+ path.glob("*.tiff"),
+ )
+ )
+ maxes = [max(map(lambda x: x[dim], dim_value)) for dim in dimorder]
+ mins = [min(map(lambda x: x[dim], dim_value)) for dim in dimorder]
+ _dim_shapes = [
+ max_val - min_val + 1 for max_val, min_val in zip(maxes, mins)
+ ]
+
+ meta = {
+ "size_" + dim: shape for dim, shape in zip(dimorder, _dim_shapes)
+ }
+ except Exception as e:
+ print(
+ f"Warning:Metadata: Cannot extract dimensions from filenames. Empty meta set {e}"
+ )
+ meta = {}
+
+ return meta
+
+
+def filename_to_dict_indices(stem: str):
+ return {
+ dim_number[0]: int(dim_number[1:])
+ for dim_number in stem.split("_")[1:]
+ }
diff --git a/src/aliby/io/image.py b/src/aliby/io/image.py
index 290d5d80bf6211981743bdfefc7c28e9647bef68..2f6132d59aa797aa9740883d1a906fdde750603d 100644
--- a/src/aliby/io/image.py
+++ b/src/aliby/io/image.py
@@ -14,6 +14,7 @@ from omero.model import enums as omero_enums
from tifffile import TiffFile
from yaml import safe_load
+from agora.io.metadata import dir_to_meta
from aliby.io.omero import BridgeOmero
# convert OMERO definitions into numpy types
@@ -59,6 +60,23 @@ class BaseLocalImage:
def __enter__(self):
return self
+ def format_data(self, img):
+
+ self._formatted_img = da.rechunk(
+ img,
+ chunks=(
+ 1,
+ 1,
+ 1,
+ *[self._meta[f"size_{n}"] for n in self.dimorder[-2:]],
+ ),
+ )
+ return self._formatted_img
+
+ @property
+ def data(self):
+ return self.get_data_lazy()
+
class ImageLocal(BaseLocalImage):
def __init__(self, path: str, dimorder=None):
@@ -80,14 +98,13 @@ class ImageLocal(BaseLocalImage):
meta["name"] = self.meta["Image"]["@Name"]
meta["type"] = self.meta["Image"]["Pixels"]["@Type"]
- except Exception as e:
- print("Metadata not found: {}".format(e))
- assert (
- self.dimorder or self.meta.get("dims") is not None
- ), "No dimensional info provided."
+ except Exception as e: # Images not in OMEXML
+ base = "TCZXY"
+
+ print("Warning:Metadata not found: {}".format(e))
+ print(f"Warning: No dimensional info provided. Assuming {base}")
# Mark non-existent dimensions for padding
- base = "TCZXY"
self.base = base
self.ids = [base.index(i) for i in dimorder]
@@ -169,21 +186,10 @@ class ImageLocal(BaseLocalImage):
return self.format_data(img)
- def format_data(self, img):
-
- self._formatted_img = da.rechunk(
- img,
- chunks=(
- 1,
- 1,
- 1,
- *[self._meta[f"size_{n}"] for n in self.dimorder[-2:]],
- ),
- )
- return self._formatted_img
+ # TODO continue here. Ensure _dim_values are generated, or called from _meta
-class ImageDir(ImageLocal):
+class ImageDir(BaseLocalImage):
"""
Image class for the case in which all images are split in one or
multiple folders with time-points and channels as independent files.
@@ -200,36 +206,7 @@ class ImageDir(ImageLocal):
super().__init__(path)
self.image_id = str(self.path.stem)
- filenames = list(self.path.glob("*.tiff"))
-
- # Deduct order from filenames
- self.dimorder = "".join(
- map(lambda x: x[0], filenames[0].stem.split("_")[1:])
- )
-
- dim_value = list(
- map(
- lambda f: filename_to_dict_indices(f.stem),
- self.path.glob("*.tiff"),
- )
- )
- maxes = [
- max(map(lambda x: x[dim], dim_value)) for dim in self.dimorder
- ]
- mins = [min(map(lambda x: x[dim], dim_value)) for dim in self.dimorder]
- self._dim_shapes = [
- max_val - min_val + 1 for max_val, min_val in zip(maxes, mins)
- ]
-
- # Set internal metadata from shape and channel order
- self.dimorder += "xy"
-
- # Use images to redefine axes
-
- self._meta = {
- "size_" + dim: shape
- for dim, shape in zip(self.dimorder, self._dim_shapes)
- }
+ self._meta = dir_to_meta(self.path)
def get_data_lazy(self) -> da.Array:
"""Return 5D dask array. For lazy-loading local multidimensional tiff files"""
@@ -237,12 +214,16 @@ class ImageDir(ImageLocal):
img = imread(str(self.path / "*.tiff"))
# If extra channels, pick the first stack of the last dimensions
+
+ pixels = img
while len(img.shape) > 3:
img = img[..., 0]
- self._meta["size_x"], self._meta["size_y"] = img.shape[-2:]
+ if self._meta:
+ self._meta["size_x"], self._meta["size_y"] = img.shape[-2:]
- img = da.reshape(img, (*self._dim_shapes, *img.shape[1:]))
- return self.format_data(img)
+ img = da.reshape(img, (*self._dim_values(), *img.shape[1:]))
+ pixels = self.format_data(img)
+ return pixels
class Image(BridgeOmero):
@@ -351,37 +332,3 @@ class UnsafeImage(Image):
except Exception as e:
print(f"ERROR: Failed fetching image from server: {e}")
self.conn.connect(False)
-
-
-def get_data_lazy(image) -> da.Array:
- """
- Get 5D dask array, with delayed reading from OMERO image.
- """
- nt, nc, nz, ny, nx = [getattr(image, f"getSize{x}")() for x in "TCZYX"]
- pixels = image.getPrimaryPixels()
- dtype = PIXEL_TYPES.get(pixels.getPixelsType().value, None)
- # using dask
- get_plane = delayed(lambda idx: pixels.getPlane(*idx))
-
- def get_lazy_plane(zct):
- return da.from_delayed(get_plane(zct), shape=(ny, nx), dtype=dtype)
-
- # 5D stack: TCZXY
- t_stacks = []
- for t in range(nt):
- c_stacks = []
- for c in range(nc):
- z_stack = []
- for z in range(nz):
- z_stack.append(get_lazy_plane((z, c, t)))
- c_stacks.append(da.stack(z_stack))
- t_stacks.append(da.stack(c_stacks))
-
- return da.stack(t_stacks)
-
-
-def filename_to_dict_indices(stem: str):
- return {
- dim_number[0]: int(dim_number[1:])
- for dim_number in stem.split("_")[1:]
- }