fix: 🎨 Make datasplit from csv consistent with DaCapo convention

src/cellmap_data/datasplit.py

@@ -1,4 +1,5 @@
 import csv
+import os
 from typing import Callable, Dict, Iterable, Mapping, Optional, Sequence
 import tensorstore
 from .dataset import CellMapDataset
@@ -27,7 +28,6 @@ class CellMapDataSplit:
     force_has_data: bool = False
     context: Optional[tensorstore.Context] = None  # type: ignore
 
-    # TODO: may want different transforms for different arrays
     def __init__(
         self,
         input_arrays: dict[str, dict[str, Sequence[int | float]]],
@@ -116,7 +116,12 @@ def from_csv(self, csv_path):
             for row in reader:
                 if row[0] not in dataset_dict:
                     dataset_dict[row[0]] = []
-                dataset_dict[row[0]].append({"raw": row[1], "gt": row[2]})
+                dataset_dict[row[0]].append(
+                    {
+                        "raw": os.path.join(row[1], row[2]),
+                        "gt": os.path.join(row[3], row[4]),
+                    }
+                )
 
         self.dataset_dict = dataset_dict
         self.construct(dataset_dict)

src/cellmap_data/image.py

@@ -31,6 +31,7 @@ def __init__(
         target_voxel_shape: Sequence[int],
         axis_order: str | Sequence[str] = "zyx",
         value_transform: Optional[Callable] = None,
+        # TODO: Add global grid enforcement to ensure that all images are on the same grid
         context: Optional[tensorstore.Context] = None,  # type: ignore
     ):
         """Initializes a CellMapImage object.
@@ -98,6 +99,7 @@ def to(self, device: str) -> None:
         """Sets what device returned image data will be loaded onto."""
         self.device = device
 
+    # TODO: move into __init__
     def construct(self):
         self._bounding_box = None
         self._sampling_box = None