core\refac: #40 standard shape for crowd seg

- delivered masks as the standard shape for crowd seg data

core/pyproject.toml

@@ -1,7 +1,7 @@
 [project]
 description = "Framework for handling image segmentation in the context of multiple annotators"
 name = "seg_tgce"
-version = "0.1.3"
+version = "0.1.3.dev1"
 readme = "README.md"
 authors = [{ name = "Brandon Lotero", email = "[email protected]" }]
 maintainers = [{ name = "Brandon Lotero", email = "[email protected]" }]
@@ -15,7 +15,7 @@ Issues = "https://github.com/blotero/seg_tgce/issues"
 
 [tool.poetry]
 name = "seg_tgce"
-version = "0.1.3"
+version = "0.1.3.dev1"
 authors = ["Brandon Lotero <[email protected]>"]
 description = "A package for the SEG TGCE project"
 readme = "README.md"

core/seg_tgce/data/crowd_seg/__main__.py

@@ -2,11 +2,14 @@
 
 
 def main() -> None:
-    train, val, test = get_all_data()
+    train, val, test = get_all_data(batch_size=8)
     val.visualize_sample(["NP8", "NP16", "NP21", "expert"])
     print(f"Train: {len(train)}")
     print(f"Val: {len(val)}")
     print(f"Test: {len(test)}")
+    img, mask = train[0]
+    print(f"Images shape: {img.shape}")
+    print(f"Masks shape: {mask.shape}")
 
 
 main()

core/seg_tgce/data/crowd_seg/generator.py

@@ -6,6 +6,7 @@
 from keras.preprocessing.image import img_to_array, load_img
 from keras.utils import Sequence
 from matplotlib import pyplot as plt
+from tensorflow import transpose
 
 from .retrieve import fetch_data, get_masks_dir, get_patches_dir
 from .stage import Stage
@@ -15,11 +16,20 @@
 
 
 class CustomPath(TypedDict):
+    """Custom path for image and mask directories."""
+
     image_dir: str
     mask_dir: str
 
 
 class ImageDataGenerator(Sequence):  # pylint: disable=too-many-instance-attributes
+    """
+    Data generator for crowd segmentation data.
+    Delivered data is in the form of images and masks.
+    Shapes are as follows:
+    - images: (batch_size, image_size[0], image_size[1], 3)
+    - masks: (batch_size, image_size[0], image_size[1]), n_classes, n_scorers"""
+
     def __init__(  # pylint: disable=too-many-arguments
         self,
         n_classes: int,
@@ -81,7 +91,7 @@ def visualize_sample(
             for class_num in range(self.n_classes):
                 axes[scorer_num][0].imshow(images[sample_index].astype(int))
                 axes[scorer_num][class_num + 1].imshow(
-                    masks[sample_index, scorer_num, class_num]
+                    masks[sample_index, :, :, class_num, scorer_num]
                 )
                 axes[scorer_num][0].axis("off")
                 axes[scorer_num][class_num + 1].axis("off")
@@ -135,4 +145,4 @@ def __data_generation(self, batch_filenames):
 
             images[batch] = image
 
-        return images, masks
+        return images, transpose(masks, perm=[0, 3, 4, 2, 1])