core\feat: #68 crowd_seg improvements

- improvements in data parsing
- improvements in sample visualization
- made retrieves submodule private

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.dev2"
+version = "0.1.3.dev3"
 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.dev2"
+version = "0.1.3.dev3"
 authors = ["Brandon Lotero <[email protected]>"]
 description = "A package for the SEG TGCE project"
 readme = "README.md"

core/seg_tgce/data/crowd_seg/__init__.py

@@ -3,14 +3,11 @@
 from .generator import ImageDataGenerator
 from .stage import Stage
 
-_DEFAULT_N_CLASSES = 6
-
 
 def get_all_data(
-    n_classes: int = _DEFAULT_N_CLASSES,
     image_size: Tuple[int, int] = (256, 256),
     batch_size: int = 32,
-    shuffle: bool = True,
+    shuffle: bool = False,
 ) -> Tuple[ImageDataGenerator, ...]:
     """
     Retrieve all data generators for the crowd segmentation task.
@@ -19,7 +16,6 @@ def get_all_data(
     return tuple(
         ImageDataGenerator(
             batch_size=batch_size,
-            n_classes=n_classes,
             image_size=image_size,
             shuffle=shuffle,
             stage=stage,
@@ -30,17 +26,15 @@ def get_all_data(
 
 def get_stage_data(
     stage: Stage,
-    n_classes: int = _DEFAULT_N_CLASSES,
     image_size: Tuple[int, int] = (256, 256),
     batch_size: int = 32,
-    shuffle: bool = True,
+    shuffle: bool = False,
 ) -> ImageDataGenerator:
     """
     Retrieve a data generator for a specific stage of the crowd segmentation task.
     """
     return ImageDataGenerator(
         batch_size=batch_size,
-        n_classes=n_classes,
         image_size=image_size,
         shuffle=shuffle,
         stage=stage,

core/seg_tgce/data/crowd_seg/__main__.py

@@ -3,13 +3,10 @@
 
 def main() -> None:
     train, val, test = get_all_data(batch_size=8)
-    val.visualize_sample(["NP8", "NP16", "NP21", "expert"])
+    val.visualize_sample(batch_index=138, sample_indexes=[2, 3, 4, 5])
     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()