Fix batch augmentations for p=0

luxonis_ml/data/augmentations/batch_compose.py

@@ -47,6 +47,9 @@ def __call__(
             for batch in yield_batches(data_batch, transform.batch_size):
                 data = transform(**batch)  # type: ignore
 
+                if isinstance(next(iter(data.values())), list):
+                    data = {key: value[0] for key, value in batch.items()}
+
                 data = self.check_data_post_transform(data)
                 new_batch.append(data)
             data_batch = new_batch

luxonis_ml/data/augmentations/utils.py

@@ -1,4 +1,4 @@
-from typing import Any, Dict, Iterator, List, Tuple
+from typing import Dict, Iterator, List, Tuple, TypeVar
 
 import numpy as np
 
@@ -66,9 +66,12 @@ def postprocess_keypoints(
     return keypoints
 
 
+T = TypeVar("T")
+
+
 def yield_batches(
-    data_batch: List[Dict[str, Any]], batch_size: int
-) -> Iterator[Dict[str, List[Any]]]:
+    data_batch: List[Dict[str, T]], batch_size: int
+) -> Iterator[Dict[str, List[T]]]:
     """Yield batches of data.
 
     @type data_batch: List[Dict[str, Any]]

tests/test_data/test_augmentations/test_batched.py

@@ -61,3 +61,17 @@ def test_mixup(
     config = [{"name": "MixUp", "params": {"p": 1.0}}]
     augmentations = AlbumentationsEngine(256, 256, targets, config)
     augmentations.apply([(image.copy(), deepcopy(labels)) for _ in range(2)])
+
+
+def test_batched_p_0(
+    image: np.ndarray, labels: Labels, targets: Dict[str, TaskType]
+):
+    config = [
+        {
+            "name": "Mosaic4",
+            "params": {"p": 0, "out_width": 640, "out_height": 640},
+        },
+        {"name": "MixUp", "params": {"p": 0}},
+    ]
+    augmentations = AlbumentationsEngine(256, 256, targets, config)
+    augmentations.apply([(image.copy(), deepcopy(labels)) for _ in range(8)])