@@ -1,5 +1,5 @@
 from super_gradients.common.factories.base_factory import BaseFactory
-from super_gradients.training.utils.bbox_formats import BBOX_FORMATS
+from super_gradients.training.datasets.data_formats.bbox_formats import BBOX_FORMATS
 
 
 class BBoxFormatFactory(BaseFactory):

from super_gradients.common.factories.type_factory import TypeFactory
from super_gradients.training.datasets.data_formats.default_formats import DEFAULT_CONCATENATED_TENSOR_FORMATS


class ConcatenatedTensorFormatFactory(TypeFactory):
    def __init__(self):
        super().__init__(DEFAULT_CONCATENATED_TENSOR_FORMATS)

@@ -50,7 +50,6 @@ class Transforms:
     DetectionHSV = "DetectionHSV"
     DetectionHorizontalFlip = "DetectionHorizontalFlip"
     DetectionPaddedRescale = "DetectionPaddedRescale"
-    DetectionTargetsFormat = "DetectionTargetsFormat"
     DetectionTargetsFormatTransform = "DetectionTargetsFormatTransform"
     RandomResizedCropAndInterpolation = "RandomResizedCropAndInterpolation"
     RandAugmentTransform = "RandAugmentTransform"
@@ -253,3 +252,18 @@ class Models:
     PP_LITE_B_SEG75 = "pp_lite_b_seg75"
     UNET_CUSTOM = "unet_custom"
     UNET_CUSTOM_CLS = "unet_custom_cls"
+
+
+class ConcatenatedTensorFormats:
+    XYXY_LABEL = "XYXY_LABEL"
+    XYWH_LABEL = "XYWH_LABEL"
+    CXCYWH_LABEL = "CXCYWH_LABEL"
+    LABEL_XYXY = "LABEL_XYXY"
+    LABEL_XYWH = "LABEL_XYWH"
+    LABEL_CXCYWH = "LABEL_CXCYWH"
+    NORMALIZED_XYXY_LABEL = "NORMALIZED_XYXY_LABEL"
+    NORMALIZED_XYWH_LABEL = "NORMALIZED_XYWH_LABEL"
+    NORMALIZED_CXCYWH_LABEL = "NORMALIZED_CXCYWH_LABEL"
+    LABEL_NORMALIZED_XYXY = "LABEL_NORMALIZED_XYXY"
+    LABEL_NORMALIZED_XYWH = "LABEL_NORMALIZED_XYWH"
+    LABEL_NORMALIZED_CXCYWH = "LABEL_NORMALIZED_CXCYWH"