documentation addition + fix

Author: vivinousi

Diff for: docs/reference/object-detection-2d-centernet.md

@@ -5,7 +5,7 @@ The *centernet* module contains the *CenterNetDetectorLearner* class, which inhe
 ### Class CenterNetDetectorLearner
 Bases: `engine.learners.Learner`
 
-The *CenterNetDetectorLearner* class is a wrapper of the SSD detector[[1]](#centernet-1)
+The *CenterNetDetectorLearner* class is a wrapper of the CenterNet detector[[1]](#centernet-1)
 [GluonCV implementation](https://github.com/dmlc/gluon-cv/blob/master/gluoncv/model_zoo/center_net/center_net.py).
 It can be used to perform object detection on images (inference) as well as train new object detection models.
 

Diff for: docs/reference/object-detection-2d-datasets.md

@@ -0,0 +1,87 @@
+# Object Detection 2D Datasets
+
+## Base Classes
+
+### DetectionDataset base class
+
+Bases: `engine.datasets.DatasetIterator`
+
+The *DetectionDataset* class inherits from the *DatasetIterator* class and extends it with functions and properties aimed at 2d Object Detection datasets. Each *DetectionDataset* object must be initialized with the following parameters:
+
+- **classes**: *list*\
+  List of class names of the training dataset.
+- **dataset_type**: *str*\
+  Dataset type, i`.e., an assigned name.
+- **root**: *str*\
+  Path to dataset root directory.
+- **image_paths**: *list, default=None*\
+  List of image data paths.
+- **splits**: *str, default=''*\
+  List of dataset splits to load (e.g., train/val).
+- **image_transform**: *callable object, default=None*\
+  Transformation to apply to images. Intended for image format transformations.
+- **target_transform**: *callable object, default=None*\
+  Transformation to apply to bounding boxes. Intended for formatting the bounding boxes for each detector.
+- **transform**: *callable object, default=None*\
+  Transformation to apply to both images and bounding boxes. Intended for data augmentation purposes.
+  
+Methods:
+
+#### `DetectionDataset.set_transform`
+Setter for the internal **transform** object/function.
+
+#### `DetectionDataset.set_image_transform`
+Setter for the internal **image_transform** object/function.
+
+#### `DetectionDataset.set_target_transform`
+Setter for the internal **target_transform** object/function.
+
+#### `DetectionDataset.transform`
+Returns the `DetectionDataset` wrapped as a `MappedDetectionDataset`, where the data is transformed according to the argument callable object/function. This function ensures fit/eval compatibility between `DetectionDataset` and `ExternalDataset` for [GluonCV](https://github.com/dmlc/gluon-cv) based detectors.
+
+#### `DetectionDataset.get_image`
+Returns an image from the dataset. Intended for test sets without annotations.
+
+#### `DetectionDataset.get_bboxes`
+Returns the bounding boxes for a given sample.
+
+
+### MappedDetectionDataset class
+
+Bases: `engine.datasets.DatasetIterator`
+
+This class wraps any `DetectionDataset` and applies `map_function` to the data.
+
+### ConcatDataset class
+
+Bases: `perception.object_detection_2d.datasets.DetetionDataset`
+
+Returns a new `DetectionDataset` which is a concatenation of the `datasets` param. The datasets are assumed to have the same classes.
+
+### XMLBasedDataset class
+
+Bases: `perception.object_detection_2d.datasets.DetetionDataset`
+
+This class is intended for any dataset in PASCAL VOC .xml format, making it compatible with datasets annotated using the [labelImg](https://github.com/tzutalin/labelImg) tool. Each *XMLBasedDataset* object must be initialized with the following parameters:
+
+- **dataset_type**: *str*\
+  Dataset type, i.e., assigned name.
+- **root**: *str*\
+  Path to dataset root directory.
+- **classes**: *list, default=None*\
+  Class names. If None, they will be inferred from the annotations.
+- **splits**: *str, default=''*\
+  List of dataset splits to load (e.g., train/val).
+- **image_transform**: *callable object, default=None*\
+  Transformation to apply to images. Intended for image format transformations.
+- **target_transform**: *callable object, default=None*\
+  Transformation to apply to bounding boxes. Intended for formatting the bounding boxes for each detector.
+- **transform**: *callable object, default=None*\
+  Transformation to apply to both images and bounding boxes. Intended for data augmentation purposes.
+- **images_dir**: *str, default='images'*\
+  Name of subdirectory containing dataset images.
+- **annotations_dir**: *str, default='annotations'*\
+  Name of subdirectory containing dataset annotations.
+- **preload_anno**: *bool, default=False*\
+  Whether to preload annotations, for datasets that fit in memory.
+