Repository: Lightning-Universe/lightning-flash

Issue:
ObjectDetectionData doc typos
## 📚 Documentation

In the API doc for ObjectDetectionData, the parameter descriptions for `train_ann_file` for `from_voc` and `from_via` both mention “COCO format”.



Discussion:

Resolving patch:
diff --git a/flash/image/detection/data.py b/flash/image/detection/data.py
--- a/flash/image/detection/data.py
+++ b/flash/image/detection/data.py
@@ -93,7 +93,7 @@ def from_coco(
         **data_module_kwargs: Any,
     ) -> "ObjectDetectionData":
         """Creates a :class:`~flash.image.detection.data.ObjectDetectionData` object from the given data folders
-        and annotation files in the COCO format.
+        and annotation files in the `COCO JSON format <https://cocodataset.org/#format-data>`_.
 
         Args:
             train_folder: The folder containing the train data.
@@ -152,15 +152,16 @@ def from_voc(
         **data_module_kwargs: Any,
     ) -> "ObjectDetectionData":
         """Creates a :class:`~flash.image.detection.data.ObjectDetectionData` object from the given data folders
-        and annotation files in the VOC format.
+        and annotation files in the `PASCAL VOC (Visual Obect Challenge)
+        <http://host.robots.ox.ac.uk/pascal/VOC/>`_ XML format.
 
         Args:
             train_folder: The folder containing the train data.
-            train_ann_file: The COCO format annotation file.
+            train_ann_file: The VOC format annotation file.
             val_folder: The folder containing the validation data.
-            val_ann_file: The COCO format annotation file.
+            val_ann_file: The VOC format annotation file.
             test_folder: The folder containing the test data.
-            test_ann_file: The COCO format annotation file.
+            test_ann_file: The VOC format annotation file.
             predict_folder: The folder containing the predict data.
             train_transform: The dictionary of transforms to use during training which maps
                 :class:`~flash.core.data.io.input_transform.InputTransform` hook names to callable transforms.
@@ -211,15 +212,17 @@ def from_via(
         **data_module_kwargs: Any,
     ) -> "ObjectDetectionData":
         """Creates a :class:`~flash.image.detection.data.ObjectDetectionData` object from the given data folders
-        and annotation files in the VIA format.
+        and annotation files in the VIA (`VGG Image Annotator <https://www.robots.ox.ac.uk/~vgg/software/via/>`_)
+        `JSON format <https://gitlab.com/vgg/via/-/blob/via-3.x.y/via-3.x.y/CodeDoc.md#structure-of-via-project-
+        json-file>`_.
 
         Args:
             train_folder: The folder containing the train data.
-            train_ann_file: The COCO format annotation file.
+            train_ann_file: The VIA format annotation file.
             val_folder: The folder containing the validation data.
-            val_ann_file: The COCO format annotation file.
+            val_ann_file: The VIA format annotation file.
             test_folder: The folder containing the test data.
-            test_ann_file: The COCO format annotation file.
+            test_ann_file: The VIA format annotation file.
             predict_folder: The folder containing the predict data.
             train_transform: The dictionary of transforms to use during training which maps
                 :class:`~flash.core.data.io.input_transform.InputTransform` hook names to callable transforms.


Test patch: