Is the area formula for bouding box used in the tfrecord code correct?

Prerequisites

Please answer the following questions for yourself before submitting an issue.

• I am using the latest TensorFlow Model Garden release and TensorFlow 2.
• I am reporting the issue to the correct repository. (research directory)
• I checked to make sure that this issue has not already been filed.

1. The entire URL of the file you are using

research/object_detection/dataset_tools/context_rcnn/create_cococameratraps_tfexample_main.py

2. Describe the bug

"
for object_annotations in annotations:
if 'bbox' in object_annotations and self._keep_bboxes:
(x, y, width, height) = tuple(object_annotations['bbox'])
if width <= 0 or height <= 0:
num_annotations_skipped += 1
print(f"Skipping annotation for image ID: {image_id} - Invalid bounding box dimensions.")
continue
if x + width > image_width or y + height > image_height:
num_annotations_skipped += 1
print(f"Skipping annotation for image ID: {image_id} - Bounding box exceeds image boundaries.")
continue
xmin.append(float(x) / image_width)
xmax.append(float(x + width) / image_width)
ymin.append(float(y) / image_height)
ymax.append(float(y + height) / image_height)
if 'area' in object_annotations:
area.append(object_annotations['area'])
else:
# approximate area using lw/2
area.append(widthheight/2.0)
"

Inside the code, I found that the formula of area for the bounding box being used is "widthheight/2.0". Since the bounding box is a rectangle, I am wondering why is the original formula of an area of a rectangle(area = widthheight) is being divided by 2? Is it correct?