Update README.md

README.md

@@ -91,9 +91,21 @@ A data point comprises an image and its face and license plate annotations.
 
 - `image`: A `PIL.Image.Image` object containing the image. Note that when accessing the image column: `dataset[0]["image"]` the image file is automatically decoded. Decoding of a large number of image files might take a significant amount of time. Thus it is important to first query the sample index before the `"image"` column, *i.e.* `dataset[0]["image"]` should **always** be preferred over `dataset["image"][0]`
 - `objects`: a dictionary of face and license plate bounding boxes present on the image
-  - `bbox`: the bounding box of each face and license plate (in the [yolo](https://albumentations.ai/docs/getting_started/bounding_boxes_augmentation/#yolo) format). Basically, each row in `.txt` file for each `.png` image file consists of data in format: `<object-class> <x_center> <y_center> <width> <height>`:
+  - `bbox`: the bounding box of each face and license plate (in the [yolo](https://albumentations.ai/docs/getting_started/bounding_boxes_augmentation/#yolo) format). Basically, each row in annotation `.txt` file for each image `.png` file consists of data in format: `<object-class> <x_center> <y_center> <width> <height>`:
     - `object-class`: integer number of object from 0 to 1, where 0 indicate face object, and 1 indicate licese plate object
-    - `x_center`: normalized x-axis coordinate of the center of the bounding box. `x_center = <absolute_x_center> / <image_width>`
+    - `x_center`: normalized x-axis coordinate of the center of the bounding box. 
+      `x_center = <absolute_x_center> / <image_width>`
+    - `y_center`: normalized y-axis coordinate of the center of the bounding box. 
+      `y_center = <absolute_y_center> / <image_height>`
+    - `width`: normalized width of the bounding box. 
+      `width = <absolute_width> / <image_width>`
+    - `height`: normalized wheightdth of the bounding box. 
+      `height = <absolute_height> / <image_height>`
+    - Example lines in YOLO v1.1 format `.txt' annotation file:
+      ` 1 0.716797 0.395833 0.216406 0.147222
+        0 0.687109 0.379167 0.255469 0.158333
+        1 0.420312 0.395833 0.140625 0.166667
+      `
 
 ## Dataset Creation