Update README.md

README.md

@@ -12,11 +12,12 @@ multilinguality:
 size_categories:
 - 1K<n<10K
 source_datasets:
-- extended|other-wider
+- extended
 task_categories:
 - object-detection
 task_ids:
 - face-detection
+- license-plate-detection
 pretty_name: PP4AV
 ---
 
@@ -69,18 +70,18 @@ English
 
 ### Data Instances
 
-A data point comprises an image and its face annotations.
+A data point comprises an image and its face and license plate annotations.
 
 ```
 {
-  'image': <PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=1024x755 at 0x19FA12186D8>, 'faces': {
+  'image': <PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=1024x755 at 0x19FA12186D8>, 'objects': {
     'bbox': [
-      [0.230078, 0.317081, 0.239062, 0.331367],
-      [0.5017185, 0.0306425, 0.5185935, 0.0410975],
-      [0.695078, 0.0710145, 0.7109375, 0.0863355],
-      [0.4089065, 0.31646, 0.414375, 0.32764],
-      [0.1843745, 0.403416, 0.201093, 0.414182],
-      [0.71325, 0.3393474, 0.717922, 0.3514285]
+      [0 0.230078 0.317081 0.239062 0.331367],
+      [1 0.5017185 0.0306425 0.5185935 0.0410975],
+      [1 0.695078 0.0710145 0.7109375 0.0863355],
+      [1 0.4089065 0.31646 0.414375 0.32764],
+      [0 0.1843745 0.403416 0.201093 0.414182],
+      [0 0.7132 0.3393474 0.717922 0.3514285]
     ]
   }
 }
@@ -89,8 +90,10 @@ A data point comprises an image and its face annotations.
 ### Data Fields
 
 - `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]`
-- `faces`: a dictionary of face attributes for the faces present on the image
-  - `bbox`: the bounding box of each face (in the [yolo](https://albumentations.ai/docs/getting_started/bounding_boxes_augmentation/#yolo) format)
+- `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>`:
+    - `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>`
 
 ## Dataset Creation