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@@ -181,3 +181,171 @@ pretty_name: AwA-Pose-Full
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  size_categories:
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  - 10K<n<100K
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  ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  size_categories:
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  - 10K<n<100K
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  ---
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+
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+ ## **Dataset Summary**
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+
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+ AwA Pose, a quadrupedal keypoint detection dataset that offers richer annotations and greater species diversity than existing datasets. The data supports efficiency, advances in research on generalized keypoint detection in animals.
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+
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+ The dataset was explored, filtered, and stored in a [pyarrow type](https://arrow.apache.org/docs/python/index.html). See : [AwA2_dataset_analysis](https://www.kaggle.com/code/radimkzl/awa2-dataset-analysis)
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+ ***Original Kaggle dataset:*** [AwA2_dataset](https://www.kaggle.com/datasets/radimkzl/awa2-dataset)
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+
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+ The original data comes from two sources and is described in:
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+
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+ - [A Novel Dataset for Keypoint Detection of
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+ Quadruped Animals from Images](https://arxiv.org/pdf/2108.13958)
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+ - [GitHub: prinik/AwA-Pose](https://github.com/prinik/AwA-Pose/tree/main)
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+ - [Animals with Attributes 2](https://cvml.ista.ac.at/AwA2/)
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+
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+ *The dataset contains:*
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+ - Lite version of keypoints dataset
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+ - Full version of keypoints dataset
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+
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+ *All version contains:*
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+ - train dataset: 90%
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+ - validation dataset: 5%
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+ - test dataset: 5%
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+
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+ ## **Description of data in the dataset**
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+
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+ *Class names:*
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+ - antelope
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+ - bobcat
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+ - buffalo
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+ - chihuahua
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+ - collie
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+ - cow
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+ - dalmatian
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+ - deer
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+ - elephant
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+ - fox
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+ - german+shepherd
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+ - giant+panda
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+ - giraffe
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+ - grizzly+bear
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+ - hippopotamus
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+ - horse
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+ - leopard
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+ - lion
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+ - moose
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+ - otter
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+ - ox
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+ - persian+cat
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+ - pig
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+ - polar+bear
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+ - rabbit
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+ - raccoon
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+ - rhinoceros
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+ - sheep
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+ - siamese+cat
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+ - squirrel
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+ - tiger
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+ - weasel
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+ - wolf
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+ - zebra
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+
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+ ## **Columns description**
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+
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+ | name column| description of column |
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+ |:--------------|:--------------------------------|
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+ | id | id number of records|
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+ | right_eye | keypoint values [x,y] |
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+ | right_earbase | keypoint values [x,y] |
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+ | right_earend | keypoint values [x,y] |
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+ | right_antler_base | keypoint values [x,y] |
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+ | right_antler_end | keypoint values [x,y] |
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+ | left_antler_base | keypoint values [x,y] |
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+ | left_antler_end | keypoint values [x,y] |
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+ | left_earbase | keypoint values [x,y] |
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+ | left_earend | keypoint values [x,y] |
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+ | left_eye | keypoint values [x,y] |
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+ | nose | keypoint values [x,y] |
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+ | upper_jaw | keypoint values [x,y] |
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+ | lower_jaw | keypoint values [x,y] |
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+ | mouth_end_right | keypoint values [x,y] |
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+ | throat_base | keypoint values [x,y] |
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+ | neck_base | keypoint values [x,y] |
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+ | neck_end | keypoint values [x,y] |
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+ | back_base | keypoint values [x,y] |
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+ | back_middle | keypoint values [x,y] |
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+ | back_end | keypoint values [x,y] |
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+ | tail_base | keypoint values [x,y] |
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+ | body_middle_right | keypoint values [x,y] |
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+ | bbox | bounding box dimension [x1, y1, x2, y2] |
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+ | mouth_end_left | keypoint values [x,y] |
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+ | throat_end | keypoint values [x,y] |
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+ | tail_end | keypoint values [x,y] |
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+ | front_left_thai | keypoint values [x,y] |
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+ | front_left_knee | keypoint values [x,y] |
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+ | front_left_paw | keypoint values [x,y] |
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+ | front_right_thai | keypoint values [x,y] |
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+ | front_right_paw | keypoint values [x,y] |
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+ | front_right_knee | keypoint values [x,y] |
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+ | back_left_knee | keypoint values [x,y] |
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+ | back_left_paw | keypoint values [x,y] |
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+ | back_left_thai | keypoint values [x,y] |
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+ | back_right_thai | keypoint values [x,y] |
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+ | back_right_paw | keypoint values [x,y] |
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+ | back_right_knee | keypoint values [x,y] |
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+ | belly_bottom | keypoint values [x,y] |
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+ | body_middle_left | keypoint values [x,y] |
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+ | name_file | name of file as string |
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+ | name_class | name of class as string |
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+ | left_antlerbase | keypoint values [x,y] |
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+ | left_antlerend | keypoint values [x,y] |
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+ | right_antlerend | keypoint values [x,y] |
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+ | right_antlerbase | keypoint values [x,y] |
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+ | neckbase | keypoint values [x,y] |
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+ | neckend | keypoint values [x,y] |
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+ | backbase | keypoint values [x,y] |
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+ | backmiddle | keypoint values [x,y] |
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+ | backend | keypoint values [x,y] |
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+ | tailend | keypoint values [x,y] |
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+ | bellybottom | keypoint values [x,y] |
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+ | back_right_pi | keypoint values [x,y] |
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+ | tail_e | keypoint values [x,y] |
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+ | left_eara | keypoint values [x,y] |
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+ | right_earE | keypoint values [x,y] |
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+ | right_earea | keypoint values [x,y] |
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+ | left_ear_base | keypoint values [x,y] |
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+ | left_ear_end | keypoint values [x,y] |
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+ | right_ear_end | keypoint values [x,y] |
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+ | right_ear_base | keypoint values [x,y] |
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+ | tail_ea | keypoint values [x,y] |
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+ | wither | keypoint values [x,y] |
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+ | throat | keypoint values [x,y] |
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+ | left_ey | keypoint values [x,y] |
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+ | throat_be | keypoint values [x,y] |
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+ | tail_be | keypoint values [x,y] |
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+ | back_left_ta | keypoint values [x,y] |
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+ | image_base64s | image as string Base64 |
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+ | image_width | value of with of image |
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+ | image_height | value of height of image |
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+ | image_license | text of licence of image |
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+
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+ ## **Notes on data**
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+
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+ &gt; If a *keypoints* contains `[-1.0, -1.0]`, it means that the point is not visible in the image. These points must be masked when training the model.
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+
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+ &gt; Images are stored as a Base64 string. They can be transformed using the function:
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+
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+ ```python
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+ import base64
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+ import io
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+ from PIL import Image
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+
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+ def base64_to_img(base64_str):
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+ img_bytes = base64.b64decode(base64_str)
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+ img_buffer = io.BytesIO(img_bytes)
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+ img = Image.open(img_buffer)
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+
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+ return img
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+ ```
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+
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+ Find out more in [AwA2_dataset_analysis](https://www.kaggle.com/code/radimkzl/awa2-dataset-analysis#Create-AwA2-dataset-for-Hugging-Face...)
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+
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+ ## **Licensing Information**
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+
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+ Data for keypoints is licensed according to [GitHub: prinik/AwA-Pose](https://github.com/prinik/AwA-Pose/tree/main), this license is [MIT](https://github.com/prinik/AwA-Pose/tree/main?tab=MIT-1-ov-file#readme).
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+
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+ The license for the images is according to [Animals with Attributes 2](https://cvml.ista.ac.at/AwA2/), see data column `image_license `.