AnimalPose : Pose Esimation for Animals

This is an introduction to「AnimalPose」, a machine learning model that can be used with ailia SDK. You can easily use this model to create AI applications using ailia SDK as well as many other ready-to-use ailia MODELS.

Overview

AnimalPose takes an image of an animal as input and computes a skeleton made of 20 keypoints. Since the model works on cows, it could for example be used in the field of agriculture.

Source: https://pixabay.com/ja/photos/%e7%89%9b-%e5%ae%b6%e7%95%9c-%e4%b9%b3%e7%89%9b-%e4%b9%b3%e7%94%a8%e7%89%9b-%e5%8b%95%e7%89%a9-5717276/

open-mmlab/mmpose

Architecture

AnimalPose is published as part of mmpose, a general-purpose pose estimation framework. Two pre-trained models of AnimalPose are provided, one using hrnet and the other using pose_resnet.

Animal — MMPose 0.15.0 documentation

Both models are based on a Top-down approach, which detects the keypoints of a single animal at a time. Animals are first detected using object detection models such as YOLO, and then the keypoints of each animal are computed by AnimalPose. More details on the difference between Top-down and Bottom-up approaches here.

Dataset

AnimalPose was trained using Animal-Pose Dataset, which has been partially created based on PASCAL2011 dataset annotations and images.

The dataset contains more than 3000 images annotated in five categories, with a total of 5517 instances. Each instance has 20 key points defined: 4 paws, 2 eyes, 2 ears, 4 elbows, nose, throat, withers, tail base, and 4 knees points.

Source: https://sites.google.com/view/animal-pose/

Cross-Domain Adaptation for Animal Pose Estimation

Usage

Use the following command to run AnimalPose on a video file.

$ python3 animalpose.py -v input.mp4

axinc-ai/ailia-models

Here is a result example.

Related topics

BlazePose : A 3D Pose Estimation Model

LightWeightHumanPose : A Machine Learning Model for Fast Multi-person Pose Estimation.

PoseResnet : A Top-down Machine Learning Model for Pose Estimation

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