Pose estimation is a computer vision technique for determining the pose of an object in an image.

In this example, you learn how to implement inference code with a ModelZoo model to detect dogs in an image.

The source code can be found at PoseEstimation.java.

Follow setup to configure your development environment.

You can find the image used in this example in the project test resource folder: `src/test/resources/pose_soccer.jpg`

Use the following command to run the project:

```
cd examples
./gradlew run -Dmain=ai.djl.examples.inference.PoseEstimation
```

Your output should look like the following:

```
[INFO ] - Pose image has been saved in: build/output/joints.png
[INFO ] -
[ Joint [x=0.333, y=0.063], confidence: 0.6940,
Joint [x=0.333, y=0.031], confidence: 0.7182,
Joint [x=0.354, y=0.047], confidence: 0.4949,
Joint [x=0.354, y=0.047], confidence: 0.9011,
Joint [x=0.458, y=0.031], confidence: 0.8790,
Joint [x=0.375, y=0.172], confidence: 0.8546,
Joint [x=0.542, y=0.156], confidence: 0.8659,
Joint [x=0.417, y=0.313], confidence: 0.7731,
Joint [x=0.625, y=0.328], confidence: 0.9211,
Joint [x=0.458, y=0.500], confidence: 0.7541,
Joint [x=0.542, y=0.359], confidence: 0.5837,
Joint [x=0.458, y=0.469], confidence: 0.6387,
Joint [x=0.563, y=0.469], confidence: 0.6686,
Joint [x=0.271, y=0.703], confidence: 0.8583,
Joint [x=0.625, y=0.719], confidence: 0.8233,
Joint [x=0.125, y=0.969], confidence: 0.7007,
Joint [x=0.958, y=0.844], confidence: 0.7480
]
```

An output image with the detected joints will be saved as build/output/joints.png: