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train a custom classifier to score dart throws, relate to throwing form through pose estimation
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README.md

Shoot your shot!

Shoot Your Shot

A weekend hackathon project to build a smart dart application. This demo uses two cameras to view the thrower and view the dartboard and track poses and dart placement.

Shoot Your Shot

Getting started

You can run the pose demo in the pose directory by running

python run_pose.py

You can also run the dart demo in the dart directory by running

python vogelpik.py

To run the entire demo, run:

python client.py 

on the jetson nano and

python pushbutton.py

on the raspberry pi to trigger each session.

Requirements

Hardware

Install

Clone the trt_pose repo:

git clone https://github.com/NVIDIA-AI-IOT/trt_pose.git

Follow the instructions to install on your jetson nano.

Install the rest of the dependencies with pip:

pip install -r requirements.txt

If you are using the RealSense camera, make sure to follow these instructions to install the librealsense library.

If you are using AWS to push your data to the cloud, make sure to configure your device with with your AWS credentials and edit each main script in the pose/ and darts/ directory with you S3 bucket name and DynamoDB table name.

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