Pose Estimation with TensorFlow readme

accepts a stream that is sent to a proxy server in next js to avoid CORs error does pose estimation then calculte the mid point of shoulder and hips and console.logs the angle

if angle is lesser then 45 or greate than 145 give a notification to keep the back straight

backend python script that sends a stream .

from flask import Flask, Response
import requests
from flask_cors import CORS

app = Flask(__name__)
CORS(app, resources={r"/video": {"origins": "*"}}) 

@app.route('/')
def hello_world():
    return 'Hello, World!'

@app.route('/video')
def stream_video():
    video_path = 'bikeRiding.mp4'
    def generate():
        with open(video_path, 'rb') as video_file:
            while True:
                data = video_file.read(1024)
                if not data:
                    break
                yield data

    return Response(generate(), mimetype='video/mp4')

if __name__ == '__main__':
    app.run(host='0.0.0.0', port=5000)

to run

npm install
npm run dev

connect to a server route for video fecting.

todos / remaining

1. add strava auth workflow #Done
2. add mongodb to store angles #Done
3. add a background voice when angles or not correct or a tost notification ??