Building a Real Time Sign Language Detection App with React.JS and Tensorflow.JS | Deep Learning
Tired of just using your Python Tensorflow Object Detection model in OpenCV?
Want to showcase your work in a standalone app?
Maybe, you want to do exactly this and help solve the sign language barrier!
Well you can!
In this video you’ll learn how to do exactly that in 45 minutes. You’ll convert an existing Python Tensorflow model and leverage it in a standalone app with real time detections. You’ll be able to see the results in real time! But what’s even better is that you can take this and apply to to your very own use cases, whatever they might be!
This video covers:
1. Converting a Tensorflow Object Detection API model to Tensorflow.JS Graph Model format
2. Hosting a trained Tensorflow deep learning model for applications
3. Downloading the React and Tensorflow.JS Computer Vision Template
4. Making real time detections using a deployed Tensorflow.JS model
5. Visualising detections within the HTML canvas
Completed Code:
https://github.com/nicknochnack/RealT...
Other Links
Template Code: https://github.com/nicknochnack/React...
Setting Up Cloud Object Storage on IBM Cloud: https://cloud.ibm.com/objectstorage/c...
Installing the Cloud Object Storage CLI: https://github.com/IBM-Cloud/ibm-clou...
Installing the Cloud Object Storage Plugin: https://github.com/IBM/ibmcloud-objec...
Tensorflow.JS : https://www.tensorflow.org/js
React: https://reactjs.org/
Oh, and don't forget to connect with me!
LinkedIn: / nicholasr. .
Facebook: / nickrenotte
GitHub: https://github.com/nicknochnack
Happy coding!
Nick
P.s. Let me know how you go and drop a comment if you need a hand!
Смотрите видео Building a Real Time Sign Language Detection App with React.JS and Tensorflow.JS | Deep Learning онлайн без регистрации, длительностью часов минут секунд в хорошем качестве. Это видео добавил пользователь Nicholas Renotte 22 Ноябрь 2020, не забудьте поделиться им ссылкой с друзьями и знакомыми, на нашем сайте его посмотрели 90,762 раз и оно понравилось 2 тысяч людям.