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!
Watch video Building a Real Time Sign Language Detection App with React.JS and Tensorflow.JS | Deep Learning online, duration hours minute second in high quality that is uploaded to the channel Nicholas Renotte 22 November 2020. Share the link to the video on social media so that your subscribers and friends will also watch this video. This video clip has been viewed 90,762 times and liked it 2 thousand visitors.
