Learn how to Build a Real Time Sign Language Detection or Hand Gesture Recognition in Python Using TensorFlow Object Detection

An AI Powered Emoji Detector can help you in detecting any kind of emotions and expressions on your face OR hand gestures from web camera. It will help in detecting whether you are happy, sad or angry and so on. This technology is also used for predicting different kinds of expressions like happiness, fear, sadness etc. But how do you build an emoji detector?

The answer is in this course using the kandi 1-click solution kit. You will have a working model at the end of the session!

Learning Objectives

After completing this course you will:

  • Have a good working knowledge of the Fundamentals of Computer Vision.
  • Learn various concepts involved in image preparation and pre-processing of the dataset using OpenCV-python.
  • Have a fully functional emoji detector prototype that you can customize, showcase, share, using the existing source code.
  • Be able to fine tune the model to enhance its performance.

Complete this course in 3 easy steps to earn your certificate!

STEP 1 : Watch the below self-guided tutorial.
STEP 2 : Practice as you watch the video by installing and working with the kandi 1-click solution kit.
STEP 3 : Complete the assessment to receive your certificate.


STEP 1 : TUTORIAL

Watch this self-guided tutorial on installing dependencies, loading pre-trained model, and testing real-time emoji detection to build your own AI-powered Emoji Detector.


STEP 2 : PRACTICAL EXERCISE

Click the below button to access the emoji detector kandi kit. This kit has all the required dependencies and resources you need to build your application.

kandi 1click kits include Python, Jupyter notebook and helps you learn to apply the basics of computer vision to implement an emoji detector application that will be able to identify hand gestures in real-time, perform image preparation and pre-processing of dataset using opencv-python and use state of the art deep learning frameworks like Keras, TensorFlow, h5py to compute image embeddings and build an application that can identify our hand gestures.

Click on the 1-Click Installer button on the kandi kit page to install the emoji detector kit. On installing and running this kit, you will have a working model that you can customize and use in your project.

kandi 1click kit button

After completing this step, proceed to STEP 3.


STEP 3 : ASSESSMENT

Complete a short assessment and earn your certificate now. Congrats
TakeAssessment

Your assessment will be reviewed and you will receive a verified certificate via email within a week.


SUPPORT

Reach out to us by replying below for any help you may need with this course.

We hope you enjoyed using kandi! Continue your learning journey with kandi Congrats

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