Hand Gesture Recognition using Tensorflow and Keras

4.2
10 個評分
提供方
Coursera Project Network
在此指導項目中,您將:

Learn about label binarization.

Learn how to create a custom CNN model.

Create a Streamlit app to allow users to select a hand gesture and obtain the alphabet it represents using the model you trained.

Clock1 hour 30 minutes
Beginner初級
Cloud無需下載
Video分屏視頻
Comment Dots英語(English)
Laptop僅限桌面

Note: The rhyme platform currently does not support webcams, so this is not a live hand gesture recognition project. This guided project is about hand gesture recognition using Python,TensorFlow2 and Keras. Hand gesture recognition comes under the computer vision domain. In this project you will learn how to build a convolutional neural network(CNN) using Tensorflow2 and Keras. While you are watching me code, you will get a cloud desktop with all the required software pre-installed. This will allow you to code along with me. After all, we learn best with active, hands-on learning. Special Feature: 1) Learn about data augmentation. 2) How to reshape data to fit a CNN. 3) Explanation of each layer in a CNN. 4) Create a Streamlit app to allow users to select a hand gesture and obtain the alphabet it represents using the model you trained. Note: This project works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.

您要培養的技能

  • CNN
  • Deep Learning
  • Python Programming
  • Tensorflow
  • keras

分步進行學習

在與您的工作區一起在分屏中播放的視頻中,您的授課教師將指導您完成每個步驟:

  1. Preprocess grayscale images.

  2. Normalize and reshape images.

  3. Build the CNN with TensorFlow2 and Keras.

  4. Save the model.

  5. Load the pre-trained model in a streamlit app.

指導項目工作原理

您的工作空間就是瀏覽器中的雲桌面,無需下載

在分屏視頻中,您的授課教師會為您提供分步指導

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