Hand Gesture Recognition using Tensorflow and Keras

4.2
별점
10개의 평가
제공자:
Coursera Project Network
학습자는 이 안내 프로젝트에서 다음을 수행하게 됩니다.

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
Beginner초급
Cloud다운로드 필요 없음
Video분할 화면 동영상
Comment Dots영어
Laptop데스크톱 전용

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.

개발할 기술

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

단계별 학습

작업 영역이 있는 분할 화면으로 재생되는 동영상에서 강사는 다음을 단계별로 안내합니다.

  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.

안내형 프로젝트 진행 방식

작업 영역은 브라우저에 바로 로드되는 클라우드 데스크톱으로, 다운로드할 필요가 없습니다.

분할 화면 동영상에서 강사가 프로젝트를 단계별로 안내해 줍니다.

검토

HAND GESTURE RECOGNITION USING TENSORFLOW AND KERAS의 최상위 리뷰

모든 리뷰 보기

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