Image Colorization using TensorFlow 2 and Keras

提供方
Coursera Project Network
在此指导项目中,您将:

Learn how to work with images in the .npy file format.

Learn how to create a custom CNN model.

Create an app to allow users to colorize black and white images using the model you trained.

Clock1 hour 30 minutes
Beginner初级
Cloud无需下载
Video分屏视频
Comment Dots英语(English)
Laptop仅限桌面

This guided project is about image colorization using TensorFlow2 and Keras. Image colorization 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) Explanation of the process of image colorization. 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 colorize a black and white image 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.

您要培养的技能

  • Deep Learning
  • Convolutional Neural Network
  • Tensorflow
  • Streamlit
  • keras

分步进行学习

在与您的工作区一起在分屏中播放的视频中,您的授课教师将指导您完成每个步骤:

  1. Preprocess grayscale images.

  2. Extract colors from colorful images to provide as inputs to the model.

  3. Build the CNN with TensorFlow2 and Keras.

  4. Save the model.

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

指导项目工作原理

您的工作空间就是浏览器中的云桌面,无需下载

在分屏视频中,您的授课教师会为您提供分步指导

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