Image Colorization using TensorFlow 2 and Keras

ofrecido por
Coursera Project Network
En este proyecto guiado, tú:

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
BeginnerPrincipiante
CloudNo se necesita descarga
VideoVideo de pantalla dividida
Comment DotsInglés (English)
LaptopSolo escritorio

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.

Habilidades que desarrollarás

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

Aprende paso a paso

En un video que se reproduce en una pantalla dividida con tu área de trabajo, tu instructor te guiará en cada paso:

  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.

Cómo funcionan los proyectos guiados

Tu espacio de trabajo es un escritorio virtual directamente en tu navegador, no requiere descarga.

En un video de pantalla dividida, tu instructor te guía paso a paso

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