Object Detection on Custom Dataset With Keras Using Python

Object Detection on Custom Dataset With Keras Using Python

Object Detection on Custom Dataset With Keras Using Python

Vision Transformer for Computer Vision with Keras and TensorFlow in Google Colab Platform : Hands-on

Language: english

Note: 5.0/5 (1 notes) 32 students  New course 

Instructor(s): Karthik K

Last update: 2022-10-01

What you’ll learn

  • Understand the fundamentals of Vision Transformer (ViT)
  • Build and train a deep learning network using Keras with Tensorflow as a backend using Google Colab
  • Assess the performance of trained model
  • Learn to use the trained model to predict the object of a new image data set

 

Requirements

  • Basic knowledge of Python Programming

 

Description

Welcome to the “Object Detection on Custom Dataset with Keras using Python” course. In this course, you will learn how to create a Vision Transformer in Keras with a TensorFlow backend from scratch, and you will learn to train the deep learning model to solve object detection problems. Please note that you don’t need a high-powered workstation to learn this course. We will be carrying out the entire project in the Google Colab environment, which is free. You only need an internet connection and a free Gmail account to complete this course. This is a practical course, we will focus on Python programming, and you will understand every part of the program very well. By the end of this course, you will be able to build and train the deep learning network using Keras with TensorFlow as a backend. You will also be able to visualise data and use the model to make predictions on new data. This object detection course is practical and directly applicable to many industries. You can add this project to your portfolio of projects which is essential for your following job interview. This course is designed most straightforwardly to utilise your time wisely. Happy learning.


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The average Deep Learning Engineer’s salary is $143,793 as of August 29, 2022, but the salary range typically falls between $124,179 and $165,138.

 

Who this course is for

  • Beginners starting out to the field of Deep Learning
  • Industry professionals and aspiring data scientists
  • People who want to know how to write their object detection code

 

Course content

  • Fundamentals
    • Introduction
    • Artificial Intelligence
    • Machine Learning
    • Deep Learning
    • Object Detection
    • How object detection is done?
    • Vision Transformer Architecture
  • Building, Evaluating and Predicting Object Detection Model
    • Download Dataset
    • What is inside leopards_images folder?
    • What is inside leopards_annotation folder?
    • What is the .h5 file?
    • Object Detection Python Code
    • Enabling GPU in Google Colab
    • Is GPU connected to Colab notebook?
    • Connect Google Colab with Google Drive
    • Download TensorFlow Addons
    • Check the Number of Images in the Dataset
    • Preparing the Dataset
    • Visualizing a Sample Image in the Dataset
    • Building Multilayer-Perceptron (MLP) Network
    • Building the Patch Creation Layer
    • Displaying Patches for an Input Image
    • Building the Patch Encoding Layer
    • Building Vision Transformer
    • Compiling and Displaying Model
    • Training the Model
    • Evaluating : Intersection over Union / Jaccard Index

 

Time remaining or 969 enrolls left

 

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