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You're reading from  Modern Computer Vision with PyTorch

Product typeBook
Published inNov 2020
Reading LevelBeginner
PublisherPackt
ISBN-139781839213472
Edition1st Edition
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Authors (2):
V Kishore Ayyadevara
V Kishore Ayyadevara
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V Kishore Ayyadevara

V Kishore Ayyadevara leads a team focused on using AI to solve problems in the healthcare space. He has 10 years' experience in data science, solving problems to improve customer experience in leading technology companies. In his current role, he is responsible for developing a variety of cutting edge analytical solutions that have an impact at scale while building strong technical teams. Prior to this, Kishore authored three books — Pro Machine Learning Algorithms, Hands-on Machine Learning with Google Cloud Platform, and SciPy Recipes. Kishore is an active learner with keen interest in identifying problems that can be solved using data, simplifying the complexity and in transferring techniques across domains to achieve quantifiable results.
Read more about V Kishore Ayyadevara

Yeshwanth Reddy
Yeshwanth Reddy
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Yeshwanth Reddy

Yeshwanth is a highly accomplished data scientist manager with 9+ years of experience in deep learning and document analysis. He has made significant contributions to the field, including building software for end-to-end document digitization, resulting in substantial cost savings. Yeshwanth's expertise extends to developing modules in OCR, word detection, and synthetic document generation. His groundbreaking work has been recognized through multiple patents. He also created a few Python libraries. With a passion for disrupting unsupervised and self-supervised learning, Yeshwanth is dedicated to reducing reliance on manual annotation and driving innovative solutions in the field of data science.
Read more about Yeshwanth Reddy

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Preparing our data for image classification

Given that we are covering multiple scenarios in this chapter, in order for us to see the advantage of one scenario over the other, we will work on a single dataset throughout this chapter the Fashion MNIST dataset. Let's prepare this dataset:

The following code is available as Preparing_our_data.ipynb in the Chapter03 folder of this book's GitHub repository - https://tinyurl.com/mcvp-packt
  1. Start by downloading the dataset and importing the relevant packages. The torchvision package contains various datasets one of which is the FashionMNIST dataset, which we will be working on in this chapter:
from torchvision import datasets
import torch
data_folder = '~/data/FMNIST' # This can be any directory
# you want to download FMNIST to
fmnist = datasets.FashionMNIST(data_folder, download=True, \
train=True)

In the preceding code, we are specifying the folder (data_folder) where we...

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Modern Computer Vision with PyTorch
Published in: Nov 2020Publisher: PacktISBN-13: 9781839213472

Authors (2)

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V Kishore Ayyadevara

V Kishore Ayyadevara leads a team focused on using AI to solve problems in the healthcare space. He has 10 years' experience in data science, solving problems to improve customer experience in leading technology companies. In his current role, he is responsible for developing a variety of cutting edge analytical solutions that have an impact at scale while building strong technical teams. Prior to this, Kishore authored three books — Pro Machine Learning Algorithms, Hands-on Machine Learning with Google Cloud Platform, and SciPy Recipes. Kishore is an active learner with keen interest in identifying problems that can be solved using data, simplifying the complexity and in transferring techniques across domains to achieve quantifiable results.
Read more about V Kishore Ayyadevara

author image
Yeshwanth Reddy

Yeshwanth is a highly accomplished data scientist manager with 9+ years of experience in deep learning and document analysis. He has made significant contributions to the field, including building software for end-to-end document digitization, resulting in substantial cost savings. Yeshwanth's expertise extends to developing modules in OCR, word detection, and synthetic document generation. His groundbreaking work has been recognized through multiple patents. He also created a few Python libraries. With a passion for disrupting unsupervised and self-supervised learning, Yeshwanth is dedicated to reducing reliance on manual annotation and driving innovative solutions in the field of data science.
Read more about Yeshwanth Reddy