You're reading from Modern Computer Vision with PyTorch

Product typeBook

Published inNov 2020

Reading LevelBeginner

PublisherPackt

ISBN-139781839213472

Edition1st Edition

Languages

Python

Tools

PyTorch

Concepts

Computer Vision

Authors (2):

V Kishore Ayyadevara

Yeshwanth Reddy

View More author details

Crowd counting

Imagine a scenario where you are given a picture of a crowd and are asked to estimate the number of people present in the image. A crowd counting model comes in handy in such a scenario. Before we go ahead and build a model to perform crowd counting, let's understand the data available and the model architecture first.

In order to train a model that predicts the number of people in an image, we will have to load the images first. The images should constitute the location of the center of the heads of all the people present in the image. A sample of the input image and the location of the center of the heads of the respective people in the image is as follows (source: ShanghaiTech dataset (https://github.com/desenzhou/ShanghaiTechDataset)):

In the preceding example, the image representing ground truth (the image on the right – the center of the heads of the people present in the image) is extremely sparse. There are exactly N white pixels, where N is the number...

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Modern Computer Vision with PyTorch

Published in: Nov 2020Publisher: PacktISBN-13: 9781839213472

Authors (2)

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 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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Crowd counting

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