Deep Learning CNN Convolutional Neural Networks with Python - HOG Features

Deep Learning CNN Convolutional Neural Networks with Python - HOG Features

Assessment

Interactive Video

Information Technology (IT), Architecture, Other

University

Practice Problem

Hard

Created by

Wayground Content

FREE Resource

The video tutorial introduces the concept of Histogram of Oriented Gradients (HOG) in Python, focusing on importing necessary libraries like Matplotlib and skimage. It guides through loading images, setting HOG parameters, and visualizing results. The tutorial emphasizes the importance of correct parameter settings and demonstrates how to rescale images after processing. It concludes with troubleshooting common errors and ensuring the code runs smoothly.

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4 questions

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1.

OPEN ENDED QUESTION

3 mins • 1 pt

Explain how to set up subplots for displaying images in Matplotlib.

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2.

OPEN ENDED QUESTION

3 mins • 1 pt

What steps are taken to rescale an image after processing it with HOG?

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3.

OPEN ENDED QUESTION

3 mins • 1 pt

Discuss the importance of matching parameters in the HOG function.

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4.

OPEN ENDED QUESTION

3 mins • 1 pt

What is the final output of the HOG function when applied to an image?

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