Tag Archives | neural nets

How to create a deep learning dataset using Google Images

PyImageSearch reader José asks: Hey Adrian, thanks for putting together Deep Learning for Computer Vision with Python. This is by far the best resource I’ve seen for deep learning. My question is this: I’m working on a project where I need to classify the scenes of outdoor photographs into four distinct categories: cities, beaches, mountains, and […]

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Raspberry Pi: Deep learning object detection with OpenCV

A few weeks ago I demonstrated how to perform real-time object detection using deep learning and OpenCV on a standard laptop/desktop. After the post was published I received a number of emails from PyImageSearch readers who were curious if the Raspberry Pi could also be used for real-time object detection. The short answer is “kind […]

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Stochastic Gradient Descent (SGD) with Python

In last week’s blog post, we discussed gradient descent, a first-order optimization algorithm that can be used to learn a set of classifier coefficients for parameterized learning. However, the “vanilla” implementation of gradient descent can be prohibitively slow to run on large datasets — in fact, it can even be considered computationally wasteful. Instead, we should apply Stochastic […]

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