Python OpenCV - Guide to Image Processing for AI/ML

Python OpenCV - Guide to Image Processing for AI/ML

In this topic, we’ll cover the Python OpenCV library in complete detail. Computer Vision refers to the field of study which deals with how computers perceive images. It involves feeding images into a computer and then trying to gain high-level intelligence from it using different algorithms. Python OpenCV - Guide to Image Processing for AI/ML

In this topic, we’ll cover the Python OpenCV library in complete detail. Computer Vision refers to the field of study which deals with how computers perceive images. It involves feeding images into a computer and then trying to gain high-level intelligence from it using different algorithms.

It works in close coordination with fields like** Machine Learning** and Artificial Intelligence. Computer Vision is a broad field and is progressing rapidly.

Computer Vision has a variety of real-world applications:

  1. Object detection
  2. Facial Recognition
  3. Self-Driving Cars
  4. Cancer-Detection

One of the popular tasks under the broad field of Computer Vision is Image Processing.

Image processing involves performing some operations on an image, in order to get an enhanced image or to extract some useful information from it.

A major part of object detection is solved using Convolution Neural Networks.

  • What is a Convolution Neural Network?

A convolutional neural network is a class of deep neural networks that can analyze image data. It is able to draw useful high-level information from image data. These networks can be trained for recognizing objects, facial features,  handwriting, and image classification.

A Convolutional Neural Network usually containsa combination of the following layers.

  • Convolutional Layers
  • Pooling Layers
  • Flattening Layers.

Let’s briefly discuss about these layers.

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