Computer Vision

A step-by-step guide to applying a perspective transformation on images

Computer vision is all abuzz now. People everywhere are working on some form of deep-learning-based computer vision projects. But before the advent of Deep Learning, image processing techniques were employed to manipulate and transform images in order to obtain insights that would help us achieve the task at hand. Today, let’s see how we can implement a simple yet helpful technique known as Perspective Projection to warp an image.

But wait! What does warping an image mean? I could explain it with a lot of fancy words and technical jargon. But then, it will be easy to just show the…

A simple tutorial to perform instance segmentation using Python and OpenCV

Computer Vision as a field of research has seen a lot of development in recent years. Ever since the introduction of Convolutional Neural Networks, the state of the art in domains such as classification, object detection, image segmentation, etc. have constantly been challenged. With the aid of sophisticated hardware providing very high computational power, these neural network models are being employed in real-time in emerging fields such as Autonomous Navigation.

Our topic of focus today will be a sub-field of Computer Vision known as Image Segmentation. To be more precise, we’ll be performing Instance Segmentation on an image or video…

Using PyTorch and CNNs to classify x-ray images that show traits of Pneumonia.

Utilizing computer vision and deep learning for diagnosing medical conditions is an extensive area of research and there have been several breakthroughs in this field. Classifying images based on some criteria into various categories is termed Image Classification. In this article, I’ll be explaining the concept of Binary Classification, a sub-set of Image Classification. We’ll develop a deep learning model using PyTorch and achieve good enough results with the use of a concept called Transfer Learning. The model would analyze and classify x-ray images into two categories — “Pneumonia” and “Normal”.

Example Output — Image by Author

Let’s now take a stroll through the pipeline:-


A journey into detecting objects in real-time using YOLOv3 and OpenCV

Deep learning has revolutionized the realm of computer vision. Neural Networks are widely used in almost all of the cutting-edge tech such as Tesla’s auto-pilot feature. They perform too well that there are times they lead to ethical issues and conflicts. Well, we won’t be diving into those today. Let’s focus on a sub-category of computer vision called “Detection”.

What does one mean by detecting an object? When we see an object, we can exactly point where it is and determine what it is with ease. For computers though, the task is not so simple. This has been an active…

G SowmiyaNarayanan

Using Deep Learning and Computer Vision to tackle challenges | Diagnosed with Obsessive Coffee Disorder | Motto : Try -> Succeed/Fail -> Persevere

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