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Come, see for yourself, how Cropping an Image using OpenCV works. First, why do we need to crop? Cropping is done to remove all unwanted objects or areas from an
Come, let’s learn about image resizing with OpenCV. To resize an image, scale it along each axis (height and width), considering the specified scale factors or just set the desired
Reading, displaying, and writing images are basic to image processing and computer vision. Even when cropping, resizing, rotating, or applying different filters to process images, you’ll need to first read
Most of the Machine Learning and Deep Learning problems that you solve are conceptualized from the Generative and Discriminative Models. In Machine Learning, one can clearly distinguish between the two
Consider this, you’re in the middle of your work, and then suddenly due to some reason the internet stops working due to some router issue you’re informed that it will
In this post, we will learn about Video Classification. We will go over a number of approaches to make a video classifier for Human Activity Recognition. Basically, you will learn
Can we distinguish one person from another by looking at the face? We can probably list several features such as eye color, hairstyle, skin tone, the shape of the nose
We will learn the concepts of Epipolar geometry and point correspondences. We will then use these concepts discuss how to calculate depth from stereo disparity.
Stanford ML Group, led by Andrew Ng, works on important problems in areas such as healthcare and climate change, using AI. Last year they released a knee MRI dataset consisting
When approaching a problem using Machine Learning or Deep Learning, researchers often face a necessity of model tuning because the chosen method usually depends on various hyperparameters and used data.
In a previous post, we went over the geometry of image formation and learned how a point in 3D gets projected on to the image plane of a camera. The
The foreground is the part of a view or picture, that is nearest to you when you look at it (Oxford dictionary). We, humans, are usually good at distinguishing foreground
