Knowing where an object is in an image is called localization in computer vision. Using contour detection, we can detect the borders of objects, and therefore, localize them easily. Importantly, ...
Image Matting with state-of-the-art Method “F, B, Alpha Matting”
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 objects on images from the ...
Otsu’s Thresholding with OpenCV
In this post, we will examine Otsu's method for automatic image thresholding. What is Image Thresholding? Image thresholding is used to binarize the image based on pixel intensities. The ...
Applications of Foreground-Background separation with Semantic Segmentation
In our previous post, we learned what is semantic segmentation and how to use DeepLab v3 in PyTorch to get an RGB mask of the detected labels within an image. Recall that semantic segmentation is ...
Mask R-CNN Instance Segmentation with PyTorch
In this post, we will discuss the theory behind Mask R-CNN and how to use the pre-trained Mask R-CNN model in PyTorch. This post is part of our series on PyTorch for Beginners. 1. Semantic ...
Faster R-CNN Object Detection with PyTorch
1. Image Classification vs. Object Detection Image Classification is a problem where we assign a class label to an input image. For example, given an input image of a cat, the output of an image ...
