In addition, it uses the ‘ Cascade of Classifiers’. edges, lines) efficiently with the concept of integral image (or summed-area table), which trumps the default computationally-heavy way of subtracting sums of pixels across multiple regions of an entire image. It extracts numerical values for features (e.g. It is a machine learning based approach (involving AdaBoost) where a cascade function is trained from many positive and negative images. In 2001, Paul Viola and Michael Jones came up with the object detection technique using Haar feature-based cascade classifiers. Let’s first talk about the theory behind Haar Cascades since it is an important concept. (ii) Haar Cascade XML File Besides installing the OpenCV library, another important thing to retrieve is the Haar Cascade XML file. We install the Python version of OpenCV (in your virtual environment) with the following command: pip install opencv-python It mainly focuses on image processing, video capture and analysis, including features like face detection and object detection, and it helps to provide a common infrastructure for computer vision applications. (i) OpenCV OpenCV (Open Source Computer Vision Library) is an open-source computer vision and machine learning software library. Before we proceed further, here are the steps to get these tools fully set up on your machine. We will be using Python Jupyter notebook to build our project, along with two open-source software to make the magic happen, namely OpenCV and TesseractOCR.
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