1. What is computer vision? Computer vision is a field of artificial intelligence that involves the development of algorithms and systems that can analyze, interpret, and understand visual data from the world around us. 2. What are the main applications of computer vision? Computer vision has a wide range of applications, including image and video…
Image classification is the process of assigning a label to a given image, such as “cat”, “dog”, or “tiger”. There are two main types of image classification methods: Supervised Classification The supervised classification technique is based on the idea that a user can select specific pixels from an image to become a focal point for…
Machine Learning is a powerful, but often misunderstood technology. It’s best known for its applications in the computer vision field, but can be applied to any industry. One of the more common uses is for automatic pedestrian and car detection in footage from surveillance systems and factory video feeds. Object detection is a deep learning…
In recent years, automatic license plate recognition or license plate recognition has become one of the useful approaches for vehicle surveillance. This article presents an automatic license plate recognition project using OpenCV and EasyOCR. Traffic control and vehicle owner identification have become major problems in all countries. It can be difficult to identify the owner of a speeding vehicle that violates the road rules. Therefore, due to the speed of the vehicle, traffic personnel may not be able to obtain the vehicle number of the moving vehicle, so such…
Counting objects in an image is the job of computer vision. There are many Python computer vision libraries available for this task. However, this article describes a very simple approach to counting objects in images using Python. How to count objects in an image using Python? Counting objects in an image is a computer vision task. There are many image processing libraries available for this task. B. OpenCV, TensorFlow, PyTorch, Scikit-image, and cvlib. You probably haven’t heard much about Python’s cvlib library. This is a very simple, advanced, and easy-to-use…
What is Edge detection? Edge detection is a computer vision technique that uses the edges of an image to find and extract objects. It is widely used in a variety of fields such as photography, video and computer vision. it is used in many ways in computer vision, including image segmentation, which divides an image…
In this article, I will be discussing about various algorithms of image feature detection, description using OpenCV. Introduction What do humans typically do when they see the image? He will be able to recognize the faces which are there inside the images. So, in a simple form, computer vision is what allows computers to see…
You may be already familiar with the word ‘contour.’ I’ve used this term several times in previous posts. A contour line is a curved line representing values. It is a very simple type of map that outlines the changes in an area, typically separating the different landforms. But then you may ask this. The terms ‘edges’…
Today we’re going to talk about how to manipulate images. These are preprocessing steps. When it comes to detecting edges and contours, noise plays a major role in the accuracy of the detection process. -The model needs to focus on the general details of their images in order to produce higher accuracies. -Blurring, thresholding, and…
Image Processing is used to perform some operations on images in order to animate them, develop videos, or generate graphics. To get started with data analysis, you can use image preprocessing feature engineering. It’s not difficult to extract useful information from images – this is accomplished via image processing methods. Reduction of noise, adjustment of…
1 – What is F1 score? F1 score is a measure of the accuracy of a model. It is defined as the harmonic mean of precision and recall. F1 score is one of the most popular metrics for assessing how well a machine learning algorithm performs on predicting a target variable. F1 score ranges from…
Histogram Equalizer is a computer vision technique that adjusts the luminosity levels of an image to make it more visually appealing. Histogram equalization is a process that lets us take an image and adjust the brightness levels so that each pixel in the image has a similar level of illumination. It does this by mapping…