Notes on robotics, vision, and systems.
Since the NexT theme has been updated several times, many resources said to modify the custom.styl configuration file. However, my theme did not contain this file. After consulting a great deal of material, I finally found the location of the sidebar configuration file.
In Hexo, there are generally two _config.yml files—one in the root directory, which I call the site configuration file, and one in the theme directory, which I call the theme configuration file. This article covers settings such as theme switching, menu configuration, sidebar configuration, author avatar, social links, site name, author name, Chinese/English switching, number of posts shown on the homepage, and translation settings.
First, create the Categories and Tags pages as described below. Then, create a .md file in the source\_posts directory to create a new blog post. Add the following code at the beginning of the post to assign categories and tags; the annotations explain the purpose of each section.
First, download all the files in `opencv/samples/dnn/face_detector/` from OpenCV's GitHub site and overwrite the files in the local directory. Then open weights.meta4 in Notepad and download the files corresponding to the two URLs it contains.
Mean filtering uses the principle of image convolution. As shown in the figure below, when the convolution kernel is a third-order unit matrix, mean filtering is performed: each third-order submatrix of the original image has its mean computed and assigned to the center element.
An image histogram is a statistical feature of image pixel values. It is inexpensive to compute and has many advantages, including invariance to image translation, rotation, and scaling. It is widely used across image processing, especially for grayscale image thresholding, color-based image retrieval, image classification, and backprojection tracking. Common types are grayscale histograms and color histograms.
Reading and processing video is essential in image processing. In OpenCV, the main function used to read camera video is capture(). This article explains how to read camera video with OpenCV and describes the functions used to save it, including their implementation and specific details.
Common image transformation methods include image scaling, flipping, and rotation. In OpenCV, each of these image transformation operations has a corresponding function. This article introduces various image transformation methods through explanations of function definitions and concrete examples.
Normalization constrains the data to be processed, after processing (via some algorithm), within a certain range. This makes later data processing easier and also helps the program converge faster during runtime.
This article introduces how to handle keyboard and mouse input in OpenCV, the functions involved, and the parameters of each function. It also uses keyboard and mouse input handling to create several interesting small programs.
