Programming VIP

catalogue 1, Basic theory 1. Thought 2. Principle 2, Process Step induction 1. Convert the original image to binary image 2. Open operation denoising 3. Determine the background area (expansion) (get the background / maximum pass area) 4. Determine foreground area (distance transformation) (separation) (get seed / foreground) 5. U ...

1, HOG feature extraction principle    HOG feature extraction process can be divided into five parts: detection window, normalized image, calculating gradient, statistical histogram, normalization of gradient histogram, and obtaining HOG feature vector. Detection window:    HOG divides the image through window and blo ...

Answer card recognition project based on Opencv image recognition In the course of watching Mr. Tang Yudi's image processing, there is a small item of answer card recognition. Here, I will make a simple summary combined with my own understanding. 1. Project analysis First, when getting the project, analyze what the purpose of the project is, ...

The three neural networks described above are "series", just the continuous stacking of convolution layers, and the structure is relatively simple. The next two blogs will introduce the "parallel" structure in GoogLeNet and ResNet, which are also the last two neural networks to be introduced before officially entering the ta ...

preface The pioneering work of the VIT model is to use a pure transformer structure, as shown in the title of the paper: AN IMAGE IS WORTH 16X16 WORDS, which embeds the pictures into a series of sequence s, and realizes the effect comparable to the SOTA model in CNN through multiple encoder structures and head s. Image classification t ...

1 Introduction In the process of image processing, we often encounter some operations related to the object contour, such as calculating the perimeter area of the target contour. We can easily obtain the contour of each target by directly using the findContours function of Opencv, but after visualization, the order is disordered, as shown on t ...

02 introduction to deep learning What is the field of perception: the stage at which people can quickly perceive and process (English to Chinese). Deep learning, computer vision and natural language processing are the three largest contents in the field of AI. Application of deep learning Image classification (IMAGENET), at present, the erro ...

A vision project requires the jetson nano computing platform and intel realsense sr300 camera. We need to call it in python. After understanding, it can be configured in the following steps. 1: Install various dependent packages and check the corresponding versions 2: Download librealsense and compile build (this step is very important. Blogger ...

Supervised learning is a traditional method of training machine learning model. During training, every observed data needs to be labeled. What if we had a way to train machine learning models without collecting labels? What if we extract tags from the same data collected? This type of learning algorithm is called self supervised learning. This ...

Supervised learning is a traditional method of training machine learning model. During training, every observed data needs to be labeled. What if we had a way to train machine learning models without collecting labels? What if we extract tags from the same data collected? This type of learning algorithm is called self supervised learning. This ...