The svm algorithm has been provided in opencv to achieve multi-classification of images. The task of using the svm algorithm to classify images is mostly used in scenes with simple scenes and time requirements, because the svm training of opencv generally only takes a short time to complete the training task. . However, there is currently no tool on the Internet that can solve the training problem very well. Most of them need to program themselves to achieve the training tasks. This is very unfriendly to newcomers who are new to opencv. Some of them can’t even write code or refer to the code written by others. It cannot run normally. Even if the trained model is incorrect, even if the model is trained correctly, calling it is still difficult. For this purpose, a software is developed to achieve one-click fool-like training without writing any code to complete the training task. You only need to prepare your own pictures to complete a model training. In addition, the software provides calling cases and supports C#, C++ and python calling. , first of all, before opening the training, you need to prepare a directory and pictures in a unified format. It is required that the pictures and directories should not have Chinese characters and spaces. For example, the following folder access method:
Then we open the software and click FIRC.exe to open:
Then we select the folder where the picture is located and the directory where you want to save the model. Finally, click Start Training to train your own model. It only takes 8 seconds to test 900 images to train a model! For more detailed usage tutorials, please refer to:
svm fast training assistant tutorial C++ python C# svm training calls the model for image classification_bilibili_bilibili This is a multi-class image classification model training used on Windows using the svm algorithm in Opencv. The trained model supports C++, C#, python, etc. are called, and corresponding programming test samples are provided to train svm image classification to operate in a fool-proof manner. There is no need to write code in the whole process. You only need to write simple code to implement the svm algorithm for image classification tasks! , video views 7, comments 0, likes 0, coins tossed 0, favorites 0, forwards 0, video author Future Independent Research Center, author profile Future Independent Research Center, related videos: C# realizes the entire network Yolov7 is currently the fastest winform target detection, using C++ to deploy yolov8's onnx and bytetrack to achieve target tracking, please listen! I have a Python script to grab train tickets, but I don’t recommend you use it! 600,000 people swipe 12,306 tickets per second, revealing the principle of ticket grabbing, using C# to deploy yolov8's tensorrt model for target detection, the fastest detection speed of winform, C# calling yolov7 for target detection winform development, [Russian programming teaching] up to two minutes The pretty girl teaches you C++, video demonstration of target tracking based on yolov8+bytetrack, tesseract-ocr fast training assistant, [Python] to easily crack WiFi passwords and surf the Internet anytime and anywhere (source code attached)! ! ! , based on yolov8 official target tracking botsort and bytetrack source code development video demonstration 
https://www.bilibili.com/video/BV1tH4y1f7mR