说明： 基于SVM的烟雾识别系统 运动区域提取使用的是 自适应混合高斯背景建模 特征算法使用的是 HOG+LBP 机器学习方法使用的是 scikit的SVM(Smoke recognition system based on SVM The moving region extraction uses adaptive Gaussian mixture background modeling feature algorithm, hog + LBP machine learning method and scikit SVM)
说明： 通过代码实现对图片和视频中车辆的检测与识别(Through the code to achieve the detection and recognition of vehicles in pictures and videos)
说明： 此代码简单易学，能有效检测烟雾，识别率高，机器学习。(This code is easy to learn, can effectively detect smoke, high recognition rate, machine learning.)
说明： 行人的检测使用库函数OpenCV里已经内置的行人检测方法，调用OpenCV预先训练好了的HOG+线性SVM模型，能够对图像和视频中的行人进行检测，系统会分别使用两种算法通过矩形条框将图片中的行人框出来。(Pedestrian detection uses the built-in pedestrian detection method in OpenCV library function, calling the pre-trained HOG + linear SVM model of OpenCV, which can detect the pedestrians in images and videos. The system uses two algorithms to frame the pedestrians in pictures through rectangular bars.)
可以利用python opencv实现获取图像上鼠标点击的点的像素的坐标(Python opencv can be used to obtain the coordinates of the pixels clicked by the mouse on the image)
说明： 可以利用python opencv实现获取图像上鼠标点击的点的像素的坐标(Python opencv can be used to obtain the coordinates of the pixels clicked by the mouse on the image)
基于python的opencv学习资料，非常适合入门者学习。(Opencv learning materials based on Python are very suitable for beginners.)
说明： 基于python的opencv学习资料，非常适合入门者学习。(Opencv learning materials based on Python are very suitable for beginners.)
手动选择三对特征点，标注特征点，实现二维图像的仿射配准；每完成一对需要按Q键进行下一对；平台是Spyter(Radiation registration by labeling feature points)
说明： 手动选择三对特征点，标注特征点，实现二维图像的仿射配准；每完成一对需要按Q键进行下一对；平台是Spyter(Radiation registration by labeling feature points)
说明： sift stitch基于opencv库的拼接算法小测试(sift stitch Small test of Mosaic algorithm based on opencv library)
sift stitch基于opencv库的拼接算法小测试(sift stitch Small test of Mosaic algorithm based on opencv library)
说明： opencv人脸识别例程，平时自学时编写，可当作笔记使用，忘记时拿出来翻翻(Opencv face recognition routine, usually written in self-study, can be used as notes, and can be taken out and turned over when forgetting)
说明： 基于OpenCV计算机视觉库，对进行全景图像拼接(Panoramic image mosaic based on OpenCV Computer Vision Library)
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