OpenCv4学习路线的点亮图谱——需要日常打卡

目录

总体分块

任务拆分

安装教学

课时安排

---

总体分块

1. OpenCv IO模块-（图像与视频读写）
2. GUI部分-（窗口与显示）
3. 图像处理基础知识
4. 卷积处理相关
5. 二值图像与图像分析
6. 特征提取与对象检测
7. 视频内容分析与跟踪
8. OpenCv深度神经网络-DNN模块
9. 案例学习与代码分享

任务拆分

1.    IO模块
2.    图像读写
3.    视频读写
4.    Mat与Numpy操作
5.    像素遍历与访问
6.    图像算术与几何操作
7.    图像查找表LUT
8.    伪彩色与颜色表
9.    图像通道合并与分离
10.    色彩空间转换
11.    像素统计
12.    像素归一化
13.    图像几何操作(翻转、旋转、放缩)
14.    图形绘制(线、矩形、圆、椭圆)
15.    图像规则ROI与不规则ROI
16.    图像直方图(均衡化、相似性、反向投影)
17.    卷积基本原理
18.    图像卷积(高斯、中值、均值)
19.    图像噪声与去噪
20.    边缘保留滤波(高斯双边、非局部均值、均值迁移)
21.    自定义滤波器与快速滤波
22.    图像梯度(sobel,scharr,robot,prewitt)
23.    拉普拉斯与USM
24.    Canny边缘检测
25.    图像金字塔(高斯与拉普拉斯)
26.    金字塔重建
27.    模板匹配
28.    图像二值化(全局阈值与自适应)
29.    图像连通组件分析（中心位置、外接矩形）
30.    图像轮廓发现（树形层次、编码方式、最小外接矩形、面积与周长）
31.    轮廓逼近与编码
32.    图像距(几何矩、中心矩、hu矩)
33.    轮廓拟合(直线/圆与椭圆)
34.    手势凸包检测
35.    霍夫变换(直线与圆)
36.    形态学基础(腐蚀、膨胀、开闭操作)
37.    形态学操作(梯度、击中击不中、顶帽与黑帽)
38.    二值图像分析案例(工业刀片缺陷检测)
39.    图像去水印与修复
40.    透视变换与几何变换
41.    视频分析-基于颜色的对象跟踪
42.    视频分析-移动对象前景与背景分析
43.    视频分析-背景消除与前景ROI提取
44.    视频分析-对象角点检测
45.    视频分析-KLT光流分析
46.    视频分析-帧差与三帧差法
47.    视频分析-FB稠密光流分析
48.    视频分析-均值迁移的移动对象跟踪
49.    视频分析-连续自适应的对象跟踪与轨迹绘制
50.    特征提取-LBP与HAAR特征
51.    特征提取-ORB Fast特征
52.    特征提取-BRIEF特征
53.    特征提取-特征描述子与匹配
54.    特征提取-SIFT特征
55.    特征提取-HOG特征与行人检测
56.    特征提取-AKAZE特征
57.    特征提取-Brisk特征
58.    特征提取-GFTTDetector特征
59.    特征分析-BLOB特征分析
60.    案例-基于HOG+SVM的自定义对象检测
61.    机器学习-KMeans数据分析
62.    机器学习-KMeans图像分割
63.    机器学习-KMeans主色彩提取
64.    案例-基于KMeans的背景替换
65.    机器学习-KNN算法与手写数字识别
66.    机器学习-决策树算法与手写数字识别
67.    机器学习-SVM算法与手写数字识别
68.    图像分割-均值迁移分割
69.    图像分割-Grabcut分割
70.    案例-基于Grabcut交互式分割的图像背景虚化
71.    对象检测-人脸检测
72.    对象检测-二维码检测
73.    深度神经网络-获取网络各层信息
74.    深度神经网络-使用图像分类模型实现图像分类
75.    深度神经网络-DNN模块计算后台设置
76.    深度神经网络-使用SSD对象检测模型实现对象检测
77.    深度神经网络-基于SSD的实时对象检测
78.    深度神经网络-基于残差网络的人脸检测
79.    深度神经网络-视频实时人脸检测
80.    深度神经网络-如何调用导出的tensorflow模型
81.    深度神经网络-调用openpose姿态与手势评估模型
82.    深度神经网络-YOLOv3对象检测网络运行 
83.    深度神经网络- YOLOv3-tiny版本对象检测网络运行 
84.    深度神经网络- 单张与多张图像推断
85.    深度神经网络- 图像颜色化模型使用
86.    深度神经网络- ENet图像分割
87.    深度神经网络- 图像快速风格化
88.    深度神经网络- 解析模型网络输出的各种结果
89.    案例-基于预训练模型的人脸检测与性别年龄预测
90.    案例-基于二值图像分析的数字识别

安装教学

http://space.bilibili.com/365916694/#/

课时安排

OpenCV-day-001. [图像读取与显示](https://t.zsxq.com/auvvV3f )
OpenCV-day-002. [图像色彩空间转换](https://t.zsxq.com/rrvNnI2 )
OpenCV-day-003. [图像对象的创建与赋值](https://t.zsxq.com/YjM3BUV )
OpenCV-day-004. [图像像素的读写操作](https://t.zsxq.com/Ybyb2bU )
OpenCV-day-005. [图像像素的算术操作](https://t.zsxq.com/u3Jam6y )
OpenCV-day-006. [LUT的作用与用法](https://t.zsxq.com/7yBEaIe )
OpenCV-day-007. [图像像素的逻辑操作](https://t.zsxq.com/ZbYnmMJ )
OpenCV-day-008. [通道分离与合并](https://t.zsxq.com/qZfQzf2 )
OpenCV-day-009. [图像色彩空间转换](https://t.zsxq.com/M3zVbaQ )
OpenCV-day-010. [图像像素值统计](https://t.zsxq.com/2vJYzRv )

OpenCV-day-011. [像素归一化](https://t.zsxq.com/UZnUrfm )
OpenCV-day-012. [视频文件的读写](https://t.zsxq.com/NBYzNJq )
OpenCV-day-013. [图像翻转](https://t.zsxq.com/BQ7EmUj )
OpenCV-day-014. [图像插值](https://t.zsxq.com/ZzfIEur )
OpenCV-day-015. [几何形状绘制](https://t.zsxq.com/FQnMjam )
OpenCV-day-016. [图像ROI与ROI操作](https://t.zsxq.com/zJuvVzJ )
OpenCV-day-017. [图像直方图](https://t.zsxq.com/nqR3Rvn )
OpenCV-day-018. [图像直方图均衡化](https://t.zsxq.com/nUr3BaI )
OpenCV-day-019. [图像直方图比较](https://t.zsxq.com/Vz3nEYJ )
OpenCV-day-020. [图像直方图反向投影](https://t.zsxq.com/v7MjEiu ) 

OpenCV-day-021. [图像卷积操作](https://t.zsxq.com/IAyRvB2 )
OpenCV-day-022. [图像均值与高斯模糊](https://t.zsxq.com/BURFM7Y )
OpenCV-day-023. [中值模糊](https://t.zsxq.com/y3z33vN )
OpenCV-day-024. [图像噪声](https://t.zsxq.com/6EQRjmq )
OpenCV-day-025. [图像去噪声](https://t.zsxq.com/2FEqRzN )
OpenCV-day-026. [高斯双边模糊](https://t.zsxq.com/iUVb2RZ )
OpenCV-day-027. [均值迁移模糊](https://t.zsxq.com/Nf2RNrZ )
OpenCV-day-028. [图像积分图算法](https://t.zsxq.com/AiEe2ZV )
OpenCV-day-029. [快速的图像边缘滤波算法](https://t.zsxq.com/f2NfUnA )
OpenCV-day-030. [OpenCV自定义的滤波器](https://t.zsxq.com/3J2BAYr ) 

OpenCV-day-031. [图像梯度–Sobel算子](https://t.zsxq.com/YZZRjQ3 )
OpenCV-day-032. [图像梯度–更多梯度算子](https://t.zsxq.com/amYRBQz )
OpenCV-day-033. [图像梯度–拉普拉斯算子]((https://t.zsxq.com/BYBEAQb )
OpenCV-day-034. [图像锐化](https://t.zsxq.com/jiaM7eA )
OpenCV-day-035. [USM锐化增强算法](https://t.zsxq.com/7UNvJyB )
OpenCV-day-036. [Canny边缘检测器](https://t.zsxq.com/RRr7mMB )
OpenCV-day-037. [图像金字塔](https://t.zsxq.com/N7iiMRf )
OpenCV-day-038. [拉普拉斯金字塔](https://t.zsxq.com/fUrzZfq )
OpenCV-day-039. [图像模板匹配](https://t.zsxq.com/2fEIMrJ )
OpenCV-day-040. [二值图像介绍](https://t.zsxq.com/RR33VBe ) 

OpenCV-day-041. [OpenCV中的基本阈值操作](https://t.zsxq.com/R3jiAey )
OpenCV-day-042. [OTSU二值寻找算法](https://t.zsxq.com/Q3bMJIu )
OpenCV-day-043. [TRIANGLE二值寻找算法](https://t.zsxq.com/u7QFAM7 )
OpenCV-day-044. [自适应阈值算法](https://t.zsxq.com/i6IQfey )
OpenCV-day-045. [图像二值化与去噪](https://t.zsxq.com/7UZRVrb )
OpenCV-day-046. [二值图像联通组件寻找](https://t.zsxq.com/UVbEYrZ )
OpenCV-day-047. [二值图像连通组件状态统计](https://t.zsxq.com/mam2jiI )
OpenCV-day-048. [二值图像分析—轮廓发现](https://t.zsxq.com/ybEYVFU )
OpenCV-day-049. [二值图像分析—轮廓外接矩形](https://t.zsxq.com/7UJyJqV )
OpenCV-day-050. [二值图像分析 – 矩形面积与弧长](https://t.zsxq.com/2N7AujY ) 2019/4/17

OpenCV-day-051. [二值图像分析—使用轮廓逼近](https://t.zsxq.com/3biQZ33 )
OpenCV-day-052. [二值图像分析—用几何矩计算轮廓中心与横纵比过滤](https://t.zsxq.com/B2BAqji )
OpenCV-day-053. [二值图像分析—Hu矩实现轮廓匹配](https://t.zsxq.com/UbIyrbA )
OpenCV-day-054. [二值图像分析—对轮廓圆与椭圆拟合](https://t.zsxq.com/eujYbuN )
OpenCV-day-055. [二值图像分析—凸包检测](https://t.zsxq.com/7aIyjQJ )
OpenCV-day-056. [二值图像分析–直线拟合与极值点寻找](https://t.zsxq.com/AMvjMrB )
OpenCV-day-057. [二值图像分析—点多边形测试](https://t.zsxq.com/J2jAee6 )
OpenCV-day-058. [二值图像分析—寻找最大内接圆](https://t.zsxq.com/Vz3rzbE )
OpenCV-day-059. [二值图像分析—霍夫直线检测](https://t.zsxq.com/6Yv3NFq )
OpenCV-day-060. [二值图像分析—霍夫直线检测二](https://t.zsxq.com/ei6IMf6 )

OpenCV-day-061. [二值图像分析—霍夫圆检测](https://t.zsxq.com/YRnyznE )
OpenCV-day-062. [图像形态学—膨胀与腐蚀](https://t.zsxq.com/Jeyvjqn )
OpenCV-day-063. [图像形态学—膨胀与腐蚀](https://t.zsxq.com/BMz3vfu )
OpenCV-day-064. [图像形态学—开操作](https://t.zsxq.com/aeqZFUb )
OpenCV-day-065. [图像形态学—闭操作](https://t.zsxq.com/3b6qJQZ )
OpenCV-day-066. [图像形态学—开闭操作时候结构元素应用演示](https://t.zsxq.com/EQzFqB2 )
OpenCV-day-067. [图像形态学—顶帽操作](https://t.zsxq.com/URj27ae )
OpenCV-day-068. [图像形态学—黑帽操作](https://t.zsxq.com/6uZ376M )
OpenCV-day-069. [图像形态学—图像梯度](https://t.zsxq.com/3rJQbmA )
OpenCV-day-070. [形态学应用—用基本梯度实现轮廓分析](https://t.zsxq.com/Uvr3rBy )

OpenCV-day-071. [形态学操作—击中击不中](https://t.zsxq.com/vniEQ33 )
OpenCV-day-072. [二值图像分析—缺陷检测一](https://t.zsxq.com/yNN76YJ )
OpenCV-day-073. [二值图像分析—缺陷检测二](https://t.zsxq.com/eIMbmY3 )
OpenCV-day-074. [二值图像分析—提取最大轮廓与编码关键点](https://t.zsxq.com/yf6u33B )
OpenCV-day-075. [图像去水印/修复]( https://t.zsxq.com/EIUBIaA )
OpenCV-day-076. [图像透视变换应用](https://t.zsxq.com/QnyfmQR )
OpenCV-day-077. [视频读写与处理](https://t.zsxq.com/YrfUJ2r )
OpenCV-day-078. [识别与跟踪视频中的特定颜色对象](https://t.zsxq.com/AQ7UBie )
OpenCV-day-079. [视频分析—背景/前景提取](https://t.zsxq.com/baQbIa6 )
OpenCV-day-080. [视频分析—背景消除与前景ROI提取](https://t.zsxq.com/UfeAUNf ) 

OpenCV-day-081. [角点检测—Harris角点检测](https://t.zsxq.com/Z3jiYJa )
OpenCV-day-082. [角点检测—shi-tomas角点检测](https://t.zsxq.com/buVJAUV )
OpenCV-day-083. [角点检测—亚像素级别角点检测](https://t.zsxq.com/bAmi2Ba )
OpenCV-day-084. [视频分析—移动对象的KLT光流跟踪算法](https://t.zsxq.com/eeybEem )
OpenCV-day-085. [视频分析—KLT光流跟踪 02](https://t.zsxq.com/EqrJ2bU )
OpenCV-day-086. [视频分析—稠密光流分析](https://t.zsxq.com/nMjIQzn )
OpenCV-day-087. [视频分析—基于帧差法实现移动对象分析](https://t.zsxq.com/rRZNRzV )
OpenCV-day-088. [视频分析—基于均值迁移的对象移动分析](https://t.zsxq.com/bmM7ea6 )
OpenCV-day-089. [视频分析—基于连续自适应均值迁移的对象移动分析](https://t.zsxq.com/IaEUnYF )
OpenCV-day-090. [视频分析—对象移动轨迹绘制](https://t.zsxq.com/RjYRFQV ) 

OpenCV-day-091. [对象检测—HAAR级联检测器使用](https://t.zsxq.com/RBMVvbA )
OpenCV-day-092. [对象检测—HAAR特征介绍](https://t.zsxq.com/b2fAIuV )
OpenCV-day-093. [对象检测—LBP特征介绍](https://t.zsxq.com/amIMnuz )
OpenCV-day-094. [ORB FAST特征关键点检测](https://t.zsxq.com/aQByrZB )
OpenCV-day-095. [BRIEF特征描述子 匹配](https://t.zsxq.com/nIEmQB6 )
OpenCV-day-096. [描述子匹配](https://t.zsxq.com/vRFi6Ie )
OpenCV-day-097. [基于描述子匹配的已知对象定位](https://t.zsxq.com/mq7aQfy )
OpenCV-day-098. [SIFT特征提取—关键点提取](https://t.zsxq.com/VRrN7AM )
OpenCV-day-099. [SIFT特征提取—描述子生成](https://t.zsxq.com/6MJYN7A )
OpenCV-day-100. [HOG特征与行人检测](https://t.zsxq.com/jm6MJQV )

OpenCV-day-101. [HOG特征描述子—多尺度检测](https://t.zsxq.com/UNZvZ7i )
OpenCV-day-102. [HOG特征描述子—提取描述子](https://t.zsxq.com/6qzvJAU )
OpenCV-day-103. [HOG特征描述子—使用描述子特征生成样本数据](https://t.zsxq.com/JAAqBYv )
OpenCV-day-104. [SVM线性分类器](https://t.zsxq.com/AyZNZN7 )
OpenCV-day-105. [HOG特征描述子—使用HOG进行对象检测](https://t.zsxq.com/NJyZvB2 )
OpenCV-day-106. [AKAZE特征与描述子](https://t.zsxq.com/ZVznUV3 )
OpenCV-day-107. [Brisk特征提取与描述子匹配](https://t.zsxq.com/EAyNBIy )
OpenCV-day-108. [特征提取之关键点检测—GFTTDetector](https://t.zsxq.com/UBQBIQj )
OpenCV-day-109. [BLOB特征分析—simpleblobdetector使用](https://t.zsxq.com/VFM3vZ3 )
OpenCV-day-110. [KMeans 数据分类](https://t.zsxq.com/vnU7eIA)

OpenCV-day-111. [KMeans图像分割](https://t.zsxq.com/YjMrN7m)
OpenCV-day-112. [KMeans图像分割—背景替换](https://t.zsxq.com/UF23v7y)
OpenCV-day-113. [KMeans图像分割—主色彩提取](https://t.zsxq.com/Fi6aA2B)
OpenCV-day-114. [KNN算法介绍](https://t.zsxq.com/3R3jAI6 )
OpenCV-day-115. [KNN算法应用](https://t.zsxq.com/6uJyfQb )
OpenCV-day-116. [决策树算法 介绍与使用](https://t.zsxq.com/FqnQrz7 )
OpenCV-day-117. [图像均值漂移分割](https://t.zsxq.com/IyjuRFa )
OpenCV-day-118. [Grabcut图像分割](https://t.zsxq.com/Yj2jY3B )
OpenCV-day-119. [Grabcut图像分割—背景替换](https://t.zsxq.com/IiuRbUN )
OpenCV-day-120. [二维码检测与识别](https://t.zsxq.com/nqZR3JM )

OpenCV-day-121. [OpenCV DNN 获取导入模型各层信息](https://t.zsxq.com/UrVjUZJ )
OpenCV-day-122. [OpenCV DNN 实现图像分类](https://t.zsxq.com/VvV7EAu )
OpenCV-day-123. [OpenCV DNN 为模型运行设置目标设备与计算后台](https://t.zsxq.com/Fqjm6Eq )
OpenCV-day-124. [OpenCV DNN 基于SSD实现对象检测](https://t.zsxq.com/bEaIQFQ )
OpenCV-day-125. [OpenCV DNN 基于SSD实现实时视频检测](https://t.zsxq.com/IAMNVRv )
OpenCV-day-126. [OpenCV DNN 基于残差网络的人脸检测](https://t.zsxq.com/RjmEamM )
OpenCV-day-127. [OpenCV DNN 基于残差网络的视频人脸检测](https://t.zsxq.com/EMz3bqz )
OpenCV-day-128. [OpenCV DNN 直接调用tensorflow的导出模型](https://t.zsxq.com/aEUVVFI )
OpenCV-day-129. [OpenCV DNN 调用openpose模型实现姿态评估](https://t.zsxq.com/y7mufau )
OpenCV-day-130. [OpenCV DNN 支持YOLO对象检测网络运行](https://t.zsxq.com/QNVbaY3 )

OpenCV-day-131. [OpenCV DNN 支持YOLOv3-tiny版本实时对象检测](https://t.zsxq.com/fAAy3Jy )
OpenCV-day-132. [OpenCV DNN单张与多张图像的推断](https://t.zsxq.com/VBa2VFm )
OpenCV-day-133. [OpenCV DNN 图像颜色化模型使用](https://t.zsxq.com/NBiaqja )
OpenCV-day-134. [OpenCV DNN ENet实现图像分割](https://t.zsxq.com/VrrfiIu )
OpenCV-day-135. [OpenCV DNN 实时快速的图像风格迁移](https://t.zsxq.com/aIUJAAa )
OpenCV-day-136. [OpenCV DNN解析网络输出结果](https://t.zsxq.com/i62ZFeI )
OpenCV-day-137. [OpenCV DNN 实现性别与年龄预测](https://t.zsxq.com/uVNVv3B )
OpenCV-day-138. [OpenCV DNN 使用OpenVINO加速](https://t.zsxq.com/qFyFI2F )
OpenCV-day-139. [案例：识别0～9印刷体数字 —Part1](https://t.zsxq.com/QfYJQvn )
OpenCV-day-140. [案例：识别0～9印刷体数字 —Part2](https://t.zsxq.com/bM37mqz )

二值分析: 车道线检测 https://t.zsxq.com/nMFqNj6
OpenCV DNN:人脸识别 https://t.zsxq.com/uZB2BqZ
视频处理: 绿幕抠图 https://t.zsxq.com/zbMRZRv
图像处理: 分水岭分割案例 https://t.zsxq.com/rNVznAU