opencv_tutorials
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Published
20 hours ago •
JimmyHHua
JimmyHHua
Opencv4.0 with python (English&中文)， and will keep the update ! 👊
OpenCV 4.0 Tutorial
✒️ 中文版本
Introduction
This repository contains source code of OpenCV Tutorial application, the environment is python3.0 and opencv4.0.
Sample
- Image load
import cv2
src = cv2.imread("test.png")
cv2.namedWindow("input", cv2.WINDOW_AUTOSIZE)
cv2.imshow("input", src)
cv2.waitKey(0)
cv2.destroyAllWindows()
- Gray Image
gray = cv2.cvtColor(src, cv.COLOR_BGR2GRAY)
More opencv4.0 tutorials plese follow the learning road as below 👇👇👇
Learning Road ⛳️
Annotation:
- ✔️ : Basic
- ✏️ : Attention
- ❣️ : Important
| No | Description | Annotation |
|---|---|---|
| code_001 | Load Image | ✔️ |
| code_002 | Gray Image | ✔️ |
| code_003 | Image Create | ✔️ |
| code_004 | Pixel Read and Write | ✔️ |
| code_005 | Image Pixel Arithmetic Operations | ✔️ |
| code_006 | Image Pseudo-Color Enhancement | ✔️ |
| code_007 | Image Pixel Operation (Logical Operation) | ✔️ |
| code_008 | Image Channel Separation and Merging | ✔️ |
| code_009 | Color Space Conversion | ✏️ |
| code_010 | Image Pixel Value Statistics | ✔️ |
| code_011 | Image Pixel Normalization | ✔️ |
| code_012 | Video Read and Write | ✔️ |
| code_013 | Image Flip | ✔️ |
| code_014 | Image Interpolation | ✔️ |
| code_015 | Draw Geometry | ✔️ |
| code_016 | ROI of Image | ✔️ |
| code_017 | Image Histogram | ✔️ |
| code_018 | Histogram Dqualization | ✏️ |
| code_019 | Histogram Comparison | ✔️ |
| code_020 | Histogram Backprojection | ✔️ |
| code_021 | Image Convolution | ✔️ |
| code_022 | Averaging and Gaussian Blur | ❣️ |
| code_023 | Median Blur | ✔️ |
| code_024 | Image Noise | ✔️ |
| code_025 | Smoothing Images | ✔️ |
| code_026 | Gaussian Bilateral Blur | ✔️ |
| code_027 | Mean-shift Blur) | ✔️ |
| code_028 | Image Integral Algorithm | ✔️ |
| code_029 | Fast Image Edge Filtering Algorithm | ✔️ |
| code_030 | Custom Filter | ✔️ |
| code_031 | Sobel Operator | ✔️ |
| code_032 | More Gradient Operators | ✔️ |
| code_033 | Laplace Operator | ✔️ |
| code_034 | Image Sharpening | ✔️ |
| code_035 | USM Sharpen Algorithm | ✔️ |
| code_036 | Canny Edge Detection | ❣️ |
| code_037 | Image Pyramid | ✔️ |
| code_038 | Laplace Pyramid | ✔️ |
| code_039 | Image Template Matching | ✔️ |
| code_040 | Binary introduction | ✔️ |
| code_041 | Basic Thresholding | ✔️ |
| code_042 | OTSU Thresholding | ✏️ |
| code_043 | TRIANGLE Thresholding | ✔️ |
| code_044 | Adaptive Thresholding | ✏️ |
| code_045 | Binary and Smoothing | ✏️ |
| code_046 | Image Connectivity component | ✔️ |
| code_047 | Image Connected component state statistics | ✔️ |
| code_048 | Image Contours | ❣️ |
| code_049 | Bounding Rectangle | ❣️ |
| code_050 | Contour Area and Perimeter | ✏️ |
| code_051 | Contour Approximation | ✔️ |
| code_052 | Contour Centroid Calculate | ✔️ |
| code_053 | HuMoment for Contour Matching | ✔️ |
| code_054 | Contour Cricle and Ellipse fitting | ✔️ |
| code_055 | Convex Hull | ✏️ |
| code_056 | Fitting a Line | ✔️ |
| code_057 | Point Polygon Test | ✔️ |
| code_058 | The Largest Inner Circle | ✔️ |
| code_059 | Hoffman Line Detection | ✔️ |
| code_060 | Probability Hoffman Line Detection | ❣️ |
| code_061 | Hoffman Cricle Detection | ❣️ |
| code_062 | Dilation and Erosion | ❣️ |
| code_063 | Structuring Element | ✔️ |
| code_064 | Opening Transformation | ✏️ |
| code_065 | Closing Transformation | ✏️ |
| code_066 | Application of Opening and Closing Operations | ✏️ |
| code_067 | Top Hat | ✔️ |
| code_068 | Black Hat | ✔️ |
| code_069 | Morph Gradient | ✔️ |
| code_070 | Contour based on Morph Gradient | ✏️ |
| code_071 | Hit and Miss | ✔️ |
| code_072 | Defect Detecting-1 | ✔️ |
| code_073 | Defect Detecting-2 | ✔️ |
| code_074 | Extract the Maximum Contour and Coding Key Points | ✔️ |
| code_075 | Image Inpainting | ✔️ |
| code_076 | Perspective Transformation | ✏️ |
| code_077 | Video Read, Write and Process | ✏️ |
| code_078 | Identify and Track Specific Color Objects in Video | ✔️ |
| code_079 | Video Analysis-Background/Foreground Extraction | ✔️ |
| code_080 | Video Analysis–Background Subtraction and ROI Extraction of the Foreground | ✔️ |
| code_081 | Corner Detection-Harris | ✔️ |
| code_082 | Corner Detection-Shi-Tomas | ✏️ |
| code_083 | Corner Detection-Sub-Pixel | ✔️ |
| code_084 | Video Analysis-KLT Optical Flow-1 | ✏️ |
| code_085 | Video Analysis-KLT Optical Flow-2 | ✏️ |
| code_086 | Video Analysis-Dense Optical Flow | ✏️ |
| code_087 | Video Analysis-Frame Difference Moving Object Analysis | ✔️ |
| code_088 | Video Analysis-Meanshift | ✏️ |
| code_089 | Video Analysis-CamShift | ✏️ |
| code_090 | Video Analysis-Object Movement Trajectory Drawing | ✔️ |
| code_091 | Object Detection-HAAR Cascade Classification | ✔️ |
| code_092 | Object Detection-HAAR Feature Analysis | ✔️ |
| code_093 | Object Detection-LBP Feature Analysis | ✔️ |
| code_094 | ORB Feature Critical Point Detection | ✏️ |
| code_095 | ORB Feature Descriptor Matching | ✔️ |
| code_096 | Multiple Descriptor Matching Methods | ✏️ |
| code_097 | Location of Known Objects Based on Descriptor Matches | ✏️ |
| code_098 | SIFT Feature Critical Point Detection | ✔️ |
| code_099 | SIFT Feature Descriptor Matching | ✔️ |
| code_100 | HOG Pedestrian Detection | ✔️ |
| code_101 | HOG Multiscale Detection | ✏️ |
| code_102 | HOG Extract Descriptor | ✔️ |
| code_103 | HOG Use Descriptors to Generate Sample Data | ✔️ |
| code_104 | (Detection Case)-HOG+SVM Train | ✔️ |
| code_105 | (Detection Case)-HOG+SVM Predict | ✔️ |
| code_106 | AKAZE Features and Descriptors | ✔️ |
| code_107 | Brisk Features and Descriptors | ✔️ |
| code_108 | GFTT Detector | ✔️ |
| code_109 | BLOB Feature Analysis | ✔️ |
| code_110 | KMeans Data Classification | ✔️ |
| code_111 | KMeans Image Segmentation | ✔️ |
| code_112 | KMeans Background Change | ✔️ |
| code_113 | KMeans Extract Image Color Card | ✔️ |
| code_114 | KNN Classification | ✔️ |
| code_115 | KNN-Train Data Save and Load | ✔️ |
| code_116 | Decision Tree Algorithm | ✔️ |
| code_117 | Image Mean-shift Segmentation | ✔️ |
| code_118 | Grabcut-Image Segmentation | ✔️ |
| code_119 | Grabcut-Background Change | ✏️ |
| code_120 | Qrcode detect and decode | ✏️ |
| code_121 | DNN- Read the information of each layer of the model | ✔️ |
| code_122 | DNN- Realize image classification | ✔️ |
| code_123 | DNN- Model runs to set the target device and compute the background | ✔️ |
| code_124 | DNN- SSD Single Image Detection | ✔️ |
| code_125 | DNN- SSD Real-time Video Detection | ✔️ |
| code_126 | DNN- Face Detection based on Residual Network | ✔️ |
| code_127 | DNN- Video Face Detection based on Residual Network | ✔️ |
| code_128 | DNN- Call the Detection Model of Tensorflow | ✔️ |
| code_129 | DNN- Call the Openpose Implementation Attitude Assessment | ✔️ |
| code_130 | DNN- Call YOLO Object Detection Network | ✔️ |
| code_131 | DNN- YOLOv3-tiny Real-time Object Detection | ✔️ |
| code_132 | DNN- Single and Multiple Image Detection | ✔️ |
| code_133 | DNN- Colorful Image Colorization | ✔️ |
| code_134 | DNN- ENet Image Segmentation | ✔️ |
| code_135 | DNN- Real-time Fast Image Style Transfer | ✔️ |
Appendix
⛳️ The weight can be download from Google Driver：
JimmyHHua