OpenCV 4.0 with Python (English&中文) - Keep the Update!

OpenCV 4.0 Tutorial

Introduction

This repository contains source code of OpenCV Tutorial application, the environment is python3.0 and opencv4.0.

Sample

  • Image load ```python import cv2

src = cv2.imread("test.png") cv2.namedWindow("input", cv2.WINDOW_AUTOSIZE) cv2.imshow("input", src) cv2.waitKey(0) cv2.destroyAllWindows()

<div align=center><img src="https://i.loli.net/2019/05/22/5ce4b40258c9155103.jpg" width=200></div>

- **Gray Image**
```python
gray = cv2.cvtColor(src, cv.COLOR_BGR2GRAY)

More opencv4.0 tutorials plese follow the learning road as below 👇👇👇

Learning Road ⛳️

Annotation:

  • ✔️ : Basic
  • ✏️ : Attention
  • ❣️ : Important
NoDescriptionAnnotation
code_001Load Image✔️
code_002Gray Image✔️
code_003Image Create✔️
code_004Pixel Read and Write✔️
code_005Image Pixel Arithmetic Operations✔️
code_006Image Pseudo-Color Enhancement✔️
code_007Image Pixel Operation (Logical Operation)✔️
code_008Image Channel Separation and Merging✔️
code_009Color Space Conversion✏️
code_010Image Pixel Value Statistics✔️
code_011Image Pixel Normalization✔️
code_012Video Read and Write✔️
code_013Image Flip✔️
code_014Image Interpolation✔️
code_015Draw Geometry✔️
code_016ROI of Image✔️
code_017Image Histogram✔️
code_018Histogram Dqualization✏️
code_019Histogram Comparison✔️
code_020Histogram Backprojection✔️
code_021Image Convolution✔️
code_022Averaging and Gaussian Blur❣️
code_023Median Blur✔️
code_024Image Noise✔️
code_025Smoothing Images✔️
code_026Gaussian Bilateral Blur✔️
code_027Mean-shift Blur)✔️
code_028Image Integral Algorithm✔️
code_029Fast Image Edge Filtering Algorithm✔️
code_030Custom Filter✔️
code_031Sobel Operator✔️
code_032More Gradient Operators✔️
code_033Laplace Operator✔️
code_034Image Sharpening✔️
code_035USM Sharpen Algorithm✔️
code_036Canny Edge Detection❣️
code_037Image Pyramid✔️
code_038Laplace Pyramid✔️
code_039Image Template Matching✔️
code_040Binary introduction✔️
code_041Basic Thresholding✔️
code_042OTSU Thresholding✏️
code_043TRIANGLE Thresholding✔️
code_044Adaptive Thresholding✏️
code_045Binary and Smoothing✏️
code_046Image Connectivity component✔️
code_047Image Connected component state statistics✔️
code_048Image Contours❣️
code_049Bounding Rectangle❣️
code_050Contour Area and Perimeter✏️
code_051Contour Approximation✔️
code_052Contour Centroid Calculate✔️
code_053HuMoment for Contour Matching✔️
code_054Contour Cricle and Ellipse fitting✔️
code_055Convex Hull✏️
code_056Fitting a Line✔️
code_057Point Polygon Test✔️
code_058The Largest Inner Circle✔️
code_059Hoffman Line Detection✔️
code_060Probability Hoffman Line Detection❣️
code_061Hoffman Cricle Detection❣️
code_062Dilation and Erosion❣️
code_063Structuring Element✔️
code_064Opening Transformation✏️
code_065Closing Transformation✏️
code_066Application of Opening and Closing Operations✏️
code_067Top Hat✔️
code_068Black Hat✔️
code_069Morph Gradient✔️
code_070Contour based on Morph Gradient✏️
code_071Hit and Miss✔️
code_072Defect Detecting-1✔️
code_073Defect Detecting-2✔️
code_074Extract the Maximum Contour and Coding Key Points✔️
code_075Image Inpainting✔️
code_076Perspective Transformation✏️
code_077Video Read, Write and Process✏️
code_078Identify and Track Specific Color Objects in Video✔️
code_079Video Analysis-Background/Foreground Extraction✔️
code_080Video Analysis–Background Subtraction and ROI Extraction of the Foreground✔️
code_081Corner Detection-Harris✔️
code_082Corner Detection-Shi-Tomas✏️
code_083Corner Detection-Sub-Pixel✔️
code_084Video Analysis-KLT Optical Flow-1✏️
code_085Video Analysis-KLT Optical Flow-2✏️
code_086Video Analysis-Dense Optical Flow✏️
code_087Video Analysis-Frame Difference Moving Object Analysis✔️
code_088Video Analysis-Meanshift✏️
code_089Video Analysis-CamShift✏️
code_090Video Analysis-Object Movement Trajectory Drawing✔️
code_091Object Detection-HAAR Cascade Classification✔️
code_092Object Detection-HAAR Feature Analysis✔️
code_093Object Detection-LBP Feature Analysis✔️
code_094ORB Feature Critical Point Detection✏️
code_095ORB Feature Descriptor Matching✔️
code_096Multiple Descriptor Matching Methods✏️
code_097Location of Known Objects Based on Descriptor Matches✏️
code_098SIFT Feature Critical Point Detection✔️
code_099SIFT Feature Descriptor Matching✔️
code_100HOG Pedestrian Detection✔️
code_101HOG Multiscale Detection✏️
code_102HOG Extract Descriptor✔️
code_103HOG Use Descriptors to Generate Sample Data✔️
code_104(Detection Case)-HOG+SVM Train✔️
code_105(Detection Case)-HOG+SVM Predict✔️
code_106AKAZE Features and Descriptors✔️
code_107Brisk Features and Descriptors✔️
code_108GFTT Detector✔️
code_109BLOB Feature Analysis✔️
code_110KMeans Data Classification✔️
code_111KMeans Image Segmentation✔️
code_112KMeans Background Change✔️
code_113KMeans Extract Image Color Card✔️
code_114KNN Classification✔️
code_115KNN-Train Data Save and Load✔️
code_116Decision Tree Algorithm✔️
code_117Image Mean-shift Segmentation✔️
code_118Grabcut-Image Segmentation✔️
code_119Grabcut-Background Change✏️
code_120Qrcode detect and decode✏️
code_121DNN- Read the information of each layer of the model✔️
code_122DNN- Realize image classification✔️
code_123DNN- Model runs to set the target device and compute the background✔️
code_124DNN- SSD Single Image Detection✔️
code_125DNN- SSD Real-time Video Detection✔️
code_126DNN- Face Detection based on Residual Network✔️
code_127DNN- Video Face Detection based on Residual Network✔️
code_128DNN- Call the Detection Model of Tensorflow✔️
code_129DNN- Call the Openpose Implementation Attitude Assessment✔️
code_130DNN- Call YOLO Object Detection Network✔️
code_131DNN- YOLOv3-tiny Real-time Object Detection✔️
code_132DNN- Single and Multiple Image Detection✔️
code_133DNN- Colorful Image Colorization✔️
code_134DNN- ENet Image Segmentation✔️
code_135DNN- Real-time Fast Image Style Transfer✔️

Appendix

⛳️ The weight can be download from Google Driver:

🌱 Weight for DNN


Download Details:

Author: JimmyHHua 

Official Github: https://github.com/JimmyHHua/opencv_tutorials 

License

#opencv #python #english 

OpenCV 4.0 with Python (English&中文) - Keep the Update!
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