Six new tutorials:

  • OpenCV3 Android application programming
    • Zero, preface,
    • Set OpenCV
    • Second, use camera frames
    • Three, the application of image effects
    • Recognition and tracking of images
    • Combine image tracking with 3D rendering
    • Mixing Java and C++ via JNI
  • OpenCV instant starter
    • OpenCV instant entry
  • Python Robot Learning Manual
    • Zero, preface,
    • I. Introduction to robot operating system
    • Second, understand the basis of differential robot
    • Three, modeling differential robot
    • Four, using ROS to simulate the differential robot
    • Design ChefBot hardware and circuit
    • Connect the actuator and sensor to the robot controller
    • Vii. Visual sensor and ROS interface
    • Viii. Build ChefBot hardware and software integration
    • 9. Use Qt and Python to design guIs for robots
    • Ten, evaluating,
  • OpenCV2 Computer vision application programming secrets
    • Zero, preface,
    • First, play with images
    • Second, manipulate pixels
    • 3. Use classes to process images
    • Use histogram to calculate pixels
    • 5. Transform image by morphological operation
    • Filter images
    • Extract straight lines, contours and parts
    • Detect and match points of interest
    • Estimate the projection relation in the image
    • Handling video sequences
  • Python OpenCV computer vision
    • Zero, preface,
    • Set OpenCV
    • Handle files, cameras and GUIs
    • Three, filter the image
    • Four, use Haar cascade to track human face
    • 5. Detect foreground/background area and depth
    • Appendix A: Integration with Pygame
    • Appendix B: Generate Haar cascades for custom targets
  • Python OpenCV blueprint
    • Zero, preface,
    • First, the fun of filters
    • Second, gesture recognition using Kinect depth sensor
    • Third, find objects through feature matching and perspective transformation
    • 4. Reconstruct 3D scenes with moving structures
    • Track visually significant objects
    • Learn to recognize traffic signs
    • Learn to recognize facial expressions

download

Docker

Docker pull apachecn0/apachecn-cv-zh docker run-tid -p <port>:80 apachecn0/apachecn-cv-zh # visit http://localhost:{port}Copy the code

PYPI

PIP install apachecn-cv-en apachecn-cv-en <port> # visit http://localhost:{port}Copy the code

NPM

NPM install -g apachecn-cv-zh apachecn-cv-zh <port> # visit http://localhost:{port}Copy the code

Contribution to guide

This project needs to be proofread, everyone is welcome to submit the Pull Request.

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