OpenCV using Raspberry Pi

OpenCV using Raspberry Pi

This workshop will provide training on OpenCV and image processing using Python. OpenCV (Open Source Computer Vision) is a library of programming functions mainly aimed at real-time computer vision. The library is cross-platform and free for use under the open-source BSD license. The Raspberry Pi is a tiny and affordable computer that students can use to learn programming through fun, practical projects. Pi will be used with Python, which is a programming language that lets the user work more quickly and integrate their systems more effectively. Students can learn to use Python and see almost immediate gains in productivity and lower maintenance costs.

Workshop Goal

To teach the basics of image processing, face detection and face recognition. The participants would be able to recognise objects, faces and identify faces with names. In the workshop, participants will be familiarised with Geometric Transformations of Images, Detecting Edges and applying image filters, cartooning an image, detecting and tracking different body parts, extracting features from an image, detecting shapes, object tracking and recognition.

Awards & Certificates

To keep the crowd interactive and active, the workshop would have tasks which would have marks associated with them. All the participants would be given certificate of participation. The best performing team would be chosen based on the highest rank and awarded with 'Certificate of Merit'. The certificates would be issued by PrismCode Info Solutions Pvt. Ltd. which can be validated internationally.

  1. Applying Geometric Transformations to Images
  2. Installing OpenCV on Pi
  3. Introduction to Raspberry Pi
  4. Basic configuration of Pi
  5. Python on Pi
  6. Reading, displaying, and saving images
  7. Image Color Spaces
  8. Image Translation, Rotation, Scaling, Affine Transformations and Projective Transformations
  9. Detecting Edges and Applying Image Filters
  10. Image Blurring, Edge detection, Motion Deblur, Sharpening, Embossing, Erosion and Dilation
  11. Cartooning an Image
  12. Accessing the Webcam
  13. Keyboard Inputs
  14. Mouse Inputs
  15. Interacting with a live video stream
  16. Detecting and Tracking Different Body Parts
  17. Using Haar cascades to Detect Things
  18. Detecting and Tracking Faces
  19. Detecting Eyes
  20. Extracting Features from an Image
  21. Detecting Shapes and Segmenting an Image
  22. Object Tracking
  23. Object Recognition
  24. Object Detection versus Object Recognition
  25. Visual Dictionary
  26. Frame Formation
  27. Face Detection
  28. Face Dictionary
  29. Face Recognition

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