Python Resource Optimization Awareness

  • 22m 30s
  • 15 questions
The Python Resource Optimization Awareness benchmark will measure your ability to read images from file system into Python source and analyze and process using OpenCV and Faust. You will be evaluated on your ability to recognize fundamental concepts related to computer vision and the basic operations performed on images using OpenCV. A learner who scores high on this benchmark demonstrates that they have the skills to perform basic operations such as add and subtract using two images and to perform stream processing through windowing operations in Faust.

Topics covered

  • access raw events and buffer events before performing operations
  • aggregate data on a per-key, per-window basis
  • apply cv2.resize() function to scale up an image along individual dimensions
  • create models with multiple fields and different data types
  • flip images vertically and horizontally and warp them using a specified perspective
  • handle GET, PUT, POST, DELETE, and HTTP requests with web views
  • introduce a text element, polygon, and arrow to an OpenCV image
  • list the components that make up the architecture of a stream processing system
  • load images into an OpenCV array from your local storage and also save an array into a local file
  • perform Gaussian and median blur operations to smoothen an image
  • perform grouping operations and understand table sharding
  • transform a color image to grayscale and then generate a mask from it
  • use channels to send and receive messages
  • use the add and add weighted operations in OpenCV to combine two images
  • use the 'faust' command to run workers and send messages to agents

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