Python Resource Optimization Competency (Intermediate Level)

  • 12m
  • 12 questions
The Python Resource Optimization Competency (Intermediate Level) benchmark measures your ability to implement a variety of image manipulations using OpenCV to prepare images for end users or machine learning pipelines. You will be evaluated on your knowledge of representing streaming elements using Faust models, processing them using agents, and sending and receiving messages using channels. A learner who scores high on this benchmark demonstrates that they have the skills to manipulate images in OpenCV and perform stream processing using models, agents, and channels in Faust.

Topics covered

  • create masks and inverted masks from a grayscale image
  • create models with multiple fields and different data types
  • create streams manually using the .stream() method
  • define stream processors to transform stream elements
  • flip images vertically and horizontally and warp them using a specified perspective
  • invoke the cast() method to await processing results from an agent
  • publish messages to a Kafka topic using the pykafka library
  • rotate images by a specific angle around a specific center by generating a rotation matrix and applying an affine transformation
  • transform a color image to grayscale and then generate a mask from it
  • use channels to send and receive messages
  • use multiple agents for chained processing of data
  • use the cv2.resize() function to reduce the size of a color image