Data Science and Machine Learning (Theory and Projects) A to Z - Image Processing: Image Processing Activity

The video tutorial guides students through an activity to implement a custom 2D convolution function in Python. The function should handle both grayscale and RGB images without using built-in convolution functions. Students are encouraged to use loops or Numpy for implementation, and to apply zero padding for boundaries. The tutorial emphasizes understanding convolution from scratch and provides detailed instructions for processing different image types. The activity aims to deepen students' understanding of image processing and prepare them for future modules on object detection.

Explain why the implementation of the convolve 2D function might be slow.

What are the boundary conditions you should assume when implementing the convolution?