Deep Learning CNN Convolutional Neural Networks with Python - Image Processing Activity

The video tutorial guides students through implementing a custom 2D convolution function in Python. The function should handle both grayscale and RGB images, applying convolution without using built-in functions. Students are encouraged to use loops or Numpy for implementation, with a focus on understanding the convolution process. The tutorial also covers handling boundary conditions with zero padding. The activity aims to deepen students' understanding of image processing by building the function from scratch. The session concludes with a preview of the next module on object detection.

Explain the difference in processing between grayscale and RGB images in the context of convolution.

How should the function handle boundary pixels during convolution?