Learn computer vision from the basics

'Oh.. There's data! Looks like I'll be able to make it soon! '

“I even made a model. First of all, it was well-made! '

“But how do I show this to users?”

In fact, these words are irresponsible expressions.

In this class

Learn essential concepts for understanding images and images, such as pixels, resolution, and color space.

Build a solid foundation by conducting simple image processing exercises with OpenCV and Python.

You can also understand at a glance what computer vision is and the differences between traditional techniques and deep learning techniques.

The core of image preprocessing and object detection

Learn various pre-processing methods for dealing with data, such as color space conversion, filtering, and binarization.

Understand edge and outline detection principles and apply them to actual data.

Learn techniques that can be used directly in practice, from removing noise to identifying object boundaries.

In the Vision model, a simple data-push model,

We call this a black box, an unexplainable model.

Be more careful and let people's thoughts and judgments come out as much as possible.
In a black box white boxThe transition to.

Let's break through that limit by thinking together.