Tens of good tutorials are available online for image processing using OpenCV library. To name just a few of the cool functions in this library, there are cvtColor and filter2D. The Former, converts your image from one color space to another, whereas the latter convolves an image with a specific kernel.
While these libraries definitely make the life of a Computer Vision Engineer easier, it is not always enough to get the job done. I’ll let you in on a secret: In order to get a position as a Computer Vision or Image Processing Engineer, you would need to go through multiple tough interviews that may destroy your life or cause you to feel failure but I want you to know that you are certainly NOT FAILING. You just need to practice. Oh! It’s not a secret anymore :).
So, let me explain why knowledge of these libraries isn’t enough. If I ask you to convolve a kernel through an image, you can easily use filter2D, pass both the image and the kernel and show the output with a big smile on your face. BUT what if I give you the following input parameters:
void conv(const unsigned char* input_image, const int img_width, const int img_height, const char* kernel, const int kernel_size, unsigned char* output_image)
and ask you to convolve a kernel without using OpenCV. I suspect you won’t have that big smile on your face, you might even feel stressed, especially when the interviewer is waiting to hear your answer and asking Google for help is not an option :’(
Are you excited after that long boring introduction? I doubt. But believe me, if you want to get a position as a CV Engineer, and work on awesome projects in the realm of self-driving cars, virtual arts or autonomous drones, you should be an expert in solving these problems without the use of libraries. That being said, you may also need skills in deep learning and point cloud processing.
In this series of articles (sorry, I’m still struggling to write this first one but am feeling positive and motivated :D), I am going to practice implementing a few functions with you in a couple of different ways.
We will start with simple exercises and progress together as we take on more challenging problems.
YESSS, we want to get hired as Computer Vision Engineers.