How To Learn Computer Vision?

Computer vision is a subfield of artificial intelligence that is used to train a computer to see, process, and identify what is inside an image or video, just like humans. In this article, I will take you through a complete roadmap on how to learn computer vision.

What is Computer Vision?

In Machine Learning, we train our system to learn from data to classify or predict labels. Much like machine learning, in computer vision, we train a system to process an image to understand what’s inside an image or video, just like humans. The ability of a computer system, web application, software application, or any type of programmed system to understand an image or video like humans is known as computer vision.

Computer vision is not new, as it is already used in a wide variety of applications to solve business problems such as:

1. Optical Character Recognition
2. Machine Inspection
3. Object Recognition
4. 3D Model Building
5. Medical Imaging
6. Automotive Safety
7. Motion Capture
8. Fingerprint Recognition
9. Face Detection
10. Visual Authentication and many more.

How To Learn Computer Vision?

Hope you now understand what computer vision is and where it is used today. In this section, I will introduce you to a complete roadmap for learning computer vision step by step.

Just like machine learning, computer vision also has many topics. First, I will start with the topics you need to learn for computer vision and then I will move to the tools and frameworks you need to learn to implement the concepts of computer vision practically. So below are the topics of computer vision that you need to learn step by step:

1. Mathematics
   1. Probability
   2. Statistics
   3. Linear Algebra
   4. Calculus
2. Fundamentals of Computer Science
   1. Programming Language (Python/Java/C++/JavaScript)
   2. Machine Learning Algorithms
   3. Neural Networks
3. Data Science
   1. Data Collection
   2. Data Preparation
   3. Data Augmentation
   4. Data Annotation
4. Image and Video Processing
   1. Image Classification
   2. Object Detection
   3. Object Tracking
   4. Image Captioning
   5. Image Segmentation
   6. Action Recognition
   7. Video Processing
   8. Video Captioning

So these were the topics you need to learn to understand the concepts of computer vision. Now, to implement the computer vision concepts mentioned above, you must first learn a programming language. The most popular programming languages for computer vision are Python, C++, and JavaScript. I use Python because it is easy to learn and the support of libraries makes it more user friendly.

Python Libraries and Frameworks

So assuming that you are also using the Python programming language to implement the concepts of computer vision, below are the Python libraries and frameworks that you need to learn for computer vision:

1. NumPy
2. Pandas
3. skimage
4. Pillow
5. OpenCV
6. TensorFlow
7. PyTorch

So this was the complete roadmap that you need for learning computer vision using the Python programming language. I hope you liked this article on how to start with computer vision. Feel free to ask your valuable questions in the comments section below.