Computer vision is a field of artificial intelligence that deals with how computers can be made to understand and interpret visual data from the world around them. This can include tasks such as image and video recognition, object detection and tracking, and image and video generation.


Some of the biggest achievements done, using Computer Vision:

  • Facial recognition technology used in security systems and social media platforms
  • Object recognition and tracking in surveillance systems and video games
  • Medical image analysis for early detection of diseases and disorders
  • Improved robotics and automation in manufacturing and other industries
  • Improved image and video editing capabilities in photography and video production
  • Enhanced virtual and augmented reality experiences for gaming and other applications.
  • Development of self-driving cars and autonomous vehicles

The salary for a computer vision specialist can vary depending on factors such as experience level, location, and industry. According to Glassdoor, the average salary for a computer vision specialist is $85,973 per year in the United States. Even though there are cases where CV job positions can come with over $300,000 per year salaries.

So, with such high salaries and a chance to work on some modern projects, using cutting edge technology, this field is one of the most popular and most desired by many developers and scientists.

If you want to start learning and working with Computer Vision, we will recommend you to pick up the OpenCV library.

OpenCV (Open Source Computer Vision Library) is a free and open-source computer vision library with a focus on real-time computer vision. It is written in C++ and is designed to be used with various platforms such as desktop, mobile, and embedded systems. OpenCV is widely used in computer vision applications, including in industry, research, and academia. It provides a number of tools and functions for working with visual data, including machine learning algorithms for image and video analysis.
Despite being written in C++, you can use OpenCV with Python, Java, Matlab and obviously C++.

In this article we are going to show you how to start with OpenCV in Python, through a short 48 lines example, where we are going to try to detect movement in a video.

 

Write a Movement Detection Script using OpenCV in Python

 

import cv2

import numpy as np

 

# Load the video file

video = cv2.VideoCapture(“movement.mp4“)

 

# Check if the video was opened successfully

if not video.isOpened():

    print(“Error opening video file“)

    exit()

 

# Read the first frame of the video

success, frame = video.read()

 

# Check if the frame was read successfully

if not success:

    print(“Error reading video file“)

    exit()

 

# Convert the frame to grayscale

gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)

 

# Define the motion detector

detector = cv2.DualTVL1OpticalFlow_create()

”””Define the threshold. You can set different values depending on the sensitivity levels you want””” 

THRESHOLD = 3

# Keep reading frames until the video is completed

while video.isOpened():

    # Read the next frame

    success, frame = video.read()

    if not success:

        break

 

    # Convert the frame to grayscale

    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)

 

    # Compute the optical flow for the current frame

    flow = detector.calc(gray, None, None)

 

    # Compute the magnitude and angle of the flow vectors

    magnitude, angle = cv2.cartToPolar(flow[…, 0], flow[…, 1])

 

    # Check if the magnitude is above a threshold

    if magnitude.mean() > THRESHOLD:

        # If it is, then there is movement in the frame

        print(“Movement detected“)

 

# Release the video file

video.release()

 

In the code above, you can do movement detection in a mp4 format video. The two libraries you need to install are OpenCV and Numpy. The code is nicely explained through the comments, so we don’t need to repeat ourselves. Please, check it and share your results with us.

Conclusion

As we’ve mentioned already, this field is really interesting, challenging, well paid, but most importantly, it is the skill of the future. As you’ve seen in the intro part, it is used in every modern industry, so if you want to get your resume ready for what follows, we recommend you to dive into Computer Vision, or any other AI related field. 


We have some other Computer Vision articles here:

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