How to Compute the Aspect Ratio of an Object in an Image using OpenCV Python?

OpenCV is a popular computer vision library that is widely used for various applications such as image and video processing, object detection, facial recognition, and much more. In this tutorial, we will learn how to compute the aspect ratio of an object in an image using OpenCV Python.

The aspect ratio of an object is the ratio of the width to the height of the object. It is an important feature of an object and can be used for various applications such as object recognition, classification, and tracking.

Installing OpenCV Python

Before we start, we need to install OpenCV Python on our system. Here are the steps to install OpenCV Python using pip.

pip install opencv-python

Reading an Image

The first step is to read an image using OpenCV Python. We can use the cv2.imread() function to read an image.

import cv2

# Read the image
img = cv2.imread('img.jpg')

# Display the image
cv2.imshow('Image', img)

# Wait for key press
cv2.waitKey(0)

In the above code, we have read an image using the cv2.imread() function and displayed the image using the cv2.imshow() function. We have also used the cv2.waitKey() function to wait for a key press.

Computing the Aspect Ratio

To compute the aspect ratio of an object in an image, we need to first detect the object in the image. We can use various object detection algorithms such as Haar cascades, HOG, YOLO, etc. In this tutorial, we will use the Haar cascade classifier.

# Load the Haar cascade classifier
classifier = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')

# Detect the object
faces = classifier.detectMultiScale(img, scaleFactor=1.1, minNeighbors=5)

# Draw a rectangle around the object
for (x, y, w, h) in faces:
    cv2.rectangle(img, (x, y), (x+w, y+h), (0, 255, 0), 2)

# Display the image
cv2.imshow('Image', img)

# Wait for key press
cv2.waitKey(0)

# Compute the aspect ratio
for (x, y, w, h) in faces:
    aspect_ratio = float(w)/h
    print("Aspect Ratio:", aspect_ratio)

In the above code, we have loaded the Haar cascade classifier using the cv2.CascadeClassifier() function. We have then detected the object in the image using the detectMultiScale() function. We have used the cv2.rectangle() function to draw a rectangle around the object. Finally, we have computed the aspect ratio of the object using the formula aspect_ratio = float(w)/h.

Conclusion

In this tutorial, we have learned how to compute the aspect ratio of an object in an image using OpenCV Python. We have used the Haar cascade classifier to detect the object in the image and have then computed the aspect ratio of the object using the formula aspect_ratio = float(w)/h. This tutorial can be used as a starting point for various applications such as object recognition, classification, and tracking.