Python OpenCV - Shell/Bash

Introduction

OpenCV (Open Source Computer Vision Library) is an open-source computer vision and machine learning software library. It has been developed to enhance the productivity of real-time applications that require computer vision. Python OpenCV is a python binding for OpenCV library that enables developers to use various OpenCV functions in their python applications.

Shell/Bash is a command-line interpreter that provides a powerful interface to control the computer. It is used to execute commands, perform operations, and automate tasks. In this article, we will look at how we can use Python OpenCV with Shell/Bash to automate various computer vision tasks.

Installation

To use Python OpenCV with Shell/Bash, we need to install both OpenCV and Python. We can install OpenCV using pip (a package manager for Python) by running the following command:

pip install opencv-python

Once OpenCV is installed, we can use it with Python.

Examples

Display Image

To display an image using Python OpenCV with Shell/Bash, we can use the following command:

python -c "import cv2; cv2.imshow('image', cv2.imread('image.jpg')); cv2.waitKey(0)"

In the above command, we import the cv2 module of OpenCV and use the imshow() function to display the image. We provide the name ‘image’ as the title of the window. We read the image using the imread() function of OpenCV. Finally, we use the waitKey() function to wait for the user to press any key before closing the window.

Face Detection

To detect faces in an image using Python OpenCV with Shell/Bash, we can use the following command:

python -c "import cv2; face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml'); img = cv2.imread('image.jpg'); faces = face_cascade.detectMultiScale(img, scaleFactor=1.1, minNeighbors=5); for (x, y, w, h) in faces: cv2.rectangle(img, (x, y), (x+w, y+h), (0, 0, 255), 2); cv2.imshow('image', img); cv2.waitKey(0)"

In the above command, we first import the cv2 module of OpenCV. We then load the face detection cascade classifier by providing the path to the xml file. We read the image using the imread() function of OpenCV. We then detect faces in the image using the detectMultiScale() function of OpenCV. We provide the scaleFactor and minNeighbors parameters to control the detection sensitivity.

Finally, we loop through the detected faces and draw a rectangle around each face using the rectangle() function of OpenCV. We use imshow() function to display the image with detected faces. We use waitKey() function to wait for the user to press any key before closing the window.

Conclusion

Python OpenCV with Shell/Bash provides a powerful interface to automate computer vision tasks. In this article, we have seen how we can use Python OpenCV with Shell/Bash to display images and detect faces in an image. The possibilities are endless, and we can use this combination to automate various other computer vision tasks.

References

1. https://opencv-python-tutroals.readthedocs.io/en/latest/py_tutorials/py_tutorials.html

2. https://docs.opencv.org/4.5.4/d9/df8/tutorial_root.html

3. https://en.wikipedia.org/wiki/Bash_(Unix_shell)

4. https://en.wikipedia.org/wiki/OpenCV

5. https://pip.pypa.io/en/stable/