OpenCV Essentials

Import Libraries

pip install opencv-python

import os
import cv2
import numpy as np
import matplotlib.pyplot as plt

from zipfile import ZipFile
from urllib.request import urlretrieve

from IPython.display import Image

%matplotlib inline

Image(filename="images/myimage1.jpg")

Reading images using OpenCV

Function Syntax

retval = cv2.imread( filename[, flags] )

Flags

1. cv2.IMREAD_GRAYSCALE or 0: Loads image in grayscale mode
2. cv2.IMREAD_COLOR or 1: Loads a color image. Any transparency of image will be neglected. It is the default flag.
3. cv2.IMREAD_UNCHANGED or -1: Loads image as such including alpha channel.

OpenCV Documentation

1. Imread: Documentation link

2. ImreadModes: Documentation link

# Read image as gray scale.
cb_img = cv2.imread("images/myimage1.jpg", 0)
# Print the image data
print(cb_img)

[[187 203 237 ... 227 233 215]
 [158 167 200 ... 217 226 197]
 [144 134 135 ... 213 224 191]
 ...
 [ 54  53  54 ...  40  40  41]
 [ 55  52  53 ...  39  39  40]
 [ 56  53  53 ...  38  39  40]]

# print the size  of image
print("Image size (H, W) is:", cb_img.shape)

# print data-type of image
print("Data type of image is:", cb_img.dtype)

Image size (H, W) is: (1525, 1526)
Data type of image is: uint8

Display Images using Matplotlib

plt.imshow(cb_img, cmap="gray")

<matplotlib.image.AxesImage at 0x2e781bd7ee0>

plt.imshow(cb_img)

<matplotlib.image.AxesImage at 0x2e7829adfa0>

# print the size  of image
print("matrix size (H, W) is:", cb_img.shape)

matrix size (H, W) is: (1525, 1526)

NP functions that are usefull for calculating with elements in matrix

np.sum:Computes the sum of array elements over a specified axis.

np.mean: Computes the arithmetic mean along the specified axis.
np.max: Computes the maximum of array elements along a specified axis.

np.min: Computes the minimum of array elements along a specified axis.
np.prod: Computes the product of array elements over a specified axis.
np.std: Computes the standard deviation along the specified axis.
np.var: Computes the variance along the specified axis.
np.argmax: Returns the indices of the maximum values along an axis.
np.argmin: Returns the indices of the minimum values along an axis.
np.median: Computes the median along the specified axis.
np.percentile: Computes the q-th percentile of the data along the specified axis.
np.cumsum: Computes the cumulative sum of array elements along a specified axis.
np.cumprod: Computes the cumulative product of array elements along a specified axis.
np.linalg.norm: Computes the vector or matrix norm.

Calculating Avreage

average = np.mean(cb_img)

print("Average of matrix elements:", average)

Average of matrix elements: 91.7139703070279

Calculating Variance

variance = np.var(cb_img)

print("Variance of matrix elements:", variance)

Variance of matrix elements: 4259.920145633649

Saving Images

# save the image
cv2.imwrite("images/myimage1_SAVED.png", cb_img )

Image(filename='images/myimage1_SAVED.png')

Thanks for your attention Kiarash Rahmani