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Image Processing

Image Processing#

[1]:

import numpy as np
import matplotlib.pyplot as plt
import matplotlib.image as mpimg
from matplotlib import style

style.use("ggplot")

%matplotlib inline

BGR to Grayscale#

from scratch#

[2]:

img = mpimg.imread("./images/rdj.jpg")

[3]:

img.shape

[3]:

(550, 550, 3)

[4]:

plt.imshow(img)

[4]:

<matplotlib.image.AxesImage at 0x7f86a455b340>
../_images/ComputerVision_ImageProcessing_6_1.png

Average method#

[6]:

gray_img = np.mean(img,axis=2)
plt.imshow(gray_img,cmap='gray')

[6]:

<matplotlib.image.AxesImage at 0x7f86a0a1a220>
../_images/ComputerVision_ImageProcessing_8_1.png

Weighted method or luminosity method#

  • 0.2989 R + 0.5870 G + 0.1140 B

[5]:

B, G, R = img[...,0], img[...,1], img[...,2]

imgGray = 0.2989 * R + 0.5870 * G + 0.1140 * B
gray_img = ( 0.21 * R ) + (0.72 * G ) + ( 0.07 * B)
plt.imshow(gray_img,cmap='gray')

[5]:

<matplotlib.image.AxesImage at 0x7f86a0a2b910>
../_images/ComputerVision_ImageProcessing_10_1.png

using pillow#

[7]:

from PIL import Image

img = Image.open("./images/rdj.jpg")
gray_img = img.convert('LA')

[8]:

plt.imshow(gray_img)

[8]:

<matplotlib.image.AxesImage at 0x7f86a09750a0>
../_images/ComputerVision_ImageProcessing_13_1.png

using cv2#

[9]:

import cv2 as cv

[10]:

img = cv.imread("./images/rdj.jpg")

[11]:

plt.imshow(cv.cvtColor(img,cv.COLOR_BGR2GRAY),cmap='gray')

[11]:

<matplotlib.image.AxesImage at 0x7f8692ef3d60>
../_images/ComputerVision_ImageProcessing_17_1.png
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