In Python OpenCV Tutorial, Explained How to Extraction or Detect Pixels Color using OpenCV Python
Get the answers of below questions:
- How do you find the color of the pixel of an image?
- How do you find the color of an image in Python?
- How do I extract color features from an image?
- How do we find items of a specific color?
- How can I identify a color in an image?
Color Pixels Extraction
How to Detect Road Marking Using OpenCV
# Show an Image
import cv2
import numpy as np
img_path =r"C:\Users\kashz\AI Life\AI Projects - IAIP, PTs (Web + Channel)\02 OpenCV\000 opencv tutorial\data\images\road\road1.jpg"
img = cv2.imread(img_path)
img = cv2.resize(img, (1280, 720))
cv2.imshow("Road Image", img)
cv2.waitKey(0)
cv2.destroyAllWindows()
Conver image in gray scale
gray_img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
cv2.imshow("Gray Image", gray_img)
cv2.waitKey(0)
cv2.destroyAllWindows()
Road Margin Detection using Gray Image
gray_img_copy = np.copy(gray_img)
gray_img_copy[gray_img_copy[:, :] < 200]=0
cv2.imshow("Gray Image", gray_img_copy)
cv2.waitKey(0)
cv2.destroyAllWindows()
gray_img ## 0 - 255 ## 0=Black, 255= White
gray_img_copy[:, :] < 200
gray_img_copy
gray_img_copy[:, 300]
Road Margin Detection using Color Image
img_copy = np.copy(img)
print("img_copy.shape: ", img_copy.shape)
img_copy[(img_copy[:, :, 0] < 200) | (img_copy[:, :, 1] < 200) | (img_copy[:, :, 2] < 200)] = 0
cv2.imshow("Color Image", img_copy)
cv2.waitKey(0)
cv2.destroyAllWindows()
Sign Board Detection
img_path =r"C:\Users\kashz\AI Life\AI Projects - IAIP, PTs (Web + Channel)\02 OpenCV\000 opencv tutorial\data\images\road\road5.jpg"
img = cv2.imread(img_path)
img = cv2.resize(img, (1280, 720))
img_copy = np.copy(img)
img_copy[(img_copy[:,:,0] > 50) | (img_copy[:,:,1] < 150) | (img_copy[:, :, 2] < 150) ]=0
img_2 = np.hstack((cv2.resize(img, (650, 500)), cv2.resize(img_copy, (650, 500))))
cv2.imshow("Yellow Road Image", img_2)
cv2.waitKey(0)
cv2.destroyAllWindows()
Red Color Pixels Extraction
img_path =r"C:\Users\kashz\AI Life\AI Projects - IAIP, PTs (Web + Channel)\02 OpenCV\000 opencv tutorial\data\images\road\road6.jpg"
img = cv2.imread(img_path)
img = cv2.resize(img, (1280, 720))
img_copy = np.copy(img)
img_copy[(img_copy[:,:,0] > 50) | (img_copy[:,:,1] > 50) | (img_copy[:, :, 2] < 90) ]=0
img_2 = np.hstack(( cv2.resize(img, (650, 500)), cv2.resize(img_copy, (650, 500)) ))
cv2.imshow("Color Image VS Color Extracted Image", img_2)
cv2.waitKey(0)
cv2.destroyAllWindows()
Yellow Color Pixels Extraction
img_path =r"C:\Users\kashz\AI Life\AI Projects - IAIP, PTs (Web + Channel)\02 OpenCV\000 opencv tutorial\data\images\road\road4.jpg"
img = cv2.imread(img_path)
img = cv2.resize(img, (1280, 720))
img_copy = np.copy(img)
img_copy[(img_copy[:,:,0] > 50) | (img_copy[:,:,1] < 150) | (img_copy[:, :, 2] < 150) ]=0
cv2.imshow("Yellow Road Image", img_copy)
cv2.waitKey(0)
cv2.destroyAllWindows()
Human Detection
img_path =r"C:\Users\kashz\AI Life\AI Projects - IAIP, PTs (Web + Channel)\02 OpenCV\000 opencv tutorial\data\images\road\sunset.jpg"
img = cv2.imread(img_path)
img = cv2.resize(img, (1280, 720))
img_copy = np.copy(img)
img_copy[(img_copy[:,:,0] > 90) | (img_copy[:,:,1] > 90) | (img_copy[:, :, 2] > 90) ]=255
img_2 = np.hstack((cv2.resize(img, (650, 500)), cv2.resize(img_copy, (650, 500))))
cv2.imshow("Yellow Road Image", img_2)
cv2.waitKey(0)
cv2.destroyAllWindows()