from __future__ import print_function
import cv2
import numpy as np
from helpers.image_reader import image_reader, show_image
im1 = "/home/joemarshal/image_processing_opencv/images/resizedronaldo.jpg"
mode = 1
img = image_reader(im1, mode)
for alpha in np.arange(0, 1.1, 0.1)[::-1]:
if alpha > 0.0:
print("transparnet image", alpha)
else:
print("Not Transparent", alpha)
overlay = img.copy()
output = img.copy()
cv2.rectangle(overlay, (420, 205), (595, 385), (0, 0, 255), -1)
cv2.addWeighted(overlay, alpha, output, 1 - alpha, 0, output)
print("alpha{}, beta{}".format(alpha, 1 - alpha))
show_image(output)
import cv2
import numpy as np
from helpers.image_reader import image_reader, show_image
def hough_transform_image(image, img):
"""
:param image: pass the canny iamge
:param img: pass the original image
:return: it will mark the lines in the canny image and passes it back to the original image
"""
lines = cv2.HoughLinesP(image, 1, np.pi / 180, 50, maxLineGap=200)
for line in lines:
print(line)
x1, x2, y1, y2 = line[0]
cv2.line(img, (x1, x2), (y1, y2), (0, 255, 0), 3)
show_image(img)
return lines
if __name__ == "__main__":
img1 = "/home/joemarshal/image_processing_opencv/images/lines.png"
mode = 0
image1 = image_reader(img1, 1)
grey = cv2.cvtColor(image1, cv2.COLOR_BGR2GRAY)
edges = cv2.Canny(grey, 75, 150)
show_image(edges)
hough = hough_transform_image(edges, image1)
import cv2
from helpers.image_reader import image_reader, show_image
if __name__ == "__main__":
img = "/home/joemarshal/image_processing_opencv/images/resizedronaldo.jpg"
mode = cv2.WINDOW_NORMAL
im = image_reader(img, mode)
rows, columns = im.shape[:2]
print(rows, columns)
center = (rows / 2, columns / 2)
rotating_image = cv2.getRotationMatrix2D(center, 570, 1.0)
m = cv2.warpAffine(im, rotating_image, (columns, rows))
i = show_image(m)
"""
Here you will find the code for low-pas-filter
"""
import cv2
from helpers.image_reader import image_reader, show_image
def low_pass_filter(img):
"""
:param img:
:return:
"""
fil = cv2.boxFilter(img, -1, (57, 57))
return fil
if __name__ == "__main__":
path = "/home/joemarshal/image_processing_opencv/images/shapes.jpg"
mode = 1
ima = image_reader(path, mode)
show_image(ima)
con = cv2.cvtColor(ima, cv2.COLOR_BGR2RGB)
show = low_pass_filter(con)
show_image(show)
"""
Here you can find how to add to images using the cv2.add() function
"""
import cv2
from helpers.image_reader import image_reader, show_image
def add_image(image1, image2):
"""
:param image1: passing image1
:param image2: passing image 2
:return: adds both the images
"""
add = cv2.add(image1, image2)
return add
if __name__ == "__main__":
img1 = "/home/joemarshal/image_processing/images/resizedronaldo.jpg"
img2 = "/home/joemarshal/image_processing/images/resizedmessi.jpg"
mode = 1
img1 = image_reader(img1, mode)
img2 = image_reader(img2, mode)
adding = add_image(img1, img2)
show_image(adding)
import cv2
import matplotlib.pyplot as plt
import numpy as np
from helpers.image_reader import image_reader, show_image
if __name__ == "__main__":
im = "/home/joemarshal/image_processing_opencv/images/resizedronaldo.jpg"
img = image_reader(im, 0)
show_image(img)
mask = np.zeros(img.shape[:2], np.uint8)
mask[82:328, 31:338] = 255
masked_img = cv2.bitwise_and(img, img, mask=mask)
show_image(masked_img)
hist_full = plt.hist(img.ravel(), 256, [0, 256])
hist_mask = plt.hist(masked_img.ravel(), 256, [0, 256])
plt.xlim([0, 256])
plt.show()
"""
Here you can run the threshold of an image without the threshold function
"""
import cv2
from helpers.image_reader import image_reader, show_image
if __name__ == "__main__":
img = "/home/joemarshal/image_processing_opencv/images/resizedronaldo.jpg"
mode = cv2.IMREAD_COLOR
im = image_reader(img, 0)
print(im)
print(im.shape)
height, width = im.shape
for h in range(height):
for w in range(width):
v = (im[h][w])
if v < 255:
im[h][w] = 127
else:
im[h][w] = 0
show_image(im)
def division(img1, img2):
"""
:param img1: pass image 1
:param img2: pass image 2
:return: returns the division of both the images
"""
return cv2.divide(img1, img2)
if __name__ == "__main__":
im1 = "/home/joemarshal/image_processing/images/resizedronaldo.jpg"
im2 = "/home/joemarshal/image_processing/images/resizedmessi.jpg"
mode = cv2.WINDOW_NORMAL
image1 = image_reader(im1, mode)
image2 = image_reader(im2, mode)
show_image(image1)
show_image(image2)
bit_and = bitwise_and(image1, image2)
bit_or = bitwise_or(image1, image2)
bit_not = bitwise_not(image1, image2)
bit_xor = bitwise_xor(image1, image2)
subt = subtract(image1, image2)
mul = multiplication(image1, image2)
div = division(image1, image2)
show_image(bit_and)
show_image(bit_or)
show_image(bit_not)
show_image(bit_xor)
show_image(subt)
