JohnPaul :
I have been able to read an image, then read a specific pixel using a co-ordinate location which works fine (pixel = img[801,600]
).
My next step is to iterate through each pixel and try to find the location (in this example [801,600]) using the pixel data.
My iteration through "img" isn't able to find the pixel. I would appreciate any help or guidance.
import cv2
import numpy as np
img = cv2.imread('one.jpg')
pixel = img[801,600]
print (pixel) # pixel value i am searching for
for i in img:
for x in i:
if x.sort == pixel.sort:
print ("SUCCESS")
DBat :
The built-in enumerate
iteration function will help you. It will provide an iteration index, that in your case, will provide a pixel index:
import cv2
import numpy as np
img = cv2.imread('one.jpg')
pixel = img[801,600]
print (pixel) # pixel value i am searching for
def search_for():
for iidx, i in enumerate(img):
for xidx, x in enumerate(i):
if (x == pixel).all():
print (f"SUCCESS - [{iidx} {xidx}]")
if __name__ == "__main__":
print("Search using for loops...")
search_for()
That being said, for loops are slow in python and it takes a while for the code to run on an suitably large image. Instead, using np.array
methods are preferred as they are optimized for this type of application:
import cv2
import numpy as np
img = cv2.imread('one.jpg')
pixel = img[801,600]
print (pixel) # pixel value i am searching for
def search_array():
# create an image of just the pixel, having the same size of
pixel_tile = np.tile(pixel, (*img.shape[:2], 1))
# absolute difference of the two images
diff = np.sum(np.abs(img - pixel_tile), axis=2)
# print indices
print("\n".join([f"SUCCESS - {idx}" for idx in np.argwhere(diff == 0)]))
if __name__ == "__main__":
print("Search using numpy methods...")
search_array()
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