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How do I use this image as a mask to perform segmentation?

asked 2020-02-07 06:48:45 -0600

tsabbir96 gravatar image

updated 2020-02-07 06:49:26 -0600

Hello I have this image:

image

i want to use this black and white image as a mask to segment the clouds from this RGB image :

image

However I am having some problem achieving this, as the black and white image is not in binary form. when i print the values of the image it prints some compex number. please kindly have a look at this attached image:

image

Please could you help me by showing a way on how to use this weird black and white image as a mask to segment clouds from the RGB image that I have attached?

btw I am a student and I am really really new to image processing. I Would appreciate your help a lot. Thank you.

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it prints some compex number

no, it's the first and last 20 numbers from your "mask", which is is floating point format

berak gravatar imageberak ( 2020-02-07 07:54:23 -0600 )edit

so if i see "2.4444e-1" such type of numbers, they are basically floating point numbers, yes?

tsabbir96 gravatar imagetsabbir96 ( 2020-02-07 08:27:38 -0600 )edit

yes. how did you acquire it, btw ? (unusual format)

berak gravatar imageberak ( 2020-02-07 08:52:08 -0600 )edit
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I generated it from a DNN. I trained a DNN to output black and white images of the clouds. I used the same DNN mentioned in this github: https://github.com/Soumyabrata/CloudS... then i used the trained model to predict the output which is the black and white image I attached

tsabbir96 gravatar imagetsabbir96 ( 2020-02-07 08:56:26 -0600 )edit

^^ awesome ;)

berak gravatar imageberak ( 2020-02-07 09:09:18 -0600 )edit

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answered 2020-02-07 08:44:50 -0600

berak gravatar image

updated 2020-02-07 08:47:42 -0600

the most common way to get a binary image is thresholding :

#help(cv2.threshold)
# assume, "gray" is your "mask" image above
thr, bin = cv2.threshold(gray, 0.1, 255.0, cv2.THRESH_BINARY);
print("threshold: ",thr)

(to use OTSU, you need to convert / scale to uint8 first !)

image description

then you can mask out the unwanted parts:

#help(cv2.bitwise_or)
# assume, "img" is the bgr cloud img
# images did not have same size, thus:
mask = cv2.resize(mask, (img.shape[1], img.shape[0]))
result = cv2.bitwise_or(img, img, mask=mask);

image description

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Your piece of white cloud cropped out. Not accurately.

supra56 gravatar imagesupra56 ( 2020-02-11 08:00:04 -0600 )edit

yea, image sizes did not match, ad-hoc threshold value, etc.

(i guess, this is more to show, you can threshold float images w/o conversion)

berak gravatar imageberak ( 2020-02-11 08:07:42 -0600 )edit

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Asked: 2020-02-07 06:48:45 -0600

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Last updated: Feb 07 '20