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How can I change numpy array into grayscale opencv image in python?
After some processing I got an array with following atributes: max value is: 0.99999999988,
min value is 8.269656407e-08 and type is: <type 'numpy.ndarray'>. I can show it as an image using cv2.imshow() function, but I can't pass it into cv2.AdaptiveTreshold() function because it has wrong type:
error: (-215) src.type() == CV_8UC1 in function cv::adaptiveThreshold
How can I convert this np.array to correct format?
436
Step 1: Import OpenCV. Step 2: Read the original image using imread(). Step 3: Convert to grayscale using cv2. cvtcolor() function.
So to convert the color image to grayscale we will be using cv2. imread("image-name. png",0) or you can also write cv2. IMREAD_GRAYSCALE in the place of 0 as it also denotes the same constant.
As the assertion states, adaptiveThreshold() requires a single-channeled 8-bit image.
Assuming your floating-point image ranges from 0 to 1, which appears to be the case, you can convert the image by multiplying by 255 and casting to np.uint8:
float_img = np.random.random((4,4))
im = np.array(float_img * 255, dtype = np.uint8)
threshed = cv2.adaptiveThreshold(im, 255, cv2.ADAPTIVE_THRESH_MEAN_C, cv2.THRESH_BINARY, 3, 0)
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