I am trying to compute the Canny Edges in an image (ndarray) using OpenCV with Python.
slice1 = slices[15,:,:]
slice1 = slice1[40:80,60:100]
print slice1.sha
Slice1 will need to be casted or created as a uint8. CV_8U is just an alias for the datatype uint8.
import numpy as np
slice1Copy = np.uint8(slice1)
slicecanny = cv2.Canny(slice1Copy,1,100)
In order to avoid losing precision while changing the data type to uint8, you can first adapt the scale to the 255 format just doing:
(image*255).astype(np.uint8)
Here I'm considering that image is a numpy array and np stand for numpy. I hope it can help someone!
You can work around this error by saving slice1 to a file and then reading it
from scipy import ndimage, misc
misc.imsave('fileName.jpg', slice1)
image = ndimage.imread('fileName.jpg',0)
slicecanny = cv2.Canny(image,1,100)
This is not the most elegant solution, but it solved the problem for me