I'm trying to convert a 2D Numpy array, representing a black-and-white image, into a 3-channel OpenCV array (i.e. an RGB image).
Based on code samples and the docs I'm attempting to do this via Python like:
import numpy as np, cv
vis = np.zeros((384, 836), np.uint32)
h,w = vis.shape
vis2 = cv.CreateMat(h, w, cv.CV_32FC3)
cv.CvtColor(vis, vis2, cv.CV_GRAY2BGR)
However, the call to CvtColor() is throwing the following cpp-level Exception:
OpenCV Error: Image step is wrong () in cvSetData, file /build/buildd/opencv-2.1.0/src/cxcore/cxarray.cpp, line 902
terminate called after throwing an instance of 'cv::Exception'
what(): /build/buildd/opencv-2.1.0/src/cxcore/cxarray.cpp:902: error: (-13) in function cvSetData
Aborted
What am I doing wrong?
3 Answers
Your code can be fixed as follows:
import numpy as np, cv
vis = np.zeros((384, 836), np.float32)
h,w = vis.shape
vis2 = cv.CreateMat(h, w, cv.CV_32FC3)
vis0 = cv.fromarray(vis)
cv.CvtColor(vis0, vis2, cv.CV_GRAY2BGR)
Short explanation:
np.uint32data type is not supported by OpenCV (it supportsuint8,int8,uint16,int16,int32,float32,float64)cv.CvtColorcan't handle numpy arrays so both arguments has to be converted to OpenCV type.cv.fromarraydo this conversion.- Both arguments of
cv.CvtColormust have the same depth. So I've changed source type to 32bit float to match the ddestination.
Also I recommend you use newer version of OpenCV python API because it uses numpy arrays as primary data type:
import numpy as np, cv2
vis = np.zeros((384, 836), np.float32)
vis2 = cv2.cvtColor(vis, cv2.COLOR_GRAY2BGR)
This is what worked for me...
import cv2
import numpy as np
#Created an image (really an ndarray) with three channels
new_image = np.ndarray((3, num_rows, num_cols), dtype=int)
#Did manipulations for my project where my array values went way over 255
#Eventually returned numbers to between 0 and 255
#Converted the datatype to np.uint8
new_image = new_image.astype(np.uint8)
#Separated the channels in my new image
new_image_red, new_image_green, new_image_blue = new_image
#Stacked the channels
new_rgb = np.dstack([new_image_red, new_image_green, new_image_blue])
#Displayed the image
cv2.imshow("WindowNameHere", new_rgbrgb)
cv2.waitKey(0)
The simplest solution would be to use Pillow lib:
from PIL import Image
image = Image.fromarray(<your_numpy_array>.astype(np.uint8))
And you can use it as an image.
