You don't need to convert NumPy array to Mat because OpenCV cv2 module can accept NumPyarray. The only thing you need to care for is that {0,1} is mapped to {0,255} and any value bigger than 1 in NumPy array is equal to 255. So you should divide by 255 in your code, as shown below.

img = numpy.zeros([5,5,3])

img[:,:,0] = numpy.ones([5,5])*64/255.0
img[:,:,1] = numpy.ones([5,5])*128/255.0
img[:,:,2] = numpy.ones([5,5])*192/255.0

cv2.imwrite('color_img.jpg', img)
cv2.imshow("image", img)
cv2.waitKey()

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:

1. np.uint32 data type is not supported by OpenCV (it supports uint8, int8, uint16, int16, int32, float32, float64)
2. cv.CvtColor can't handle numpy arrays so both arguments has to be converted to OpenCV type. cv.fromarray do this conversion.
3. Both arguments of cv.CvtColor must 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)

Most of OpenCV functions work only with BGR images and not RGB, for example imshow or imwrite. OpenCV will do the work for you to put it in the correct way and save it as JPG image that can be loaded by ANY other app. If you have it with another order, then the function won't know this and save it with the wrong order.

Removing this line:

img = cv2.cvtColor(img.astype(np.uint8), cv2.COLOR_BGR2RGB)

should do the work for you.

My guess is that is not in the correct format (np.uint8) either, since you use it in the line that I just told you to remove. So you must also change the saving part to:

cv2.imwrite(
            './saveImage/img' + str(i) + ': ' + 'True: ' + str(cls_true[i]) + ', Pred:' +
            str(cls_pred[i]) + '.JPEG', img.astype(np.uint8))

Everything should work now. This images can be loaded in another moment with PIL an any other library as well and you will get almost identical images (JPG is a lossy compression) if you want identical, try saving them in another format that has lossless compression.