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()

You need a properly sized numpy array, meaning a HxWx3 array with integers. I tested it with the following code and input, seems to work as expected.

import os.path
import numpy as np
from PIL import Image


def pil2numpy(img: Image = None) -> np.ndarray:
    """
    Convert an HxW pixels RGB Image into an HxWx3 numpy ndarray
    """

    if img is None:
        img = Image.open('amsterdam_190x150.jpg'))

    np_array = np.asarray(img)
    return np_array


def numpy2pil(np_array: np.ndarray) -> Image:
    """
    Convert an HxWx3 numpy array into an RGB Image
    """

    assert_msg = 'Input shall be a HxWx3 ndarray'
    assert isinstance(np_array, np.ndarray), assert_msg
    assert len(np_array.shape) == 3, assert_msg
    assert np_array.shape[2] == 3, assert_msg

    img = Image.fromarray(np_array, 'RGB')
    return img


if __name__ == '__main__':
    data = pil2numpy()
    img = numpy2pil(data)
    img.show()

I am using:

• Python 3.6.3
• numpy 1.14.2
• Pillow 4.3.0

You can use newer OpenCV python interface (if I'm not mistaken it is available since OpenCV 2.2). It natively uses numpy arrays:

import cv2
im = cv2.imread("abc.tiff")
print(type(im))

result:

<type 'numpy.ndarray'>

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)

RGB image is composed of three grayscale images. You can make three grayscale images like

rgb = np.random.randint(255, size=(900,800,3),dtype=np.uint8)
cv2.imshow('RGB',rgb)
cv2.waitKey(0)

In your comment you specify that the red_arr, etc. are arrays of the range -4000 to 4000.

But if we take a look at the specifications of the Image.from_array modes, then we see that it expects a matrix of three bytes (values from zero to 255).

This is however not per se a problem: we can perform:

def rescale(arr):
    arr_min = arr.min()
    arr_max = arr.max()
    return (arr - arr_min) / (arr_max - arr_min)

red_arr_b = 255.0 * rescale(red_arr)
green_arr_b = 255.0 * rescale(green_arr)
blue_arr_b = 255.0 * rescale(blue_arr)

arr[:,:,0] = red_arr_b
arr[:,:,1] = green_arr_b
arr[:,:,2] = blue_arr_b

img = Image.fromarray(arr.astype(int), 'RGB')

So first we rescale to a range 0 to 255, and then we feed that array to the PIL.

It is also possible that we want to scale red, green and blue the same way. In that case we can use:

def rescale(arr):
    arr_min = arr.min()
    arr_max = arr.max()
    return (arr - arr_min) / (arr_max - arr_min)

arr[:,:,0] = red_arr
arr[:,:,1] = green_arr
arr[:,:,2] = blue_arr

arr = 255.0 * rescale(arr)

img = Image.fromarray(arr.astype(int), 'RGB')

You can use newer OpenCV python interface (if I'm not mistaken it is available since OpenCV 2.2). It natively uses numpy arrays:

import cv2
im = cv2.imread("abc.tiff",mode='RGB')
print(type(im))

result:

<type 'numpy.ndarray'>

I did this on your camel image in Python/OpenCV to get two pixels. Channel values are not just 0 and 255.

import cv2
import numpy as np

# load image and get dimensions
img = cv2.imread("camel.jpg")
hh, ww = img.shape[:2]

# get pixel at x=0,y=0
px1 = img[0:1, 0:1]

# get pixel at center of image
hh2 = hh//2
ww2 = ww//2
px2 = img[hh2:hh2+1, ww2:ww2+1]

print(px1)
print(px2)

Results:

[[[0 0 0]]]
[[[129   0 193]]]

But you should be able to just print(img) or use Numpy to crop a region and print it.

Perhaps there is something wrong with your camel.jpeg image, but it gets fixed when saving and posting it. Try uploading the file you posted and see if it has the same issue.