How to correctly covert 3d array into continguous rgb bytes

Question

I'm trying to convert the 3d array returned by cv2.imread to the continguous rgb byte array, in order to display in GTK. And below is my conversion code:

def ndarr2rgb(img):
    r_arr = img[:, :, 0].ravel()    # read channel
    g_arr = img[:, :, 1].ravel()    # green channel
    b_arr = img[:, :, 2].ravel()    # blue channel
    numItems = img.shape[0] * img.shape[1] * img.shape[2]   # number of entries in byte array
    z = img.shape[2]                # z dimension, always equal to 3
    arr = np.zeros((numItems, 1))
    # to fill the byte array with r,g,b channel
    for i in xrange(0, numItems):
        if i % z == 0:
            arr[i] = r_arr[i/z]
        if i % z == 1:
            arr[i] = g_arr[i/z]
        if i % z == 2:
            arr[i] = b_arr[i/z]
    return arr

So, in my code, I first get the three dimensions separately into r_arr, g_arr, b_arr, then I put the values in the order or RGB into the 'arr'. So after the iteration the array 'arr' will be like 'r0, g0, b0, r1, g1, b1, ...'

And then I use "GdkPixbuf.Pixbuf.new_from_data" function to get the pixbuf from the arr returned by the "ndarr2rgb" function above. And I use "image.set_from_pixbuf" to display the image. But I got the following result:
enter image description here It's like that there is some noisy area, so please help me solve my problem, thx.

have a look at https://stackoverflow.com/questions/39936737/how-to-turn-gdk-pixbuf-object-into-numpy-array/41714464#41714464 — am70, Jun 11 '20 at 11:44

score 3 · Answer 1 · answered Jun 05 '14 at 14:48

3

just do:

all_in_one_row = np.reshape(img,(-1))

answered Jun 05 '14 at 14:48

berak

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Thanks, that's a nice method. – Philip Zhang Jun 06 '14 at 08:35

Simon Feltman · Answer 2 · 2014-06-06T00:40:01.097

3

The problem is possibly due to GdkPixbuf.Pixbuf.new_from_data not managing memory correctly, see [1]. A workaround is to write the data to a temporary file and use GdkPixbuf.Pixbuf.new_from_file [2]. Example using PIL:

from PIL import Image

image = Image.frombytes('RGB', (width, height), data)
image.save(filename)
pixbuf = GdkPixbuf.Pixbuf.new_from_file(filename)

edited Jun 06 '14 at 00:40

answered Jun 05 '14 at 20:57

Simon Feltman

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Thanks a lot, although this method doesn't seem so straight-forward, it can at least work – Philip Zhang Jun 06 '14 at 08:35

score 1 · Answer 3 · answered May 12 '17 at 16:48

Due to changes in io, PIL and/or GdkPixbuf I had trouble figuring this out, even after reading numerous suggestions. Finally I've took quite a bare bone solution:

import gi
gi.require_version('Gtk', '3.0')
from gi.repository import Gtk, GdkPixbuf

def array2pixbuf(width, height, arr):
    # pnm
    header = b"P6 %d %d 255 " % (width, height)
    # flatten and convert to an array of bytes (not a bytearray!)
    data = bytes(colour for pixel in arr for colour in pixel)

    loader = GdkPixbuf.PixbufLoader.new()
    loader.write(header)
    loader.write(data)
    pixbuf = loader.get_pixbuf()
    loader.close()

    return pixbuf

This is the only thing that worked fully for me. Although I used `arr.flatten().tobytes()` instead of `data` for a numpy array. — Francesco Pasa, May 05 '19 at 08:06

score -1 · Answer 4 · edited Jun 20 '20 at 09:12

You don't need to write a temp file in order to workaroud GdkPixbuf.Pixbuf.new_from_data not managing memory correctly, [1] you can use the pnm image format [2]:

from gi.repository import GdkPixbuf
import cv2

filename = './file.png'
# read and convert image from BGR to RGB (pnm uses RGB)
im = cv2.cvtColor(cv2.imread(filename), cv2.COLOR_BGR2RGB)
# get image dimensions (depth is not used)
height, width, depth = im.shape
pixl = GdkPixbuf.PixbufLoader.new_with_type('pnm')
# P6 is the magic number of PNM format, 
# and 255 is the max color allowed, see [2]
pixl.write("P6 %d %d 255 " % (width, height) + im.tostring())
pix = pixl.get_pixbuf()
pixl.close()

After that hack, you can use: image.set_from_pixbuf( pix )

How to correctly covert 3d array into continguous rgb bytes

4 Answers4

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