how to convert an RGB image to numpy array?

Question

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'>

PIL (Python Imaging Library) and Numpy work well together.

I use the following functions.

from PIL import Image
import numpy as np

def load_image( infilename ) :
    img = Image.open( infilename )
    img.load()
    data = np.asarray( img, dtype="int32" )
    return data

def save_image( npdata, outfilename ) :
    img = Image.fromarray( np.asarray( np.clip(npdata,0,255), dtype="uint8"), "L" )
    img.save( outfilename )

The 'Image.fromarray' is a little ugly because I clip incoming data to [0,255], convert to bytes, then create a grayscale image. I mostly work in gray.

An RGB image would be something like:

 outimg = Image.fromarray( ycc_uint8, "RGB" )
 outimg.save( "ycc.tif" )

You can also use matplotlib for this.

from matplotlib.image import imread

img = imread('abc.tiff')
print(type(img))

output: <class 'numpy.ndarray'>

As of today, your best bet is to use:

img = cv2.imread(image_path)   # reads an image in the BGR format
img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)   # BGR -> RGB

You'll see img will be a numpy array of type:

<class 'numpy.ndarray'>

Late answer, but I've come to prefer the imageio module to the other alternatives

import imageio
im = imageio.imread('abc.tiff')

Similar to cv2.imread(), it produces a numpy array by default, but in RGB form.