Question

I want to create an "array_like" QImage subclass that can be passed to numpy.array().
I’d like to avoid using PIL as a substitute; the whole point of this is to avoid the dependency on PIL. Besides, constantly converting between QImage and the PIL Image is impractical for my program.

I find the documentation cryptic, and after reading it I’m still confused about how to emulate the array interface. As the numpy documentation states, to qualify as an "array_like" object, it needs the __array_interface__ attribute, which is a dictionary with five keys. However, I’ve never dealt with types, buffers, and memory before; if someone could explain how to solve this problem it would be much appreciated.

I’m using Python 3.3 and PySide 1.1.2.
Thanks to all who reply!

Answer 1

It’s easier to just use the buffer object returned from QImage.bits() and np.frombuffer().

def qimage2array(q_image):
    width = q_image.width()
    height = q_image.height()
    arr = np.frombuffer(q_image.bits(), dtype=np.uint8).reshape([height, width, -1])
    return arr