On 16 Jul 2019, at 9:30 am, Omry Levy <[email protected]> wrote:
>
> I have a question, regarding conversion of C (unsigned char *) buffer to a
> two dimensional numpy array
>
> this is what i am doing:
> 1) I get a C network buffer of unsigned char * let's call it the source
> buffer
> the size of the source buffer is:
> W * H * 2 bytes
>
> 2) I am using PyByteArray_FromStringAndSize() to convert the source buffer
> (a C unsigned char *) to python bytes array.
> a = PyByteArray_FromStringAndSize(source buffer, W * H * 2)
>
> 3) i am using numpy.frombuffer to convert the python bytes array to a 1
> dimensional numpy array of size W *H *2 bytes
> b = numpy.frombuffer(a, dtype = np.uint8)
>
> 4) i am creating a 2 dimensional numpy array from (3) when each element in
> that array is made of 2 bytes from the python bytes array
> c = b.view(np.uint16).reshape((H, W))
>
> Is there a way to optimize this some how ?
> Can you suggest a faster and better solution ?
>
The PyByteArray conversion seems unnecessary - if you can access your input as
a buffer,
calling np.frombuffer on it directly with the correct dtype should work just as
well, and you
can reshape it on the fly:
c = np.frombuffer(source_buffer, dtype=np.uint16, [count=W*H]).reshape((H, W))
The optional ‘count’ argument would only be required if you cannot simply read
the buffer
to its end.
HTH,
Derek
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