[Numpy-discussion] create a numpy array of images

[totonixsame at gmail.com]

I've been done that but with CT and MRI dicom files, and the cool
thing is that with numpy I can do something like this:

# getting axial slice
axial = slices[n,:,:]

# getting coronal slice
coronal = slices[:, n, :]

# getting sagital slice
sagital = slices[:,:, n]

On Sun, Jan 30, 2011 at 5:29 PM, Friedrich Romstedt
<friedrichromstedt at gmail.com> wrote:
> 2011/1/28 Christopher Barker <Chris.Barker at noaa.gov>:
>> On 1/28/11 7:01 AM, Asmi Shah wrote:
>>> I am using python for a while now and I have a requirement of creating a
>>> numpy array of microscopic tiff images ( this data is 3d, meaning there are
>>> 100 z slices of 512 X 512 pixels.) How can I create an array of images?
>>
>> It's quite straightforward to create a 3-d array to hold this kind of data:
>>
>> image_block = np.empty((100, 512, 512), dtype=??)
>>
>> now you can load it up by using some lib (PIL, or ???) to load the tif
>> images, and then:
>>
>> for i in images:
>>     image_block[i,:,:] = i
>
> Notice that since PIL 1.1.6, PIL Image objects support the numpy
> interface: http://effbot.org/zone/pil-changes-116.htm
>
>>>> import PIL.Image
>>>> im = PIL.Image.open('P1010102.JPG')
>>>> im
> <PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=3264x2448 at 0x4CA0A8>
>>>> a = numpy.asarray(im)
>>>> a.shape
> (2448, 3264, 3)
>>>> a.dtype
> dtype('uint8')
>
> You can use the image just as any other ndarray:
>
>>>> stack = numpy.empty((5, 2488, 3264, 3))
>>>> stack[0] = im
> and so on
>
> for 5 images in a stack, notice that the dtype of the initially empty
> ndarray is float!
>
> It works also vice-versa:
>
>>>> im_copy = PIL.Image.fromarray(a)
>
> but this seems to require integer-valued ndarrays as input, except
> when the ndarray is monochrome.
>
> This might be even simpler than the dtype proposed by Christopher.
>
> For more info on PIL: http://www.pythonware.com/library/pil/handbook/
>
> Friedrich
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