Thanks, Patrick.
I should have been more explicit about what I was asking. The method you
outlined I was aware of.
What I'm asking has to do if you have such a large number of files or a
single file that is so large it can't be (or is impractical to be) read
into memory.
The idea I tried, and works thus far is to use a numpy memmap object.
So imagine a file "VeryLargeImageFile.img", which consists of the binary
data of type unsigned integer (uint16). Let's say this was captured with a
camera of format frame shape (512,640), and there are 10,000 frames stored
in the file.
fp = np.memmap('VeryLargeImageFile.img', dtype='unt16', mode='r',
offset=0, shape=(10000,512,640))
The variable can be passed to ImageView item by imv.setImage(fp).
However, for 32-bit operating systems, fp would still be limited to 2Gb.
So my real question is if there is a method to pass a generator which reads
a frame at a time to the ImageView or, if I had a large list of binary
files, could I create a generator which will cycle through reading each
file and return a numpy array of the data read for each file.
Is what I'm asking making more sense, now? If not, let me know and I'll
try to clarify by uploading my current code.
Thanks again.
-Dennis
On Mon, Oct 29, 2018 at 11:47 PM Patrick <[email protected]> wrote:
> Hi,
>
> You can load images into numpy arrays (usable by ImageItem, ImageView etc)
> using the scipy.ndimage.imread function. I think it relies on having the
> Python Image Library (PIL) installed. A more modern version of that library
> is Pillow, which you could also use to load image data.
>
> Limitations are though that the ImageView expects each image to have the
> same dimensions.
>
> Simple modification of ImageView example to demonstrate (specify your
> image files on command line).
>
> #!/usr/bin/env python3
>
>
> import numpy as np
> from pyqtgraph.Qt import QtCore, QtGui
> import pyqtgraph as pg
> from argparse import ArgumentParser
> from scipy.ndimage import imread
>
> argparser = ArgumentParser(description='Load images and display using
> pyqtgraph ImageView widget.')
> argparser.add_argument('input_images', help='Input filename(s) of images',
> nargs='+')
> args = argparser.parse_args()
>
> imagelist = []
> for filename in args.input_images:
> print("Loading {}...".format(filename))
> image = imread(filename)
> imagelist.append(image)
> print('Image shape: {}{}'.format(imagelist[len(imagelist)-1].shape, ''
> if imagelist[len(imagelist)-1].shape == imagelist[0].shape else ' *'))
> data=np.stack([ i for i in imagelist if i.shape==imagelist[0].shape ], 0)
> if len(args.input_images) != data.shape[0]:
> print('Warning: Shape of all input files must match. Those marked
> with * are skipped.')
>
> # Interpret image data as row-major instead of col-major
> pg.setConfigOptions(imageAxisOrder='row-major')
>
> app = QtGui.QApplication([])
>
> ## Create window with ImageView widget
> win = QtGui.QMainWindow()
> win.resize(800,800)
> imv = pg.ImageView()
> win.setCentralWidget(imv)
> win.show()
> win.setWindowTitle('pyqtgraph example: ImageView')
>
> ## Display the data
> imv.setImage(data)
>
> ## Set a custom color map
> colors = [
> (0, 0, 0),
> (45, 5, 61),
> (84, 42, 55),
> (150, 87, 60),
> (208, 171, 141),
> (255, 255, 255)
> ]
> cmap = pg.ColorMap(pos=np.linspace(0.0, 1.0, 6), color=colors)
> imv.setColorMap(cmap)
>
> ## Start Qt event loop unless running in interactive mode.
> if __name__ == '__main__':
> import sys
> if (sys.flags.interactive != 1) or not hasattr(QtCore, 'PYQT_VERSION'
> ):
> QtGui.QApplication.instance().exec_()
>
>
>
>
> On Monday, 29 October 2018 15:20:41 UTC+10:30, Dennis Norton wrote:
>>
>> I'm wondering if there is a convenient way to use the ImageView class to
>> display images either from a list of files in a directory or from a large
>> binary file consisting of multiple frames.
>>
>> Could we create a generator which yields the numpy arrays to display?
>>
>> Thanks.
>>
>> --
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-Dennis
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