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#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Copyright © 2014 - 2021 German Neuroinformatics Node (G-Node)
All rights reserved.
Redistribution and use in source and binary forms, with or without
modification, are permitted under the terms of the BSD License. See
LICENSE file in the root of the Project.
Author: Jan Grewe <jan.grewe@g-node.org>
See https://github.com/G-node/nix/wiki for more information.
We use the "Lenna" image in this tutorial.
"Lenna" by Original full portrait: "Playmate of the Month". Playboy
Magazine. November 1972, photographed by Dwight Hooker.This 512x512
electronic/mechanical scan of a section of the full portrait:
Alexander Sawchuk and two others[1] - The USC-SIPI image
database. Via Wikipedia -
http://en.wikipedia.org/wiki/File:Lenna.png#mediaviewer/File:Lenna.png
"""
import nixio
import numpy as np
from PIL import Image as img
import docutils
def load_image():
image = img.open('lenna.png')
pix = np.array(image)
channels = list(image.mode)
return pix, channels
def plot_data(data_array):
img_data = np.zeros(data_array.shape)
data_array.read_direct(img_data)
img_data = np.array(img_data, dtype='uint8')
new_img = img.fromarray(img_data)
if not docutils.is_running_under_pytest():
new_img.show()
if __name__ == '__main__':
img_data, channels = load_image()
# create a new file overwriting any existing content
file_name = 'image_example.nix'
file = nixio.File.open(file_name, nixio.FileMode.Overwrite)
# create a 'Block' that represents a grouping object. Here, the recording session.
# it gets a name and a type
block = file.create_block("block name", "nix.session")
# create a 'DataArray' and store the image data
data = block.create_data_array("lenna", "nix.image.rgb", data=img_data)
# add descriptors for width, height and channel dimensions
data.append_sampled_dimension(1, label="height")
data.append_sampled_dimension(1, label="width")
data.append_set_dimension(labels=channels)
# let's plot the data from the stored information
plot_data(data)
file.close()
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