Working with images


There are several types of images in the jicbioimage.core.image module. Raw data is contained in the jicbioimage.core.image.Image class. The jicbioimage.core.image.ProxyImage and jicbioimage.core.image.MicroscopyImage classes contain image meta data along with a reference to the raw image.

The jicbioimage.core.image.Image is a subclass of numpy.ndarray. In addition to the numpy.ndarray functionality the jicbioimage.core.image.Image class has specialised functionality for creating images, tracking the history of images and returning png/html representations of images.

Creating images

Using numpy to create images

There are several ways of creating images. One can use the functionality inherited from numpy.ndarray.

>>> from jicbioimage.core.image import Image
>>> Image((50,50))  
<Image object at 0x..., dtype=uint8>


When creating an image in this fashion it will be filled with the noise of whatever was present in that piece of computer memory before the memory was allocated to the image.

A safer way to create an image is to first create a numpy.ndarray using numpy.zeros() or numpy.ones() and then cast it to the jicbioimage.core.image.Image type.

>>> import numpy as np
>>> np.zeros((50,50), dtype=np.uint8).view(Image)  
<Image object at 0x..., dtype=uint8>

When creating an array in this fashion it’s history creation attribute is empty.

>>> print(np.zeros((50, 50), dtype=np.uint8).view(Image).history.creation)

To assign a creation event to the image history one can use the jicbioimage.core.image.Image.from_array() class method.

>>> ar = np.zeros((50, 50), dtype=np.uint8)
>>> im = Image.from_array(ar)
>>> im.history.creation
'Created Image from array'

Creating images from file

Suppose that we wanted to create an jicbioimage.core.image.Image instance from the file images/rgb_squares.png.

>>> fpath = "images/rgb_squares.png"

This can be achieved using the jicbioimage.core.image.Image.from_file() class method.

>>> im = Image.from_file(fpath)  

Accessing png representations of an image

The jicbioimage.core.image.Image.png() function can be used to access the image as a PNG binary string. This function is used internally to implement the IPython integration, which allows images to be viewed directly in IPython qtconsole/notebook.

>>> im  
RGB squares.

Working with stacks of images

Many bioimages contain stacks of 2D images representing a 3D structure. The jicbioimage.core.image.Image3D class can be used to work with this type of data.

The jicbioimage.core.image.Image3D is a subclass of numpy.ndarray. To create an instance of a jicbioimage.core.image.Image3D from a numpy array and assign a creation event to the history of the 3D image one can use the jicbioimage.core.image.Image3D.from_array method.

To access such a stack from a jicbioimage.core.image.MicroscopyCollection one can use the jicbioimage.core.image.MicroscopyCollection.zstack() method.

>>> from jicbioimage.core.image import Image3D
>>> ar = np.zeros((50, 50, 50), dtype=np.uint8)
>>> im3d = Image3D.from_array(ar)
>>> im3d.history.creation
'Created Image3D from array'

It is possible to write and read an instance of jicbioimage.core.image.Image3D as a series of 2D images to and from a directory using the jicbioimage.core.image.Image3D.to_directory() method and jicbioimage.core.image.Image3D.from_directory() class method.