Part 1: Decompress an imagefile of an Optical Array Probe¶
The first thing you might want to try is to decompress and output your own data. The following code decompresses a sample image file and then prints the first 100 images in the console.
import oap
images = []
oap.decompress("Imagefile20200830120000", images=images)
for image in images[:100]:
oap.print_array(image)
oap.print_separator()
If you collect data for the training of a neural network or another classifier, you can save single images in a self-developed file format (.oap) to be able to load and edit them later. As an example we recognized a rosette in an image and want to save it with the corresponding particle type.
oap.array_as_oap_file(image, filename="rosette01", p_type=oap.ROSETTE)
The particle image is saved with the name “rosette02.oap”. If you want to load the image again later, you can do this as follows:
>>> array, p_type = oap.read_oap_file("rosette01.oap")
>>> oap.print_array(array)
1 2
2 2 2
1 2 3 3
3 3 3 1
2 3 3 2 2 3 3 3
3 3 3 3 3 1 1 3 3 3 1 1 2 2 1
1 3 3 3 3 3 3 2 1 2 3 3 3 3 2 3 1
3 3 3 3 3 3 3 2 2 3 3 3 3 3 3
3 3 3 3 3 3 2 2 3 3 3 3 3 3
1 1 3 3 2 2 3 3 3 3 3 3 3 1
1 1 2 2 1 1 2 2 2 3 3 3 3 3 3 3 3 2 1 1 1
1 3 3 3 3 3 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 1
2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 3 2 2
1 3 3 3 3 2 1 3 1 1 1 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 3 2 1
2 1 1 2 3 3 3 3 3 3 3 3 3 3 3 3 3 2 3 1
2 3 3 3 2 3 3 3 3 2 3 2 2 1
2 3 3 3 1 2 3 3 3 2 2 2 3 1
1 2 3 2 1 2 2 3 2 3 2
2 2 3 3 2 2 3 1
2 3 3 3
2 3 3 2
1 2 2
If you want to save this image in PNG format, you can do it with the following command:
oap.array_as_png(array, "rosette01")
This method creates an image in PNG format with the name “rosette01.png”.