gradientFloatToInt.py

This code demonstrates how to adapt a float ImageView into a 16-bit unsigned integer ImageView.

This code demonstrates how to adapt a float ImageView into a 16-bit unsigned integer ImageView. Data are converted on the fly, and the resulting image has values between 0 and 65535. Both images are displayed to show their content.

import iolink
 
import numpy as np
 
 
 
 
# Create a a vertical gradient into a float ImageView
# using the given input range [min, max].
def gradientFloatImage(inputRange: iolink.Vector2f):
    shape = iolink.VectorXu64(5, 30)
 
    dt = iolink.DataTypeId.FLOAT
    image = iolink.ImageViewFactory.allocate(shape, dt)
 
    image.axes_interpretation = iolink.AxesInterpretationId.IMAGE
 
    stepLine = (inputRange[1] - inputRange[0]) / shape[1]
 
    lineSize = iolink.VectorXu64(shape[0], 1)
    valueInit = inputRange[0]
    valueToSet = valueInit
    for j in range(0, shape[1]):
        lineRegion = iolink.RegionXu64((0, j), lineSize)
        # create a buffer corresponding to the line size, and
        # initialize it to the same value
        lineBuffer = np.full((shape[0], 1), valueToSet, dtype=np.float32)
        image.write_region(lineRegion, lineBuffer)
        valueToSet = valueInit + j * stepLine
 
    return image
 
data_range = iolink.Vector2f(0.0, 5.0)
 
floatImage = gradientFloatImage(data_range)
 
# convert the float ImageView to numpy
floatNpy = iolink.NumpyInterop.to_numpy_array(floatImage)
 
# print min/max values
print("Float image min/max:", np.amin(floatNpy), np.amax(floatNpy))
 
# convert the float image to a 16-bit integer image
# an adapter is added to the float image to convert the values on the fly
# data are not duplicated
intImage = iolink.ImageViewFactory.adapt_dynamic_range(floatImage, iolink.DataTypeId.UINT16, data_range, iolink.Vector2d(0, 65535))
 
# imageView must be in-memory to be converted into numpy
# An in-memory ImageView which has been adapted is not considered as is-memory anymore
intImage = iolink.ImageViewFactory.copy_in_memory(intImage)
 
# convert the Integer ImageView to numpy
intNpy = iolink.NumpyInterop.to_numpy_array(intImage)
 
# print min/max values
print("Integer image min/max:", np.amin(intNpy), np.amax(intNpy))
 
print("SUCCESS")