machinevisiontoolbox.Image.to_int
- Image.to_int(intclass='uint8')[source]
Image as integer NumPy array
- Parameters:
intclass (str, optional) – name of NumPy supported integer class, default is ‘uint8’
- Returns:
NumPy array with integer values
- Return type:
ndarray(H,W) or ndarray(H,W,P)
Return a NumPy array with pixels converted to the integer class
intclass. For the case where the input image is:a floating point class, the pixel values are scaled from an input range of [0,1] to a range spanning zero to the maximum positive value of the output integer class.
an integer class, then the pixels are scaled and cast to
intclass. The scale factor is the ratio of the maximum value of the input and output integer classes.boolean class, False is mapped to zero and True is mapped to the maximum positive value.
Example:
>>> from machinevisiontoolbox import Image >>> img = Image([[5_000, 10_000], [30_000, 60_000]]) >>> img Image: 2 x 2 (uint16) >>> img.to_int('uint8') array([[ 19, 38], [116, 233]], dtype=uint8) >>> img.to_int('uint32') array([[ 327685000, 655370000], [1966110000, 3932220000]], dtype=uint32) >>> img = Image([[0.0, 0.3], [0.5, 1.0]]) >>> img Image: 2 x 2 (float32) >>> img.to_int('uint8') array([[ 0, 76], [128, 255]], dtype=uint8) >>> img = Image([[False, True], [True, False]]) >>> img Image: 2 x 2 (bool) >>> img.to_int('uint8') array([[ 0, 255], [255, 0]], dtype=uint8) >>> img.to_int('uint16') array([[ 0, 65535], [65535, 0]], dtype=uint16)