numpy.resize - Tutorialspoint
www.tutorialspoint.com › numpy › numpy_resizeimport numpy as np a = np.array( [ [1,2,3], [4,5,6]]) print 'First array:' print a print ' ' print 'The shape of first array:' print a.shape print ' ' b = np.resize(a, (3,2)) print 'Second array:' print b print ' ' print 'The shape of second array:' print b.shape print ' ' # Observe that first row of a is repeated in b since size is bigger print 'Resize the second array:' b = np.resize(a, (3,3)) print b.
python - Numpy Resize/Rescale Image - Stack Overflow
stackoverflow.com › questions › 48121916import math import numpy def resize_linear(image_matrix, new_height:int, new_width:int): """Perform a pure-numpy linear-resampled resize of an image.""" output_image = numpy.zeros((new_height, new_width), dtype=image_matrix.dtype) original_height, original_width = image_matrix.shape inv_scale_factor_y = original_height/new_height inv_scale_factor_x = original_width/new_width # This is an ugly serial operation.
numpy.resize — NumPy v1.22 Manual
numpy.org › reference › generatednumpy.resize¶ numpy. resize (a, new_shape) [source] ¶ Return a new array with the specified shape. If the new array is larger than the original array, then the new array is filled with repeated copies of a. Note that this behavior is different from a.resize(new_shape) which fills with zeros instead of repeated copies of a. Parameters a array_like