MinMax and percentile MinMax stretching for numpy arrays

arrays_stretching_np_torch.py

# for np arrays
import numpy as np
def minmax(img):
    return(img-np.min(img) ) / (np.max(img)-np.min(img))

import numpy as np
def minmax_percentile(img,perc=2):
    lower = np.percentile(img,perc)
    upper = np.percentile(img,100-perc)
    img[img>upper] = upper
    img[img<lower] = lower
    return(img-np.min(img) ) / (np.max(img)-np.min(img))


# for tensors
import torch
def minmax_percentile(img, perc=2):
    lower = torch.kthvalue(img.flatten(), int(len(img.flatten()) * perc / 100)).values
    upper = torch.kthvalue(img.flatten(), int(len(img.flatten()) * (100 - perc) / 100)).values
    img = torch.where(img > upper, upper, img)
    img = torch.where(img < lower, lower, img)
    return (img - torch.min(img)) / (torch.max(img) - torch.min(img))

import torch
def minmax(img):
    return (img - torch.min(img)) / (torch.max(img) - torch.min(img))