NumpyPerformanceTest

NumpyPerformanceTest.py

""" File name : NumpyPerformanceTest.py

Description : This script is to profile the performance of different numpy methods

Usage : python3 NumpyPerformanceTest.py

Author : Rex Low
"""

import cv2
import numpy as np
from time import time
np.random.seed(0)

green = [0,255,0]
blue  = [255,0,0]
red   = [0,0,255]
white = [255,255,255]
black = [0,0,0]

def np_simple():
    x = np.random.randint(0, 5, (500,500))
    row, col = x.shape
    y = np.zeros((row, col, 3), np.uint8)

    start = time()
    for i in range(row):
        for j in range(col):
            k = x[i][j]

            if k == 0:
                y[i][j] = green
            elif k == 1:
                y[i][j] = blue
            elif k == 2:
                y[i][j] = red
            elif k == 3:
                y[i][j] = white
            elif k == 4:
                y[i][j] = black
    return time() - start


def np_item():
    x = np.random.randint(0, 5, (500,500))
    row, col = x.shape
    y = np.zeros((row, col, 3), np.uint8)

    start = time()
    for i in range(row):
        for j in range(col):
            k = x.item(i, j)

            if k == 0:
                y.itemset((i, j, 0), green[0])
                y.itemset((i, j, 1), green[1])
                y.itemset((i, j, 2), green[2])
            elif k == 1:
                y.itemset((i, j, 0), blue[0])
                y.itemset((i, j, 1), blue[1])
                y.itemset((i, j, 2), blue[2])
            elif k == 2:
                y.itemset((i, j, 0), red[0])
                y.itemset((i, j, 1), red[1])
                y.itemset((i, j, 2), red[2])
            elif k == 3:
                y.itemset((i, j, 0), white[0])
                y.itemset((i, j, 1), white[1])
                y.itemset((i, j, 2), white[2])
            elif k == 4:
                y.itemset((i, j, 0), black[0])
                y.itemset((i, j, 1), black[1])
                y.itemset((i, j, 2), black[2])
    return time() - start


def np_palette():
    start = time()
    x = np.random.randint(0, 5, (500,500))
    color = np.array([green, blue, red, white, black], np.uint8)
    y = color[x]
    return time() - start


if __name__ == "__main__":
    iterations = 10
    np_simple_test = np.mean([np_simple() for _ in range(iterations)])
    np_item_test = np.mean([np_item() for _ in range(iterations)])
    np_palette_test = np.mean([np_palette() for _ in range(iterations)])

    print("Time taken for different methods")
    print("NP Simple   : {:.5f}s".format(np_simple_test))
    print("NP Item     : {:.5f}s".format(np_item_test))
    print("NP Palette  : {:.5f}s".format(np_palette_test))