Pillow & skimage & OpenCV image encode benchmark

benchmark

import numpy
from skimage import io
import time
from PIL import Image
import cv2
import sys, os

sys.path.append(os.path.join(os.path.dirname(__file__), '..'))
from config import projectPath

img = io.imread(f"{projectPath}/temp/fullimg.jpg")
now = time.time()
for i in range(20):
    io.imsave(f"{projectPath}/temp/skimg.jpg", img)
    print(f"{i} loop analysis.")
print(f"use {(time.time() - now) / 20}s per encode.")

image = Image.open(f"{projectPath}/temp/fullimg.jpg")
now = time.time()
for i in range(20):
    with open(f"{projectPath}/temp/skimg.jpg", "wb") as tempImg:
        image.save(tempImg, format='jpeg')
    print(f"{i} loop analysis.")
print(f"use {(time.time() - now) / 20}s per encode.")

opencvImage = cv2.cvtColor(numpy.array(image), cv2.COLOR_RGB2BGR)
now = time.time()
for i in range(20):
    cv2.imwrite('messigray.jpg', opencvImage)
    print(f"{i} loop analysis.")
print(f"use {(time.time() - now) / 20}s per encode.")

result

0 loop analysis.
1 loop analysis.
2 loop analysis.
3 loop analysis.
4 loop analysis.
5 loop analysis.
6 loop analysis.
7 loop analysis.
8 loop analysis.
9 loop analysis.
10 loop analysis.
11 loop analysis.
12 loop analysis.
13 loop analysis.
14 loop analysis.
15 loop analysis.
16 loop analysis.
17 loop analysis.
18 loop analysis.
19 loop analysis.
use 0.29269862174987793s per encode.
0 loop analysis.
1 loop analysis.
2 loop analysis.
3 loop analysis.
4 loop analysis.
5 loop analysis.
6 loop analysis.
7 loop analysis.
8 loop analysis.
9 loop analysis.
10 loop analysis.
11 loop analysis.
12 loop analysis.
13 loop analysis.
14 loop analysis.
15 loop analysis.
16 loop analysis.
17 loop analysis.
18 loop analysis.
19 loop analysis.
use 0.1573304533958435s per encode.
0 loop analysis.
1 loop analysis.
2 loop analysis.
3 loop analysis.
4 loop analysis.
5 loop analysis.
6 loop analysis.
7 loop analysis.
8 loop analysis.
9 loop analysis.
10 loop analysis.
11 loop analysis.
12 loop analysis.
13 loop analysis.
14 loop analysis.
15 loop analysis.
16 loop analysis.
17 loop analysis.
18 loop analysis.
19 loop analysis.
use 0.03837261199951172s per encode.