Processing time for paddleocr with multiprocessing

[FRAki73]

I measured the processing time for OCR by executing the following code.
The execution results are as follows, and the processing time is about 5 times longer when executed with multiprocessing.
I would like to know why the time is getting longer and what to do about it.
Can someone please help me?

Processing time of OCR: 1.1000 [sec]
OCR Result: The difficult thing in the life is
Processing time of OCR: 5.5675 [sec]
OCR Result: The difficult thing in the life is

import time
import multiprocessing
from multiprocessing import Process

#paddle OCR
from paddleocr import PaddleOCR

def normalEntry():
    processes = []
    p = Process(target=OCR_runnable, args=())
    processes.append(p)
    p.start()

    for process in processes:
        process.join()

def OCR_runnable():

    ocr = PaddleOCR(use_angle_cls=False, lang='en', show_log=False)

    start_time = time.time()
    result = ocr.ocr("./test.png", cls=False)
    end_time = time.time()
    elapsed_time = end_time - start_time
    print(f"Processing time of OCR: {elapsed_time:.4f} [sec]")
    print("OCR Result: " + result[0][0][1][0])

if __name__ == '__main__':
    multiprocessing.freeze_support()
    OCR_runnable()
    normalEntry()

Originally posted by @FRAki73 in #14221

[freemedom]

只看到这个代码了输出了一次时间