测试ocr文本的代码

点击查看代码

import time
import os
import cv2
from paddleocr import PaddleOCR
import numpy as np
import datetime
import os


def __init__ppocr(det_model_dir=r'D:\work\detect78\.paddleocr\whl\det\en\en_PP-OCRv4_det_infer',
                  rec_model_dir=r'D:\work\detect78\.paddleocr\whl\rec\en\en_PP-OCRv4_rec_infer',
                  cls_model_dir=r'D:\work\detect78\.paddleocr\whl\cls\ch_ppocr_mobile_v2.0_cls_infer'):
    ocr = PaddleOCR(use_angle_cls=True, lang='en', det_model_dir=det_model_dir, rec_model_dir=rec_model_dir,cls_model_dir=cls_model_dir)
    return ocr



image_path=r'./testimg/specialimg/xuegang.jpg'
image_path=r'./testimg/2_2_THRU.jpg'
# image_path=r'./testimg/specialimg/NKTHRU.png'
# image_path=r'./testimg/cropped_zimu.jpg'


ocr_model=__init__ppocr(det_model_dir=r'D:\work\detect78\.paddleocr\.paddleocr\whl\det\en\en_PP-OCRv4_det_infer',
                  rec_model_dir=r'D:\work\detect78\.paddleocr\.paddleocr\whl\rec\en\en_PP-OCRv4_rec_infer',
                  cls_model_dir=r'D:\work\detect78\.paddleocr\.paddleocr\whl\cls\ch_ppocr_mobile_v2.0_cls_infer')
image_original_color=cv2.imread(image_path, 1) #读取图像并以彩色模式加载（参数 1 表示加载为彩色图像）


img2 = image_original_color.copy()
# # 读取图像并转换为灰度图
image_original = cv2.imread(image_path, cv2.IMREAD_GRAYSCALE)#灰度图


# 对图像进行高斯模糊处理，以减少图像中的噪声和细节，参数 (5, 5) 表示高斯核的大小，0 表示标准差，根据需要可以调整。
image_gauss=cv2.GaussianBlur(image_original,(5,5),0)
image_original_color=cv2.GaussianBlur(image_original_color,(5,5),0)

start = time.time()
result = ocr_model.ocr(image_original_color)


print("ocr_result_rect_list",result)
end = time.time()

print(f"cost time: {end-start}")

start = time.time()
result = ocr_model.ocr(image_original_color)


print("ocr_result_rect_list",result)
end = time.time()

print(f"cost time: {end-start}")