easyocr 本地部署模型识别图像 ocr

使用 easyocr 本地部署识别图像 ocr ,可以满足简单图像场景的ocr识别。

可以进行中文、英文 ocr 识别。

安装 python 库

python">pip install easyocr

识别本地模型下载地址：easyocr本地部署模型识别图像ocr-python实现资源-CSDN文库

也可通过程序直接下载官方链接

识别示例代码具体如下：

python">#-*-coding:utf-8-*-
# date:2021-03-21
# Author: DataBall - XIAN
# Function: 实现图像 OCR 定位和识别import os
os.environ['EASYOCR_DATA_DIR'] = './ckpt'
import easyocr
import cv2
import numpy as npif __name__ == "__main__":reader = easyocr.Reader(['ch_sim','en'], gpu=True,model_storage_directory = "./ckpt") # 加载本地模型path_img= r"examples\s1.jpg"# path_img= r"examples\s2.jpg"print("path_img:",path_img)result = reader.readtext(path_img)# print("result:",result)print("len:",len(result))img = cv2.imread(path_img)idx = 0for m_ in result:idx += 1print(" [{}] {} ".format(idx,m_)) # 打印 ocr 识别结果pts = np.array(m_[0])pts = pts.reshape((-1,1,2))  #reshape为10x1x2的numpy# print(pts.shape)try:# 绘制区域cv2.polylines(img,[pts],True,(255,0,0),5)cv2.polylines(img,[pts],True,(0,02,550),2)except:continuecv2.namedWindow("img",0)cv2.imshow("img",img)cv2.waitKey(0)

【英文】识别ocr的示例 log如下：

python">path_img: examples\s1.jpg
len: 6[1] ([[215, 220], [372, 220], [372, 269], [215, 269]], 'Mairie du Il', 0.7160473332813915)[2] ([[256, 321], [477, 321], [477, 383], [256, 383]], 'IPalais du LOUVRE', 0.4025377946164086)[3] ([[242, 418], [515, 418], [515, 474], [242, 474]], 'LES ARTS DECORATIFS', 0.9520467181101142)[4] ([[260, 538], [481, 538], [481, 590], [260, 590]], 'IMusee du LOUVRE', 0.6906741106430193)[5] ([[197, 637], [281, 637], [281, 675], [197, 675]], 'Theatre', 0.9687920530479167)[6] ([[195, 668], [378, 668], [378, 713], [195, 713]], 'du PALAIS-ROYAII', 0.38048889529807867)

【英文】识别示例显示结果如下图：

【中文】 ocr识别示例 log如下：

python">path_img: examples\s2.jpg
len: 18[1] ([[68, 4], [411, 4], [411, 120], [68, 120]], 'T', 0.02513536960325169)[2] ([[53, 199], [151, 199], [151, 219], [53, 219]], '小科(', 0.005845191785346051)[3] ([[51, 227], [121, 227], [121, 267], [51, 267]], '雷军', 0.9930638791278288)[4] ([[312, 302], [346, 302], [346, 328], [312, 328]], '你', 0.9963706343826892)[5] ([[315, 329], [409, 329], [409, 349], [315, 349]], '不愿薏听我的', 0.12065996670191718)[6] ([[319, 357], [385, 357], [385, 377], [319, 377]], '我就闭嘴', 0.3216131031513214)[7] ([[330, 414], [376, 414], [376, 438], [330, 438]], '加旦', 0.00018517122243834601)[8] ([[334, 442], [442, 442], [442, 466], [334, 466]], '以后证明你错了', 0.9192290431047331)[9] ([[333, 473], [397, 473], [397, 493], [333, 493]], '而我了', 0.7705055472317546)[10] ([[333, 501], [443, 501], [443, 521], [333, 521]], '那你要向我道歉', 0.82041872865308)[11] ([[361, 625], [443, 625], [443, 645], [361, 645]], '本刊记者 :花月', 0.5882038669206735)[12] ([[47, 653], [69, 653], [69, 665], [47, 665]], '20元', 0.1347271710802868)[13] ([[93, 653], [125, 653], [125, 665], [93, 665]], '塑36?}', 0.0013240344658845757)[14] ([[131, 653], [189, 653], [189, 665], [131, 665]], '201841月288', 0.615746162991523)[15] ([[200, 654], [224, 654], [224, 662], [200, 662]], 'SO', 0.10028489515834976)[16] ([[231, 653], [259, 653], [259, 665], [231, 665]], '0', 0.0001401376108900185)[17] ([[262, 654], [326, 654], [326, 662], [262, 662]], 'IT6ArC', 0.0034239475033886247)[18] ([[346, 654], [422, 654], [422, 662], [346, 662]], 'SONo', 0.014922617934644222)

【中文】识别示例显示结果如下图：