1.Python安装
官网下载较慢, 可到淘宝镜像源
https://registry.npmmirror.com/binary.html?path=python/安装3.8或3.9, windows下切勿安装3.10以上版本，paddleocr的opencv依赖无法安装。
2.安装依赖
代码语言：javascript复制pip install paddlepaddle -i https://mirror.baidu.com/pypi/simple
# 有可能会提示
# Microsoft Visual C 14.0 is required.
# Get it with "Build Tools for Visual Studio":
# https://visualstudio.microsoft.com/downloads/
# 务必带入版本号,否则默认是1.x版本的识别率较低
pip install "paddleocr>=2.0.1" -i https://mirror.baidu.com/pypi/simple
#如果执行paddleocr命令提示protobuf版本错误需要降级到3.20.0版本
pip uninstall protobuf
pip install protobuf==3.20.0 -i https://mirror.baidu.com/pypi/simple3.测试例子
默认会自动下载模型到用户目录, 默认是3.0版本, 也可手动下载指定模型目录。
代码语言：javascript复制from paddleocr import PaddleOCR
ocr = PaddleOCR(use_angle_cls=True, lang="ch", use_gpu=False)
# ocr = PaddleOCR(use_angle_cls=True, lang="ch", use_gpu=False,
# rec_model_dir='./model/v3.0/ch_PP-OCRv3_rec_infer/',
# cls_model_dir='./model/v3.0/ch_ppocr_mobile_v2.0_cls_infer/',
# det_model_dir='./model/v3.0/ch_PP-OCRv3_det_infer/')
img_path = './img/1.png'
result = ocr.ocr(img_path, det=True)
for line in result:
print(line)4.简单HTTP服务器，客户端代码
服务器端安装依赖
代码语言：javascript复制pip install flaskimport base64
from flask import Flask, request, render_template, jsonify
from paddleocr import PaddleOCR
import numpy as np
import cv2
app = Flask(__name__)
# 消息体最大50M
app.config['MAX_CONTENT_LENGTH'] = 50 * 1000 * 1000
app.config['JSON_AS_ASCII'] = False
iocr = PaddleOCR(use_angle_cls=True, lang="ch", use_gpu=False,
rec_model_dir='./model/v3.0/ch_PP-OCRv3_rec_infer/',
cls_model_dir='./model/v3.0/ch_ppocr_mobile_v2.0_cls_infer/',
det_model_dir='./model/v3.0/ch_PP-OCRv3_det_infer/')
@app.route('/')
def index():
return render_template('index.html')
@app.route('/ocr', methods=['post'])
def ocr():
image_bytes = None
# 文件上传
if 'image' in request.files.keys():
print(request.files)
image_bytes = request.files['image'].read()
# json图片内容base64
elif 'image' in request.json:
base64_image = request.json['image']
image_bytes = base64.b64decode(base64_image)
# error
else:
return jsonify({
'code': 400,
'msg': '错误的请求'
})
# FIXME Try catch
try:
image_ndarray = np.fromstring(image_bytes, np.uint8)
image = cv2.imdecode(image_ndarray, cv2.IMREAD_COLOR) # cv2.IMREAD_COLOR
result = iocr.ocr(image)
return jsonify({
'code': 200,
'data': [line[1] for line in result],
'msg': '操作成功'
})
except BaseException as exp:
print("OCR失败", exp)
return jsonify({
'code': 500,
'msg': 'OCR失败'
})
if __name__ == '__main__':
app.run(port=6666, debug=True, threaded=True)
注意代码勿用于生产
代码语言：javascript复制* Environment: production
WARNING: This is a development server. Do not use it in a production deployment.
Use a production WSGI server instead.客户端代码
代码语言：javascript复制import base64
import os
import requests
import time
import cv2
OCR_URL = "http://127.0.0.1:6666/ocr"
def ocr_file_request():
root = os.getcwd() '\img'
name = "1.png"
start_time = time.time()
file = os.path.join(root, name)
file_ptr = open(file, 'rb')
files_t = {'image': (name, file_ptr)}
headers = {'File-Name': name}
r = requests.post(OCR_URL, files=files_t, headers=headers)
file_ptr.close()
end_time = time.time()
print("ocr_request耗时: {:.2f}秒".format(end_time - start_time))
print(r.text)
def ocr_json_request():
img_path = os.getcwd() '\img\7.png'
img_file = open(img_path, "rb")
img_byte_obj = base64.b64encode(img_file.read())
img_file.close()
data = {"image": img_byte_obj.decode()}
headers = {'Content-Type': 'application/json;charset=UTF-8'} # 头文件
start_time = time.time()
r = requests.post(OCR_URL, json=data, headers=headers)
end_time = time.time()
print("ocr_json_request耗时: {:.2f}秒".format(end_time - start_time))
print(r.text)
ocr_json_request()
# ocr_file_request(5.总结
PaddleOCR通用文本识别整率和资源占用比chinese_lite_ocr之类是要好一些, 而对于特定场景的例如证件，仪表识别需要训练特定模型，使用PPOCRLabel标注足够量的图片，未完待续。
