python3图片验证码识别种类最多第三方模块-MuggleOCR

官网下载地址

https://pypi.org/project/muggle-ocr/
pip install muggle_ocr
pip install muggle_ocr -i http://pypi.douban.com/simple --trusted-host pypi.douban.com

案例1

导入包

import time# 1. 导入包
import muggle_ocr"""
使用预置模型，预置模型包含了[ModelType.OCR, ModelType.Captcha] 两种
其中 ModelType.OCR 用于识别普通印刷文本, ModelType.Captcha 用于识别4-6位简单英数验证码"""# 打开印刷文本图片
with open(r"test1.png", "rb") as f:ocr_bytes = f.read()# 打开验证码图片
with open(r"test2.jpg", "rb") as f:captcha_bytes = f.read()# 2. 初始化；model_type 可选: [ModelType.OCR, ModelType.Captcha]
sdk = muggle_ocr.SDK(model_type=muggle_ocr.ModelType.OCR)# ModelType.Captcha 可识别光学印刷文本
for i in range(5):st = time.time()# 3. 调用预测函数text = sdk.predict(image_bytes=ocr_bytes)print(text, time.time() - st)# ModelType.Captcha 可识别4-6位验证码
sdk = muggle_ocr.SDK(model_type=muggle_ocr.ModelType.Captcha)
for i in range(5):st = time.time()# 3. 调用预测函数text = sdk.predict(image_bytes=captcha_bytes)print(text, time.time() - st)"""
使用自定义模型
支持基于 https://github.com/kerlomz/captcha_trainer 框架训练的模型
训练完成后，进入导出编译模型的[out]路径下, 把[graph]路径下的pb模型和[model]下的yaml配置文件放到同一路径下。
将 conf_path 参数指定为 yaml配置文件 的绝对或项目相对路径即可，其他步骤一致，如下示例：
"""
with open(r"test3.jpg", "rb") as f:b = f.read()
sdk = muggle_ocr.SDK(conf_path="./ocr.yaml")
text = sdk.predict(image_bytes=b)

案例2

import time
import muggle_ocr
import os
sdk = muggle_ocr.SDK(model_type=muggle_ocr.ModelType.OCR)
root_dir = r"./imgs"
for i in os.listdir(root_dir):
n = os.path.join(root_dir, i)
with open(n, "rb") as f:
b = f.read()
st = time.time()
text = sdk.predict(image_bytes=b)
print(i, text, time.time() - st)

案例3

import datetime
import time
import requests
import json
import base64
import muggle_ocr
import random
import warningswarnings.filterwarnings("ignore")def login_qufenqi():sdk = muggle_ocr.SDK(model_type=muggle_ocr.ModelType.Captcha)# sdk = muggle_ocr.SDK(model_type=muggle_ocr.ModelType.OCR)# num_str = ''.join(str(random.choice(range(10))) for _ in range(7))# 获取图片url = "https://passport.qufenqi.com/verify/getimg?r=0.05915737242270325"headers = {"authority": "passport.qufenqi.com","method": "GET","path": "/verify/getimg?r=0.05915737242270325","scheme": "https","accept": "image/webp,image/apng,image/*,*/*;q=0.8","accept-encoding": "gzip, deflate, br","accept-language": "zh-CN,zh;q=0.9,en;q=0.8","referer": "https://passport.qufenqi.com/i/resetloginpass","sec-fetch-dest": "image","sec-fetch-mode": "no-cors","sec-fetch-site": "same-origin","user-agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/83.0.4103.61 Safari/537.36",}response = requests.get(url, headers=headers, verify=False, timeout=10)print("图片验证码",response.content)with open('a.jpg', 'wb') as fw:fw.write(response.content)# 验证号码code = sdk.predict(response.content)print(code)url = "https://passport.qufenqi.com/i/resetloginpass/setaccount"headers = {"authority":"passport.qufenqi.com","method":"POST","path":"/i/resetloginpass/setaccount","scheme":"https","accept":"*/*","accept-encoding":"gzip, deflate, br","accept-language":"zh-CN,zh;q=0.9,en;q=0.8","content-length":"31","content-type":"application/x-www-form-urlencoded; charset=UTF-8","origin":"https://passport.qufenqi.com","referer":"https://passport.qufenqi.com/i/resetloginpass","sec-fetch-dest":"empty","sec-fetch-mode":"cors","sec-fetch-site":"same-origin","user-agent":"Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/83.0.4103.61 Safari/537.36","x-requested-with":"XMLHttpRequest",}time.sleep(1)data = {"mobile": "13918238777","imgcode": code} # input("输入验证码:")print(data)response = requests.post(url, headers=headers, data=data, verify=False, timeout=10)print(json.loads(response.text))if __name__ == '__main__':# while True:# time.sleep(1)login_qufenqi()

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