验证码识别系统开发实战

核心实现代码

1. 验证码生成
   cpp

include <opencv2/opencv.hpp>

include

include

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std::string generateRandomText(int length = 4) {
const std::string chars = "ABCDEFGHJKLMNPQRSTUVWXYZ23456789";
std::random_device rd;
std::mt19937 gen(rd());
std::uniform_int_distribution<> dist(0, chars.size()-1);

std::string text;
for(int i = 0; i < length; ++i) {
    text += chars[dist(gen)];
}
return text;

}

cv::Mat createCaptchaImage(const std::string& text) {
cv::Mat img(40, 120, CV_8UC3, cv::Scalar(255, 255, 255));
int x = 10;

for(char c : text) {
    cv::putText(img, std::string(1, c), 
               cv::Point(x, 25), 
               cv::FONT_HERSHEY_SIMPLEX, 0.8,
               cv::Scalar(0, 0, 0), 1, cv::LINE_AA);
    x += 30;
}

return img;

}
2. 模型推理接口
cpp

include <Python.h>

std::string predictCaptcha(const cv::Mat& img) {
Py_Initialize();

PyObject* pModule = PyImport_ImportModule("captcha_model");
PyObject* pFunc = PyObject_GetAttrString(pModule, "predict");

cv::Mat gray;
cv::cvtColor(img, gray, cv::COLOR_BGR2GRAY);

npy_intp dims[2] = {gray.rows, gray.cols};
PyObject* pArray = PyArray_SimpleNewFromData(2, dims, NPY_UINT8, gray.data);

PyObject* pArgs = PyTuple_New(1);
PyTuple_SetItem(pArgs, 0, pArray);

PyObject* pResult = PyObject_CallObject(pFunc, pArgs);
std::string result = PyUnicode_AsUTF8(pResult);

Py_DECREF(pResult);
Py_DECREF(pArgs);
Py_DECREF(pModule);
Py_Finalize();

return result;

}
关键功能实现

1. 高性能批处理
   cpp

include

include

std::vectorstd::string batchPredict(const std::vectorcv::Mat& images) {
std::vector<std::futurestd::string> futures;

for(const auto& img : images) {
    futures.push_back(std::async(std::launch::async, predictCaptcha, img));
}

std::vector<std::string> results;
for(auto& f : futures) {
    results.push_back(f.get());
}

return results;

}
2. 图像预处理优化
cpp
cv::Mat preprocessImage(const cv::Mat& input) {
cv::Mat output;
cv::cvtColor(input, output, cv::COLOR_BGR2GRAY);
cv::resize(output, output, cv::Size(120, 40));
cv::threshold(output, output, 127, 255, cv::THRESH_BINARY);
return output;
}
部署与集成

1. 编译命令
   bash
   g++ -std=c++17 -O3 -I/usr/include/opencv4 -I/usr/include/python3.8
   -lopencv_core -lopencv_imgproc -lopencv_highgui -lpython3.8
   -o captcha_system main.cpp
2. Python模型接口
   python

captcha_model.py

import tensorflow as tf
import numpy as np

model = tf.keras.models.load_model('model.h5')

def predict(img_array):
img = img_array.astype(np.float32)/255.0
img = np.expand_dims(img, axis=(0,-1))
pred = model.predict(img)
chars = "ABCDEFGHJKLMNPQRSTUVWXYZ23456789"
return ''.join([chars[np.argmax(p)] for p in pred[0]])