opencv 手写选择题阅卷 (四)Android端 手机应用开发

opencv 手写选择题阅卷 (四)Android 手机应用开发

在PC端把代码调通以后开始开发Android 手机应用,因为主要功能代码为C++代码,所以需要通过NDK编译,JAVA通过JNI方式调用C++代码,好在opencv已经把android 下的库都编译好了,只需要连接就可以了,Android.mk文件内容如下:

LOCAL_PATH := $(call my-dir)

include $(CLEAR_VARS)

#OPENCV_CAMERA_MODULES:=off
OPENCV_INSTALL_MODULES:=off
OPENCV_LIB_TYPE:=STATIC

include H:\OpenCV-android-sdk\sdk\native\jni/OpenCV.mk

LOCAL_SRC_FILES := \
libWriterOCR.cpp \
H:\libWriterOCR\src\img_proc.cpp \
H:\libWriterOCR\src\recognition.cpp \
H:\libWriterOCR\src\table_proc.cpp \

LOCAL_C_INCLUDES += H:\libWriterOCR\include

LOCAL_LDLIBS += -llog -ldl -lm -landroid

LOCAL_MODULE := WriterOCR

include $(BUILD_SHARED_LIBRARY)

JNI接口中,输入图像数据数组和宽高,返回最终识别结果的 byte数组,主要代码如下:

extern "C" JNIEXPORT jbyteArray JNICALL Java_com_veryjuly_scl_writerscore_WriterOCR_doOCR(JNIEnv * env, jobject jobj, jbyteArray jbyteData, jint jwidth, jint jheight)
{
    ;
    //取输入的YUV图像数据指针
    jbyte * in_bytes = (jbyte *)(env)->GetByteArrayElements(jbyteData, );
    unsigned char * yuv420data = (unsigned char*)in_bytes;

    jbyteArray resultByteArray = (env)->NewByteArray( );
    jbyte *jresults = (env)->GetByteArrayElements(resultByteArray, );
    //保存结果的数组
    unsigned char *results = (unsigned char *)jresults;

    int width = jwidth;
    int height = jheight;

    //开始识别，注意返回值，看是不是成功识别了。
    rt = yuv420sp_ocr(results, yuv420data, width, height);
    )
        results[] = rt;

    //设置返回JAVA数组结果
    (env)->SetByteArrayRegion(resultByteArray, , , jresults);

    //释放输入的YUV图像数据指针
    (env)->ReleaseByteArrayElements(jbyteData, in_bytes, );
    return resultByteArray;
}

int yuv420sp_ocr(unsigned char *results, unsigned char  * yuvdata, int width, int height)
{
    ;
    IplImage *image;
    image = cvCreateImage(cvSize(width, height), IPL_DEPTH_8U, );

    int i, j;
    ; j < height; j++)
    {
        unsigned char *pPix = (unsigned char *)image->imageData + j*image->widthStep;
        unsigned char *pY = yuvdata + j*width;
        ; i < width; i++)
        {
            pPix[i] = pY[i];
        }
    }

    //
    ret = table_recognition(image, results);

    //结束，释放图像
    cvReleaseImage(&image);
    return ret;
}