背景
OpenCV介绍
OpenCV（Open Source Computer Vision Library）是一个开源的计算机视觉和机器学习软件库。它由一系列的C函数和少量C++类构成，同时提供Python、Java和MATLAB等语言的接口，实现了图像处理和计算机视觉方面的很多通用算法。
OpenCV具有极广的应用领域，它包括但不限于：
- 人脸识别和物体识别：这是OpenCV的一项重要功能，应用在许多领域，如安全监控、交互设计等。
- 图像和视频分析：如图像增强、图像分割、视频跟踪等。
- 图像合成和3D重建：在图像处理和计算机视觉领域，OpenCV可以用于创建AR或VR效果，生成3D模型等。
- 机器学习：OpenCV内置了大量的机器学习算法，可以用于图像分类、聚类等任务。
- 深度学习：OpenCV中的dnn模块提供了一系列深度学习模型的接口，用户可以加载预训练模型进行图像识别、目标检测等任务。
本文主要介绍OpenHarmony如何用opencvlib进行应用样例开发
应用开发
创建HAP
- 通过DevEcoStudio创建项目“File->New->Create Project"创建一个工程
-
工程创建完毕后，界面入口为Index.ets
引用OpenCV lib库
-
引入opencv头文件库，放在include目录下
-
引入lib库，放在libs目录下
-
修改CMAKE
-
增加common头文件和cpp文件
//
// Created on 2024/3/5.
//
// Node APIs are not fully supported. To solve the compilation error of the interface cannot be found,
// please include "napi/native_api.h".
#ifndef OpencvSample_common_H
#define OpencvSample_common_H
#include <string>
#include <stdio.h>
#include <js_native_api.h>
#include <js_native_api_types.h>
#include <vector>
#include "opencv2/opencv.hpp"
#include "opencv2/imgcodecs/legacy/constants_c.h"
#include "hilog/log.h"
#include "napi/native_api.h"
#include "rawfile/raw_file_manager.h"
#include "rawfile/raw_file.h"
#include "rawfile/raw_dir.h"
#define GLOBAL_RESMGR (0xFFEE)
constexpr int32_t RGB_565 = 2;
constexpr int32_t RGBA_8888 = 3;
constexpr int32_t STR_MAX_SIZE = 200;
constexpr int32_t LONG_STR_MAX_SIZE = 1024;
constexpr int32_t ERR_OK = 0;
constexpr int8_t NO_ERROR = 0;
constexpr int8_t ERROR = -1;
constexpr uint8_t PARAM0 = 0;
constexpr uint8_t PARAM1 = 1;
constexpr uint8_t PARAM2 = 2;
constexpr uint8_t PARAM3 = 3;
constexpr uint8_t PARAM4 = 4;
constexpr uint8_t PARAM5 = 5;
constexpr uint8_t PARAM6 = 6;
constexpr uint8_t PARAM7 = 7;
constexpr uint8_t PARAM8 = 8;
constexpr uint8_t PARAM9 = 9;
constexpr uint8_t PARAM10 = 10;
constexpr uint8_t PARAM11 = 11;
constexpr uint8_t PARAM12 = 12;
constexpr int32_t ARGS_ONE = 1;
constexpr int32_t ARGS_TWO = 2;
constexpr int32_t ONLY_CALLBACK_MAX_PARA = 1;
constexpr int32_t ONLY_CALLBACK_MIN_PARA = 0;
struct CallbackPromiseInfo {
napi_ref callback = nullptr;
napi_deferred deferred = nullptr;
bool isCallback = false;
int32_t errorCode = 0;
};
template <typename T> void FreeMemory(T *p) {
if (p == nullptr) {
return;
}
delete p;
p = nullptr;
}
template <typename T> void FreeMemoryArray(T *p) {
if (p == nullptr) {
return;
}
delete[] p;
p = nullptr;
}
#define NAPI_RETVAL_NOTHING
#define NAPI_CALL_BASE(env, theCall, retVal) \
do { \
if ((theCall) != 0) { \
return retVal; \
} \
} while (0)
#define NAPI_CALL(env, theCall) NAPI_CALL_BASE(env, theCall, nullptr)
#define NAPI_CALL_RETURN_VOID(env, theCall) NAPI_CALL_BASE(env, theCall, NAPI_RETVAL_NOTHING)
extern bool GetMatFromRawFile(napi_env env, napi_value jsResMgr, const std::string &rawfileDir,
const std::string &fileName, cv::Mat &srcImage);
extern bool cvtMat2Pixel(cv::InputArray _src, cv::OutputArray &_dst, int code);
extern napi_value NapiGetNull(napi_env env);
extern uint32_t GetMatDataBuffSize(const cv::Mat &mat);
extern bool CreateArrayBuffer(napi_env env, uint8_t *src, size_t srcLen, napi_value *res);
extern napi_value NapiGetUndefined(napi_env env);
extern napi_value GetCallbackErrorValue(napi_env env, int32_t errCode);
extern napi_value NapiGetBoolean(napi_env env, const bool &isValue);
extern uint32_t GetMatDataBuffSize(const cv::Mat &mat);
extern void SetCallback(const napi_env &env, const napi_ref &callbackIn, const int32_t &errorCode,
const napi_value &result);
extern void SetPromise(const napi_env &env, const napi_deferred &deferred, const int32_t &errorCode,
const napi_value &result);
extern void ReturnCallbackPromise(const napi_env &env, const CallbackPromiseInfo &info, const napi_value &result);
extern napi_value JSParaError(const napi_env &env, const napi_ref &callback);
extern void PaddingCallbackPromiseInfo(const napi_env &env, const napi_ref &callback, CallbackPromiseInfo &info,
napi_value &promise);
extern bool WrapJsPixelInfoInfo(napi_env env, cv::Mat &outMat, napi_value &result);
#endif //OpencvSample_common_H
-
增加灰度转换方法
using namespace std;
using namespace cv;
static const char *TAG = "[opencv_img2Gray]";
napi_value Img2Gray(napi_env env, napi_callback_info info) {
OH_LOG_Print(LOG_APP, LOG_INFO, GLOBAL_RESMGR, TAG, "Img2Gray Begin");
napi_value result = NapiGetNull(env);
size_t argc = 3;
napi_value argv[3] = {nullptr};
napi_get_cb_info(env, info, &argc, argv, nullptr, nullptr);
size_t strSize;
char strBuf[256];
napi_get_value_string_utf8(env, argv[1], strBuf, sizeof(strBuf), &strSize);
std::string fileDir(strBuf, strSize);
OH_LOG_Print(LOG_APP, LOG_INFO, GLOBAL_RESMGR, TAG, "fileDir：%{public}s", fileDir.c_str());
napi_get_value_string_utf8(env, argv[2], strBuf, sizeof(strBuf), &strSize);
std::string fileName(strBuf, strSize);
OH_LOG_Print(LOG_APP, LOG_INFO, GLOBAL_RESMGR, TAG, "fileName：%{public}s", fileName.c_str());
Mat srcImage;
if (!GetMatFromRawFile(env, argv[0], fileDir, fileName, srcImage)) {
OH_LOG_Print(LOG_APP, LOG_ERROR, GLOBAL_RESMGR, TAG, "Get Mat from rawfile failed!.");
return result;
}
Mat srcGray;
cvtColor(srcImage, srcGray, COLOR_RGB2GRAY);
// 將图像转换为pixelMap格式
Mat outMat;
cvtMat2Pixel(srcGray, outMat, RGBA_8888);
OH_LOG_Print(LOG_APP, LOG_INFO, GLOBAL_RESMGR, TAG, "outMat size: %{public}d, cols：%{public}d, rows：%{public}d",
outMat.total(), outMat.cols, outMat.rows);
napi_create_object(env, &result);
bool retVal = WrapJsPixelInfoInfo(env, outMat, result);
if (!retVal) {
OH_LOG_Print(LOG_APP, LOG_ERROR, GLOBAL_RESMGR, TAG, "WrapJsInfo failed!.");
}
return result;
}
-
导出 //hello.cpp
EXTERN_C_START
static napi_value Init(napi_env env, napi_value exports)
{
napi_property_descriptor desc[] = {
{"add", nullptr, Add, nullptr, nullptr, nullptr, napi_default, nullptr},
{"img2Gray", nullptr, Img2Gray, nullptr, nullptr, nullptr, napi_default, nullptr}
};
napi_define_properties(env, exports, sizeof(desc) / sizeof(desc[0]), desc);
return exports;
}
EXTERN_C_END
-
导出接口 //index.d.ts
import resourceManager from '@ohos.resourceManager';
export interface PixelInfo {
rows: number;
cols: number;
buffSize: number;
byteBuffer: ArrayBuffer;
}
export const add: (a: number, b: number) => number;
export const img2Gray: (resmgr: resourceManager.ResourceManager, path: string, file: string) => PixelInfo;
-
在页面添加交互 // index.ets
Column() {
Image(this.isGray ? this.imagePixelMap : $rawfile('lena.jpg'))
.margin({ left: 24, right: 24 })
.objectFit(ImageFit.Contain)
.id('backBtn')
}
.width('100%')
.height('60%')
.alignItems(HorizontalAlign.Center)
.justifyContent(FlexAlign.Start)
Row() {
Button($r('app.string.image_gray'), { type: ButtonType.Capsule })
.backgroundColor(this.isGray ? Color.Gray : Color.Blue)
.margin({ left: 24 })
.width('30%')
.id('imageGray')
.enabled(this.isGray ? false : true)
.onClick(() => {
let pixelInfo: testNapi.PixelInfo = testNapi.img2Gray(getContext().resourceManager, '', 'lena.jpg');
Logger.info(TAG, `pixelInfo buffSize: ${pixelInfo.buffSize}`);
let opts: image.InitializationOptions = {
editable: true,
pixelFormat: this.pixelMapFormat,
size: { height: pixelInfo.rows, width: pixelInfo.cols }
}
image.createPixelMap(pixelInfo.byteBuffer, opts, (error, pixelmap) => {
if (error) {
Logger.error(TAG, `Failed to create pixelmap error_code ${error.code}`);
} else {
Logger.info(TAG, 'Succeeded in creating pixelmap.');
this.imagePixelMap = pixelmap;
}
})
this.isGray = true;
})
Button($r('app.string.image_recover'), { type: ButtonType.Capsule })
.backgroundColor(Color.Blue)
.width('30%')
.id('imageRecover')
.onClick(() => {
this.isGray = false;
})
}
.width('100%')
-
展示
总结
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