cnn_extractor.cpp
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#include "cnn_extractor.h"
#include <iostream>
#include "acl/acl.h"
#include "model_process.h"
#include "sy_errorinfo.h"
#include <time.h>
#include <sys/time.h>
#include <algorithm>
using namespace std;
namespace atlas_utils {
int CNNExtract::Init(const char* modelPath) {
ACL_CALL(aclrtGetRunMode(&runMode_), SY_SUCCESS, SY_FAILED);//获取当前昇腾AI软件栈的运行模式，根据不同的运行模式，后续的接口调用方式不同
ACL_CALL(model_.LoadModelFromFileWithMem(modelPath), SY_SUCCESS, SY_FAILED);//从文件加载离线模型数据，由用户自行管理模型运行的内存
ACL_CALL(model_.CreateDesc(), SY_SUCCESS, SY_FAILED);//获取模型的描述信息
ACL_CALL(model_.CreateOutput(outDims_), SY_SUCCESS, SY_FAILED);
ACL_CALL(model_.GetInputDims(inDims_), SY_SUCCESS, SY_FAILED);
modelHeight_ = inDims_[0][1];
modelWidth_ = inDims_[0][2];
return SY_SUCCESS;
}
int CNNExtract::Inference(ImageData& input) {
model_.CreateInput(input.data.get(), input.size);
ACL_CALL(model_.Execute(), SY_SUCCESS, SY_FAILED);
model_.DestroyInput(); //需调用CreateInput的销毁类接口DestroyInput！！！
return SY_SUCCESS;
}
int CNNExtract::GetInputWidth() {
return modelWidth_;
}
int CNNExtract::GetInputHeight() {
return modelHeight_;
}
int CNNExtract::PostProcess(vector<float>& results) {
aclmdlDataset* modelOutput = model_.GetModelOutputData();
int outDatasetNum = aclmdlGetDatasetNumBuffers(modelOutput);
for (int i = 0; i < outDatasetNum; i++) {
aclDataBuffer* dataBuffer = aclmdlGetDatasetBuffer(modelOutput, i);
if (dataBuffer == nullptr) {
return SY_FAILED;
}
uint32_t dataBufferSize = aclGetDataBufferSize(dataBuffer);
void* data = aclGetDataBufferAddr(dataBuffer);
if (data == nullptr) {
return SY_FAILED;
}
int length = dataBufferSize/sizeof(float);
float outInfo[length];
if (runMode_ == ACL_HOST) {
ACL_CALL(aclrtMemcpy(outInfo, sizeof(outInfo), data, sizeof(outInfo), ACL_MEMCPY_DEVICE_TO_HOST),
ACL_SUCCESS, SY_FAILED);
} else {
ACL_CALL(aclrtMemcpy(outInfo, sizeof(outInfo), data, sizeof(outInfo), ACL_MEMCPY_DEVICE_TO_DEVICE),ACL_SUCCESS, SY_FAILED);
//return SY_FAILED;
}
// //归一化
// float sum = 0.0;
// for(int j=0;j<length;j++){
// sum = sum + outInfo[j]*outInfo[j];
// }
// sum = sqrt(sum) + 1e-6;
// for(int j=0;j<length;j++){
// results.emplace_back(outInfo[j]/sum);
// }
for(uint32_t b = 0; b < length; b++) {
results.emplace_back(outInfo[b]);
}
}
return SY_SUCCESS;
}
void CNNExtract::Release() {
model_.Unload();
model_.DestroyDesc();
model_.DestroyOutput();
}
}