* Copyright(C) 2022. Huawei Technologies Co.,Ltd. All rights reserved.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#include "PPYoloePostProcess.h"
#include <algorithm>
#include "MxBase/CV/ObjectDetection/Nms/Nms.h"
#include "MxBase/Log/Log.h"
#include "MxBase/Maths/FastMath.h"
namespace MxBase
{
const int OUTPUT_SIZE = 2;
const int MODEL_BOX_NUM = 8400;
const int RIGHTX_IDX = 2;
const int RIGHTY_IDX = 3;
const int OUTPUT_DIMS = 3;
PPYoloePostProcess::PPYoloePostProcess() {}
PPYoloePostProcess &PPYoloePostProcess::operator=(const PPYoloePostProcess &other)
{
if (this == &other)
{
return *this;
}
ObjectPostProcessBase::operator=(other);
objectnessThresh_ = other.objectnessThresh_;
iouThresh_ = other.iouThresh_;
return *this;
}
APP_ERROR PPYoloePostProcess::Init(const std::map<std::string, std::string> &postConfig)
{
LogDebug << "Start to Init PPYoloePostProcess.";
APP_ERROR ret = ObjectPostProcessBase::Init(postConfig);
if (ret != APP_ERR_OK)
{
LogError << GetErrorInfo(ret) << "Fail to superInit in ObjectPostProcessBase.";
return ret;
}
ret = configData_.GetFileValue<float>("OBJECTNESS_THRESH", objectnessThresh_, 0.0f, 1.0f);
if (ret != APP_ERR_OK)
{
LogWarn << GetErrorInfo(ret)
<< "Fail to read OBJECTNESS_THRESH from config, default is : " << objectnessThresh_;
}
ret = configData_.GetFileValue<float>("IOU_THRESH", iouThresh_, 0.0f, 1.0f);
if (ret != APP_ERR_OK)
{
LogWarn << GetErrorInfo(ret) << "Fail to read IOU_THRESH from config, default is : " << iouThresh_;
}
LogDebug << "End to Init PPYoloePostProcess.";
return APP_ERR_OK;
}
APP_ERROR PPYoloePostProcess::DeInit() { return APP_ERR_OK; }
void PPYoloePostProcess::ConstructBoxFromOutput(float *output, float *boxOutput, size_t offset,
std::vector<ObjectInfo> &objectInfo,
const ResizedImageInfo &resizedImageInfo)
{
int classId = -1;
float maxProb = scoreThresh_;
for (int labelIdx = 0; labelIdx < classNum_; labelIdx++)
{
if (maxProb < output[offset + labelIdx * MODEL_BOX_NUM])
{
maxProb = output[offset + labelIdx * MODEL_BOX_NUM];
classId = labelIdx;
}
}
if (classId < 0 || resizedImageInfo.widthOriginal == 0 || resizedImageInfo.heightOriginal == 0)
{
return;
}
float xGain = resizedImageInfo.widthResize * 1.0 / resizedImageInfo.widthOriginal;
float yGain = resizedImageInfo.heightResize * 1.0 / resizedImageInfo.heightOriginal;
auto leftX = boxOutput[offset * BOX_DIM] / xGain;
auto leftY = (boxOutput[offset * BOX_DIM + 1]) / yGain;
auto rightX = (boxOutput[offset * BOX_DIM + RIGHTX_IDX]) / xGain;
auto rightY = (boxOutput[offset * BOX_DIM + RIGHTY_IDX]) / yGain;
ObjectInfo obj;
obj.x0 = leftX;
obj.y0 = leftY;
obj.x1 = rightX;
obj.y1 = rightY;
obj.confidence = maxProb;
obj.classId = classId;
obj.className = configData_.GetClassName(obj.classId);
if (maxProb < separateScoreThresh_[obj.classId]) return;
objectInfo.push_back(obj);
}
void PPYoloePostProcess::LogObjectInfo(std::vector<std::vector<ObjectInfo>> &objectInfos)
{
for (size_t i = 0; i < objectInfos.size(); i++)
{
LogDebug << "Objects in Image No." << i << " are listed:";
for (auto &objInfo : objectInfos[i])
{
auto number = (separateScoreThresh_.size() > objInfo.classId) ? separateScoreThresh_[(int)objInfo.classId]
: scoreThresh_;
LogDebug << "Find object: classId(" << objInfo.classId << "), confidence(" << objInfo.confidence
<< "), scoreThresh(" << number << "), Coordinates (x0, y0)=(" << objInfo.x0 << ", " << objInfo.y0
<< "); (x1, y1)=(" << objInfo.x1 << ", " << objInfo.y1 << ").";
}
}
}
APP_ERROR PPYoloePostProcess::Process(const std::vector<TensorBase> &tensors,
std::vector<std::vector<ObjectInfo>> &objectInfos,
const std::vector<ResizedImageInfo> &resizedImageInfos,
const std::map<std::string, std::shared_ptr<void>> ¶mMap)
{
LogDebug << "Start to Process PPYoloePostProcess.";
if (resizedImageInfos.empty() || tensors.size() < OUTPUT_SIZE || tensors[1].GetShape().size() != OUTPUT_DIMS)
{
LogError << "Tensors or ResizedImageInfos is not provided for ppyoloe postprocess";
return APP_ERR_INPUT_NOT_MATCH;
}
if (tensors[1].GetShape()[1] != classNum_)
{
LogError << "The model output tensor[1][1] != classNum_.";
return APP_ERR_INPUT_NOT_MATCH;
}
uint32_t batchSize = tensors[0].GetShape()[0];
if (resizedImageInfos.size() != batchSize)
{
LogError << "The size of resizedImageInfo does not match the batchSize of tensors.";
return APP_ERR_INPUT_NOT_MATCH;
}
int rows = tensors[1].GetSize() / (classNum_ * batchSize);
for (size_t k = 0; k < batchSize; k++)
{
auto output = (float *)GetBuffer(tensors[1], k);
auto boxOutput = (float *)GetBuffer(tensors[0], k);
std::vector<ObjectInfo> objectInfo;
for (size_t i = 0; i < rows; ++i)
{
ConstructBoxFromOutput(output, boxOutput, i, objectInfo, resizedImageInfos[k]);
}
MxBase::NmsSort(objectInfo, iouThresh_);
objectInfos.push_back(objectInfo);
}
LogObjectInfo(objectInfos);
LogDebug << "End to Process PPYoloePostProcess.";
return APP_ERR_OK;
}
extern "C"
{
std::shared_ptr<MxBase::PPYoloePostProcess> GetObjectInstance()
{
LogInfo << "Begin to get PPYoloePostProcess instance.";
auto instance = std::make_shared<MxBase::PPYoloePostProcess>();
LogInfo << "End to get PPYoloePostProcess instance.";
return instance;
}
}
}