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PaddleDetection

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PaddleDetection
提交 5b5346ec 编写于 作者: Y yangyaming
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上级 e7ac2889
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paddle/gserver/layers/DetectionUtil.cpp
浏览文件 @ 5b5346ec
......@@ -16,29 +16,33 @@ limitations under the License. */
namespace paddle {
size_t appendWithPermute(const MatrixPtr inMatrix,
size_t appendWithPermute(const Matrix& inMatrix,
size_t height,
size_t width,
size_t outTotalSize,
size_t outOffset,
size_t batchSize,
MatrixPtr outMatrix,
Matrix& outMatrix,
PermMode permMode,
bool useGpu) {
if (permMode == NCHWTONHWC) {
size_t inElementCnt = inMatrix->getElementCnt();
if (permMode == kNCHWToNHWC) {
size_t inElementCnt = inMatrix.getElementCnt();
size_t channels = inElementCnt / (height * width * batchSize);
size_t imgSize = height * width;
for (size_t i = 0; i < batchSize; ++i) {
size_t offset = i * (outTotalSize / batchSize) + outOffset;
const MatrixPtr inTmp =
Matrix::create(inMatrix->getData() + i * channels * imgSize,
channels,
const MatrixPtr inTmp = Matrix::create(
const_cast<real*>(inMatrix.getData()) + i * channels * imgSize,
channels,
imgSize,
false,
useGpu);
MatrixPtr outTmp =
Matrix::create(const_cast<real*>(outMatrix.getData()) + offset,
imgSize,
channels,
false,
useGpu);
MatrixPtr outTmp = Matrix::create(
outMatrix->getData() + offset, imgSize, channels, false, useGpu);
inTmp->transpose(outTmp, false);
}
return channels * imgSize;
......@@ -47,29 +51,33 @@ size_t appendWithPermute(const MatrixPtr inMatrix,
}
}
size_t decomposeWithPermute(const MatrixPtr inMatrix,
size_t decomposeWithPermute(const Matrix& inMatrix,
size_t height,
size_t width,
size_t inTotalSize,
size_t inOffset,
size_t batchSize,
MatrixPtr outMatrix,
Matrix& outMatrix,
PermMode permMode,
bool useGpu) {
if (permMode == NHWCTONCHW) {
size_t outElementCnt = outMatrix->getElementCnt();
if (permMode == kNHWCToNCHW) {
size_t outElementCnt = outMatrix.getElementCnt();
size_t channels = outElementCnt / (height * width * batchSize);
size_t imgSize = height * width;
for (size_t i = 0; i < batchSize; ++i) {
size_t offset = i * (inTotalSize / batchSize) + inOffset;
const MatrixPtr inTmp = Matrix::create(
inMatrix->getData() + offset, imgSize, channels, false, useGpu);
MatrixPtr outTmp =
Matrix::create(outMatrix->getData() + i * channels * imgSize,
channels,
const MatrixPtr inTmp =
Matrix::create(const_cast<real*>(inMatrix.getData()) + offset,
imgSize,
channels,
false,
useGpu);
MatrixPtr outTmp = Matrix::create(
const_cast<real*>(outMatrix.getData()) + i * channels * imgSize,
channels,
imgSize,
false,
useGpu);
inTmp->transpose(outTmp, false);
}
return channels * imgSize;
......@@ -99,9 +107,10 @@ real jaccardOverlap(const NormalizedBBox& bbox1, const NormalizedBBox& bbox2) {
}
}
vector<real> encodeBBoxWithVar(const NormalizedBBox& priorBBox,
const vector<real> priorBBoxVar,
const NormalizedBBox& gtBBox) {
void encodeBBoxWithVar(const NormalizedBBox& priorBBox,
const vector<real> priorBBoxVar,
const NormalizedBBox& gtBBox,
vector<real>& outVec) {
real priorBBoxWidth = priorBBox.getWidth();
real priorBBoxHeight = priorBBox.getHeight();
real priorBBoxCenterX = priorBBox.getCenterX();
......@@ -112,17 +121,15 @@ vector<real> encodeBBoxWithVar(const NormalizedBBox& priorBBox,
real gtBBoxCenterX = gtBBox.getCenterX();
real gtBBoxCenterY = gtBBox.getCenterY();
vector<real> offsetParam;
offsetParam.push_back((gtBBoxCenterX - priorBBoxCenterX) / priorBBoxWidth /
priorBBoxVar[0]);
offsetParam.push_back((gtBBoxCenterY - priorBBoxCenterY) / priorBBoxHeight /
priorBBoxVar[1]);
offsetParam.push_back(std::log(std::fabs(gtBBoxWidth / priorBBoxWidth)) /
priorBBoxVar[2]);
offsetParam.push_back(std::log(std::fabs(gtBBoxHeight / priorBBoxHeight)) /
priorBBoxVar[3]);
return offsetParam;
outVec.clear();
outVec.push_back((gtBBoxCenterX - priorBBoxCenterX) / priorBBoxWidth /
priorBBoxVar[0]);
outVec.push_back((gtBBoxCenterY - priorBBoxCenterY) / priorBBoxHeight /
priorBBoxVar[1]);
outVec.push_back(std::log(std::fabs(gtBBoxWidth / priorBBoxWidth)) /
priorBBoxVar[2]);
outVec.push_back(std::log(std::fabs(gtBBoxHeight / priorBBoxHeight)) /
priorBBoxVar[3]);
}
NormalizedBBox decodeBBoxWithVar(const NormalizedBBox& priorBBox,
......@@ -318,9 +325,9 @@ void matchBBox(const vector<NormalizedBBox>& priorBBoxes,
}
pair<size_t, size_t> generateMatchIndices(
const MatrixPtr priorValue,
const Matrix& priorValue,
const size_t numPriorBBoxes,
const MatrixPtr gtValue,
const Matrix& gtValue,
const int* gtStartPosPtr,
const size_t seqNum,
const vector<vector<real>>& maxConfScore,
......@@ -331,7 +338,7 @@ pair<size_t, size_t> generateMatchIndices(
vector<vector<int>>* matchIndicesVecPtr,
vector<vector<int>>* negIndicesVecPtr) {
vector<NormalizedBBox> priorBBoxes; // share same prior bboxes
getBBoxFromPriorData(priorValue->getData(), numPriorBBoxes, priorBBoxes);
getBBoxFromPriorData(priorValue.getData(), numPriorBBoxes, priorBBoxes);
size_t totalPos = 0;
size_t totalNeg = 0;
for (size_t n = 0; n < batchSize; ++n) {
......@@ -349,7 +356,7 @@ pair<size_t, size_t> generateMatchIndices(
}
vector<NormalizedBBox> gtBBoxes;
getBBoxFromLabelData(
gtValue->getData() + gtStartPosPtr[n] * 6, numGTBBoxes, gtBBoxes);
gtValue.getData() + gtStartPosPtr[n] * 6, numGTBBoxes, gtBBoxes);
matchBBox(
priorBBoxes, gtBBoxes, overlapThreshold, &matchIndices, &matchOverlaps);
......@@ -523,7 +530,7 @@ void getDetectionOutput(const real* confData,
const size_t batchSize,
const vector<map<size_t, vector<size_t>>>& allIndices,
const vector<vector<NormalizedBBox>>& allDecodedBBoxes,
MatrixPtr out) {
Matrix& out) {
MatrixPtr outBuffer;
Matrix::resizeOrCreate(outBuffer, numKept, 7, false, false);
real* bufferData = outBuffer->getData();
......@@ -550,7 +557,7 @@ void getDetectionOutput(const real* confData,
}
}
}
out->copyFrom(bufferData, numKept * 7);
out.copyFrom(bufferData, numKept * 7);
}
NormalizedBBox clipBBox(const NormalizedBBox& bbox) {
......
paddle/gserver/layers/DetectionUtil.h
浏览文件 @ 5b5346ec
......@@ -42,10 +42,12 @@ struct BBoxBase {
T getSize() const { return getWidth() * getHeight(); }
// coordinate of bounding box
T xMin;
T yMin;
T xMax;
T yMax;
// whether difficult object (e.g. object with heavy occlusion is difficult)
bool isDifficult;
};
......@@ -53,31 +55,31 @@ struct NormalizedBBox : BBoxBase<real> {
NormalizedBBox() : BBoxBase<real>() {}
};
enum PermMode { NCHWTONHWC, NHWCTONCHW };
enum PermMode { kNCHWToNHWC, kNHWCToNCHW };
/**
* @brief First permute input maxtrix then append to output matrix
*/
size_t appendWithPermute(const MatrixPtr inMatrix,
size_t appendWithPermute(const Matrix& inMatrix,
size_t height,
size_t width,
size_t outTotalSize,
size_t outOffset,
size_t batchSize,
MatrixPtr outMatrix,
Matrix& outMatrix,
PermMode permMode,
bool useGpu);
/**
* @brief First permute input maxtrix then decompose to output
*/
size_t decomposeWithPermute(const MatrixPtr inMatrix,
size_t decomposeWithPermute(const Matrix& inMatrix,
size_t height,
size_t width,
size_t totalSize,
size_t offset,
size_t batchSize,
MatrixPtr outMatrix,
Matrix& outMatrix,
PermMode permMode,
bool useGpu);
......@@ -89,15 +91,17 @@ size_t decomposeWithPermute(const MatrixPtr inMatrix,
real jaccardOverlap(const NormalizedBBox& bbox1, const NormalizedBBox& bbox2);
/**
* @brief Compute offset parameters between prior bbox and groundtruth bbox
* @brief Compute offset parameters between prior bbox and ground truth bbox
* and variances of prior bbox are considered
* @param priorBBox Input prior bbox
* @param priorBBoxVar Variance parameters of prior bbox
* @param gtBBox Groundtruth bbox
* @param outVec Output vector
*/
vector<real> encodeBBoxWithVar(const NormalizedBBox& priorBBox,
const vector<real> priorBBoxVar,
const NormalizedBBox& gtBBox);
void encodeBBoxWithVar(const NormalizedBBox& priorBBox,
const vector<real> priorBBoxVar,
const NormalizedBBox& gtBBox,
vector<real>& outVec);
/**
* @brief Decode prior bbox with offset parameters
......@@ -194,9 +198,9 @@ negative examples
* @param negIndicesVecPtr Save indices of negative prior bbox
*/
pair<size_t, size_t> generateMatchIndices(
const MatrixPtr priorValue,
const Matrix& priorValue,
const size_t numPriorBBoxes,
const MatrixPtr gtValue,
const Matrix& gtValue,
const int* gtStartPosPtr,
const size_t seqNum,
const vector<vector<real>>& maxConfScore,
......@@ -298,7 +302,7 @@ void getDetectionOutput(const real* confData,
const size_t batchSize,
const vector<map<size_t, vector<size_t>>>& allIndices,
const vector<vector<NormalizedBBox>>& allDecodedBBoxes,
MatrixPtr out);
Matrix& out);
NormalizedBBox clipBBox(const NormalizedBBox& bbox);
......
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