cavis/libnd4j/include/ops/declarable/helpers/cpu/image_suppression.cpp
raver119 763a225c6a [WIP] More of CUDA operations (#69)
* initial commit

Signed-off-by: raver119 <raver119@gmail.com>

* - gruCell_bp further

Signed-off-by: Yurii <yurii@skymind.io>

* - further work on gruCell_bp

Signed-off-by: Yurii <yurii@skymind.io>

* Inverse matrix cublas implementation. Partial working revision.

* Separation of segment ops helpers. Max separation.

* Separated segment_min ops.

* Separation of segment_mean/sum/prod/sqrtN ops heleprs.

* Fixed diagonal processing with LUP decomposition.

* Modified inversion approach using current state of LU decomposition.

* Implementation of matrix_inverse op with cuda kernels. Working revision.

* Implemented sequence_mask cuda helper. Eliminated waste printf with matrix_inverse implementation. Added proper tests.

* - further work on gruCell_bp (ff/cuda)

Signed-off-by: Yurii <yurii@skymind.io>

* comment one test for gruCell_bp

Signed-off-by: Yurii <yurii@skymind.io>

* - provide cuda static_rnn

Signed-off-by: Yurii <yurii@skymind.io>

* Refactored random_shuffle op to use new random generator.

* Refactored random_shuffle op helper.

* Fixed debug tests with random ops tests.

* Implement random_shuffle op cuda kernel helper and tests.

* - provide cuda scatter_update

Signed-off-by: Yurii <yurii@skymind.io>

* Implementation of random_shuffle for linear case with cuda kernels and tests.

* Implemented random_shuffle with cuda kernels. Final revision.

* - finally gruCell_bp is completed

Signed-off-by: Yurii <yurii@skymind.io>

* Dropout op cuda helper implementation.

* Implemented dropout_bp cuda helper.

* Implemented alpha_dropout_bp with cuda kernel helpers.

* Refactored helper.

* Implementation of suppresion helper with cuda kernels.

* - provide cpu code fot hsvToRgb, rgbToHsv, adjustHue

Signed-off-by: Yurii <yurii@skymind.io>

* Using sort by value method.

* Implementation of image.non_max_suppression op cuda-based helper.

* - correcting and testing adjust_hue, adjust_saturation cpu/cuda code

Signed-off-by: Yurii <yurii@skymind.io>

* Added cuda device prefixes to declarations.

* Implementation of hashcode op with cuda helper. Initital revision.

* rnn cu impl removed

Signed-off-by: raver119 <raver119@gmail.com>
2019-07-20 23:20:41 +10:00

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4.4 KiB
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/*******************************************************************************
* Copyright (c) 2015-2018 Skymind, Inc.
*
* This program and the accompanying materials are made available under the
* terms of the Apache License, Version 2.0 which is available at
* https://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.
*
* SPDX-License-Identifier: Apache-2.0
******************************************************************************/
//
// @author sgazeos@gmail.com
//
#include <ops/declarable/helpers/image_suppression.h>
//#include <blas/NDArray.h>
#include <algorithm>
#include <numeric>
namespace nd4j {
namespace ops {
namespace helpers {
template <typename T>
static void nonMaxSuppressionV2_(NDArray* boxes, NDArray* scales, int maxSize, double threshold, NDArray* output) {
std::vector<Nd4jLong> indices(scales->lengthOf());
std::iota(indices.begin(), indices.end(), 0);
std::sort(indices.begin(), indices.end(), [scales](int i, int j) {return scales->e<T>(i) > scales->e<T>(j);});
// std::vector<int> selected(output->lengthOf());
std::vector<int> selectedIndices(output->lengthOf(), 0);
auto needToSuppressWithThreshold = [] (NDArray& boxes, int previousIndex, int nextIndex, T threshold) -> bool {
T minYPrev = nd4j::math::nd4j_min(boxes.e<T>(previousIndex, 0), boxes.e<T>(previousIndex, 2));
T minXPrev = nd4j::math::nd4j_min(boxes.e<T>(previousIndex, 1), boxes.e<T>(previousIndex, 3));
T maxYPrev = nd4j::math::nd4j_max(boxes.e<T>(previousIndex, 0), boxes.e<T>(previousIndex, 2));
T maxXPrev = nd4j::math::nd4j_max(boxes.e<T>(previousIndex, 1), boxes.e<T>(previousIndex, 3));
T minYNext = nd4j::math::nd4j_min(boxes.e<T>(nextIndex, 0), boxes.e<T>(nextIndex, 2));
T minXNext = nd4j::math::nd4j_min(boxes.e<T>(nextIndex, 1), boxes.e<T>(nextIndex, 3));
T maxYNext = nd4j::math::nd4j_max(boxes.e<T>(nextIndex, 0), boxes.e<T>(nextIndex, 2));
T maxXNext = nd4j::math::nd4j_max(boxes.e<T>(nextIndex, 1), boxes.e<T>(nextIndex, 3));
T areaPrev = (maxYPrev - minYPrev) * (maxXPrev - minXPrev);
T areaNext = (maxYNext - minYNext) * (maxXNext - minXNext);
if (areaNext <= T(0.f) || areaPrev <= T(0.f)) return false;
T minIntersectionY = nd4j::math::nd4j_max(minYPrev, minYNext);
T minIntersectionX = nd4j::math::nd4j_max(minXPrev, minXNext);
T maxIntersectionY = nd4j::math::nd4j_min(maxYPrev, maxYNext);
T maxIntersectionX = nd4j::math::nd4j_min(maxXPrev, maxXNext);
T intersectionArea =
nd4j::math::nd4j_max(T(maxIntersectionY - minIntersectionY), T(0.0f)) *
nd4j::math::nd4j_max(T(maxIntersectionX - minIntersectionX), T(0.0f));
T intersectionValue = intersectionArea / (areaPrev + areaNext - intersectionArea);
return intersectionValue > threshold;
};
// int numSelected = 0;
int numBoxes = boxes->sizeAt(0);
int numSelected = 0;
for (int i = 0; i < numBoxes; ++i) {
bool shouldSelect = numSelected < output->lengthOf();
PRAGMA_OMP_PARALLEL_FOR //_ARGS(firstprivate(numSelected))
for (int j = numSelected - 1; j >= 0; --j) {
if (shouldSelect)
if (needToSuppressWithThreshold(*boxes, indices[i], indices[selectedIndices[j]], T(threshold))) {
shouldSelect = false;
}
}
if (shouldSelect) {
output->p(numSelected, indices[i]);
selectedIndices[numSelected++] = i;
}
}
}
void nonMaxSuppressionV2(nd4j::LaunchContext * context, NDArray* boxes, NDArray* scales, int maxSize, double threshold, NDArray* output) {
BUILD_SINGLE_SELECTOR(boxes->dataType(), nonMaxSuppressionV2_, (boxes, scales, maxSize, threshold, output), NUMERIC_TYPES);
}
BUILD_SINGLE_TEMPLATE(template void nonMaxSuppressionV2_, (NDArray* boxes, NDArray* scales, int maxSize, double threshold, NDArray* output), NUMERIC_TYPES);
}
}
}