shugeo
GitHub
commit
dbabd11f83
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@ -1422,6 +1422,7 @@ namespace nd4j {
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template <typename T>
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void p(const Nd4jLong i, const Nd4jLong j, const Nd4jLong k, const Nd4jLong l, const T value);
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void p(const Nd4jLong i, const Nd4jLong j, const Nd4jLong k, const Nd4jLong l, NDArray const& value);
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template <typename T>
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@ -4187,6 +4187,24 @@ void NDArray::p(const Nd4jLong i, const NDArray& scalar) {
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NDArray::registerPrimaryUse({this}, {&scalar});
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}
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////////////////////////////////////////////////////////////////////////
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void NDArray::p(const Nd4jLong i, const Nd4jLong j, const Nd4jLong k, const Nd4jLong l, const NDArray& scalar) {
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if(!scalar.isScalar())
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throw std::invalid_argument("NDArray::p method: input array must be scalar!");
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if (i >= _length)
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throw std::invalid_argument("NDArray::p(i, NDArray_scalar): input index is out of array length !");
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// void *p = reinterpret_cast<void *>(scalar.getBuffer());
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Nd4jLong coords[4] = {i, j, k, l};
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auto xOffset = shape::getOffset(getShapeInfo(), coords);
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NDArray::preparePrimaryUse({this}, {&scalar}, true);
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// BUILD_SINGLE_PARTIAL_SELECTOR(dataType(), templatedSet<, T>(this->getBuffer(), xOffset, p), LIBND4J_TYPES);
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BUILD_SINGLE_SELECTOR(scalar.dataType(), templatedSet, (this->getBuffer(), xOffset, scalar.dataType(), scalar.getBuffer()), LIBND4J_TYPES);
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NDArray::registerPrimaryUse({this}, {&scalar});
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}
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//////////////////////////////////////////////////////////////////////////
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void NDArray::addRowVector(const NDArray *row, NDArray *target) const {
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@ -0,0 +1,49 @@
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/*******************************************************************************
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* Copyright (c) 2015-2018 Skymind, Inc.
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*
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* This program and the accompanying materials are made available under the
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* terms of the Apache License, Version 2.0 which is available at
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* https://www.apache.org/licenses/LICENSE-2.0.
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
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* WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
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* License for the specific language governing permissions and limitations
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* under the License.
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*
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* SPDX-License-Identifier: Apache-2.0
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******************************************************************************/
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//
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// @author George A. Shulinok <sgazeos@gmail.com>
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//
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#include <op_boilerplate.h>
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#if NOT_EXCLUDED(OP_draw_bounding_boxes)
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#include <ops/declarable/headers/parity_ops.h>
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#include <ops/declarable/helpers/image_draw_bounding_boxes.h>
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namespace nd4j {
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namespace ops {
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OP_IMPL(draw_bounding_boxes, 3, 1, true) {
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auto images = INPUT_VARIABLE(0);
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auto boxes = INPUT_VARIABLE(1);
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auto colors = INPUT_VARIABLE(2);
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auto output = OUTPUT_VARIABLE(0);
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helpers::drawBoundingBoxesFunctor(block.launchContext(), images, boxes, colors, output);
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return ND4J_STATUS_OK;
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}
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DECLARE_TYPES(draw_bounding_boxes) {
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getOpDescriptor()
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->setAllowedInputTypes(0, {HALF, FLOAT32})// TF allows HALF and FLOAT32 only
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->setAllowedInputTypes(1, {FLOAT32}) // as TF
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->setAllowedInputTypes(2, {FLOAT32}) // as TF
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->setAllowedOutputTypes({HALF, FLOAT32}); // TF allows HALF and FLOAT32 only
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}
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}
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}
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#endif
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@ -1244,6 +1244,23 @@ namespace nd4j {
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DECLARE_CUSTOM_OP(extract_image_patches, 1, 1, false, 0, 7);
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#endif
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/**
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* draw_bounding_boxes op - modified input image with given colors exept given boxes.
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*
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* input params:
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* 0 - images tensor (4D) with shape {batch, width, height, channels}, where channes is 1 (BW image),
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* 3 (RGB) or 4 (RGBA)
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* 1 - boxes tensor (3D) with shape {batch, number_of_boxes, 4} where last dimension encoded as
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* (y_min, x_min, y_max, x_max), all values in between 0. and 1.
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* 2 - colours tensor (2D) with shape {number_of_boxes, channels} -- bordering color set (palette)
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*
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* output:
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* 0 - 4D tensor with same shape as images (input 0)
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*/
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#if NOT_EXCLUDED(OP_draw_bounding_boxes)
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DECLARE_OP(draw_bounding_boxes, 3, 1, true);
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#endif
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/**
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* roll - op porting from numpy (https://docs.scipy.org/doc/numpy-1.14.0/reference/generated/numpy.roll.html)
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*
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@ -0,0 +1,78 @@
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/*******************************************************************************
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* Copyright (c) 2015-2018 Skymind, Inc.
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*
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* This program and the accompanying materials are made available under the
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* terms of the Apache License, Version 2.0 which is available at
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* https://www.apache.org/licenses/LICENSE-2.0.
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
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* WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
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* License for the specific language governing permissions and limitations
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* under the License.
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*
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* SPDX-License-Identifier: Apache-2.0
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******************************************************************************/
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//
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// @author sgazeos@gmail.com
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//
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#include <op_boilerplate.h>
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#include <NDArray.h>
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namespace nd4j {
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namespace ops {
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namespace helpers {
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void drawBoundingBoxesFunctor(nd4j::LaunchContext * context, NDArray* images, NDArray* boxes, NDArray* colors, NDArray* output) {
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// images - batch of 3D images with BW (last dim = 1), RGB (last dim = 3) or RGBA (last dim = 4) channel set
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// boxes - batch of 2D bounds with last dim (y_start, x_start, y_end, x_end) to compute i and j as
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// floor((height - 1 ) * y_start) => rowStart, floor((height - 1) * y_end) => rowEnd
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// floor((width - 1 ) * x_start) => colStart, floor((width - 1) * x_end) => colEnd
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// height = images->sizeAt(1), width = images->sizeAt(2)
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// colors - colors for each box given
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// set up color for each box as frame
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auto batchSize = images->sizeAt(0);
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auto height = images->sizeAt(1);
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auto width = images->sizeAt(2);
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auto channels = images->sizeAt(3);
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//auto imageList = images->allTensorsAlongDimension({1, 2, 3}); // split images by batch
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// auto boxList = boxes->allTensorsAlongDimension({1, 2}); // split boxes by batch
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auto colorSet = colors->allTensorsAlongDimension({1});
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output->assign(images); // fill up all output with input images, then fill up boxes
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PRAGMA_OMP_PARALLEL_FOR
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for (auto b = 0; b < batchSize; ++b) { // loop by batch
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// auto image = imageList->at(b);
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for (auto c = 0; c < colorSet->size(); ++c) {
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// box with shape
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auto internalBox = (*boxes)(b, {0})(c, {0});//internalBoxes->at(c);
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auto color = colorSet->at(c);
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auto rowStart = nd4j::math::nd4j_max(Nd4jLong (0), Nd4jLong ((height - 1) * internalBox.e<float>(0)));
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auto rowEnd = nd4j::math::nd4j_min(Nd4jLong (height - 1), Nd4jLong ((height - 1) * internalBox.e<float>(2)));
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auto colStart = nd4j::math::nd4j_max(Nd4jLong (0), Nd4jLong ((width - 1) * internalBox.e<float>(1)));
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auto colEnd = nd4j::math::nd4j_min(Nd4jLong(width - 1), Nd4jLong ((width - 1) * internalBox.e<float>(3)));
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for (auto y = rowStart; y <= rowEnd; y++) {
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for (auto e = 0; e < color->lengthOf(); ++e) {
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output->p(b, y, colStart, e, color->e(e));
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output->p(b, y, colEnd, e, color->e(e));
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}
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}
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for (auto x = colStart + 1; x < colEnd; x++) {
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for (auto e = 0; e < color->lengthOf(); ++e) {
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output->p(b, rowStart, x, e, color->e(e));
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output->p(b, rowEnd, x, e, color->e(e));
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}
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}
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}
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// delete internalBoxes;
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}
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delete colorSet;
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// delete imageList;
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// delete boxList;
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}
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}
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}
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}
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@ -0,0 +1,100 @@
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/*******************************************************************************
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* Copyright (c) 2015-2018 Skymind, Inc.
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*
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* This program and the accompanying materials are made available under the
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* terms of the Apache License, Version 2.0 which is available at
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* https://www.apache.org/licenses/LICENSE-2.0.
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
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* WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
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* License for the specific language governing permissions and limitations
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* under the License.
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*
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* SPDX-License-Identifier: Apache-2.0
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******************************************************************************/
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//
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// @author sgazeos@gmail.com
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//
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#include <op_boilerplate.h>
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#include <NDArray.h>
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namespace nd4j {
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namespace ops {
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namespace helpers {
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template <typename T>
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static __global__ void drawBoundingBoxesKernel(T const* images, Nd4jLong* imagesShape, T const* boxes,
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Nd4jLong* boxesShape, T const* colors, Nd4jLong* colorsShape, T* output, Nd4jLong* outputShape,
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Nd4jLong batchSize, Nd4jLong width, Nd4jLong height, Nd4jLong channels, Nd4jLong colorSetSize) {
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for (auto b = blockIdx.x; b < (int)batchSize; b += gridDim.x) { // loop by batch
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for (auto c = 0; c < colorSetSize; c++) {
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// box with shape
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auto internalBox = &boxes[b * colorSetSize * 4 + c * 4];//(*boxes)(b, {0})(c, {0});//internalBoxes->at(c);
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auto color = &colors[channels * c];//colorSet->at(c);
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auto rowStart = nd4j::math::nd4j_max(Nd4jLong (0), Nd4jLong ((height - 1) * internalBox[0]));
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auto rowEnd = nd4j::math::nd4j_min(Nd4jLong (height - 1), Nd4jLong ((height - 1) * internalBox[2]));
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auto colStart = nd4j::math::nd4j_max(Nd4jLong (0), Nd4jLong ((width - 1) * internalBox[1]));
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auto colEnd = nd4j::math::nd4j_min(Nd4jLong(width - 1), Nd4jLong ((width - 1) * internalBox[3]));
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for (auto y = rowStart + threadIdx.x; y <= rowEnd; y += blockDim.x) {
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for (auto e = 0; e < channels; ++e) {
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Nd4jLong yMinPos[] = {b, y, colStart, e};
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Nd4jLong yMaxPos[] = {b, y, colEnd, e};
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auto zIndexYmin = shape::getOffset(outputShape, yMinPos);
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auto zIndexYmax = shape::getOffset(outputShape, yMaxPos);
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output[zIndexYmin] = color[e];
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output[zIndexYmax] = color[e];
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}
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}
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for (auto x = colStart + 1 + threadIdx.x; x < colEnd; x += blockDim.x) {
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for (auto e = 0; e < channels; ++e) {
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Nd4jLong xMinPos[] = {b, rowStart, x, e};
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Nd4jLong xMaxPos[] = {b, rowEnd, x, e};
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auto zIndexXmin = shape::getOffset(outputShape, xMinPos);
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auto zIndexXmax = shape::getOffset(outputShape, xMaxPos);
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output[zIndexXmin] = color[e];
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output[zIndexXmax] = color[e];
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}
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}
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}
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}
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}
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template <typename T>
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void drawBoundingBoxesH(nd4j::LaunchContext* context, NDArray const* images, NDArray const* boxes, NDArray const* colors, NDArray* output) {
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auto batchSize = images->sizeAt(0);
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auto height = images->sizeAt(1);
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auto width = images->sizeAt(2);
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auto channels = images->sizeAt(3);
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auto stream = context->getCudaStream();
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auto colorSetSize = colors->sizeAt(0);
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auto imagesBuf = images->getDataBuffer()->specialAsT<T>();
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auto boxesBuf = boxes->getDataBuffer()->specialAsT<T>();
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auto colorsBuf = colors->getDataBuffer()->specialAsT<T>();
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auto outputBuf = output->dataBuffer()->specialAsT<T>();
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drawBoundingBoxesKernel<<<batchSize > 128? 128: batchSize, 256, 1024, *stream>>>(imagesBuf, images->getSpecialShapeInfo(),
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boxesBuf, boxes->getSpecialShapeInfo(), colorsBuf, colors->getSpecialShapeInfo(),
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outputBuf, output->specialShapeInfo(), batchSize, width, height, channels, colorSetSize);
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}
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void drawBoundingBoxesFunctor(nd4j::LaunchContext * context, NDArray* images, NDArray* boxes, NDArray* colors, NDArray* output) {
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// images - batch of 3D images with BW (last dim = 1), RGB (last dim = 3) or RGBA (last dim = 4) channel set
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// boxes - batch of 2D bounds with last dim (y_start, x_start, y_end, x_end) to compute i and j as
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// floor((height - 1 ) * y_start) => rowStart, floor((height - 1) * y_end) => rowEnd
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// floor((width - 1 ) * x_start) => colStart, floor((width - 1) * x_end) => colEnd
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// height = images->sizeAt(1), width = images->sizeAt(2)
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// colors - colors for each box given
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// set up color for each box as frame
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NDArray::prepareSpecialUse({output}, {images, boxes, colors});
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output->assign(images);
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BUILD_SINGLE_SELECTOR(output->dataType(), drawBoundingBoxesH, (context, images, boxes, colors, output), FLOAT_TYPES);
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NDArray::registerSpecialUse({output}, {images, boxes, colors});
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}
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BUILD_SINGLE_TEMPLATE(template void drawBoundingBoxesH, (nd4j::LaunchContext* context, NDArray const* images, NDArray const* boxes, NDArray const* colors, NDArray* output), FLOAT_TYPES);
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}
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}
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}
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@ -0,0 +1,34 @@
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/*******************************************************************************
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* Copyright (c) 2015-2018 Skymind, Inc.
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*
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* This program and the accompanying materials are made available under the
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* terms of the Apache License, Version 2.0 which is available at
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* https://www.apache.org/licenses/LICENSE-2.0.
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
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* WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
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* License for the specific language governing permissions and limitations
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* under the License.
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*
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* SPDX-License-Identifier: Apache-2.0
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******************************************************************************/
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//
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// @author sgazeos@gmail.com
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//
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#ifndef __IMAGE_DRAW_BOUNDING_BOXES_H_HELPERS__
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#define __IMAGE_DRAW_BOUNDING_BOXES_H_HELPERS__
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#include <op_boilerplate.h>
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#include <NDArray.h>
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namespace nd4j {
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namespace ops {
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namespace helpers {
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void drawBoundingBoxesFunctor(nd4j::LaunchContext * context, NDArray* images, NDArray* boxes, NDArray* colors, NDArray* output);
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}
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}
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}
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#endif
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@ -2043,6 +2043,76 @@ TEST_F(DeclarableOpsTests10, Image_CropAndResize_5) {
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delete results;
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}
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////////////////////////////////////////////////////////////////////
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TEST_F(DeclarableOpsTests10, Image_DrawBoundingBoxes_1) {
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NDArray images = NDArrayFactory::create<float>('c', {2,4,5,3});
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NDArray boxes = NDArrayFactory::create<float>('c', {2, 2, 4}, {
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0. , 0. , 1. , 1. , 0.1, 0.2, 0.9, 0.8,
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0.3, 0.3, 0.7, 0.7, 0.4, 0.4, 0.6, 0.6
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});
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NDArray colors = NDArrayFactory::create<float>('c', {2, 3}, {201., 202., 203., 127., 128., 129.});
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//NDArray<float> ('c', {6}, {0.9f, .75f, .6f, .95f, .5f, .3f});
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NDArray expected = NDArrayFactory::create<float>('c', {2,4,5,3}, {
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127., 128., 129., 127., 128., 129., 127., 128., 129., 127., 128., 129., 201., 202., 203.,
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127., 128., 129., 19., 20., 21., 22., 23., 24., 127., 128., 129., 201., 202., 203.,
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127., 128., 129., 127., 128., 129., 127., 128., 129., 127., 128., 129., 201., 202., 203.,
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201., 202., 203., 201. ,202. ,203., 201., 202., 203., 201., 202., 203., 201., 202., 203.,
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61., 62., 63., 201., 202., 203., 201., 202., 203., 70., 71., 72., 73., 74., 75.,
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76., 77., 78., 127., 128., 129., 127., 128., 129., 85., 86., 87., 88., 89., 90.,
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91., 92., 93., 201., 202., 203., 201., 202., 203., 100., 101., 102., 103., 104., 105.,
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106., 107., 108., 109., 110., 111., 112., 113., 114., 115., 116., 117., 118., 119., 120.
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});
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images.linspace(1.);
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nd4j::ops::draw_bounding_boxes op;
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auto results = op.execute({&images, &boxes, &colors}, {}, {});
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ASSERT_EQ(ND4J_STATUS_OK, results->status());
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auto result = results->at(0);
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// result->printBuffer("Bounded boxes");
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// expected.printBuffer("Bounded expec");
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ASSERT_TRUE(expected.isSameShapeStrict(result));
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ASSERT_TRUE(expected.equalsTo(result));
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delete results;
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}
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////////////////////////////////////////////////////////////////////
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TEST_F(DeclarableOpsTests10, Image_DrawBoundingBoxes_2) {
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NDArray images = NDArrayFactory::create<float>('c', {1,9,9,1});
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NDArray boxes = NDArrayFactory::create<float>('c', {1, 1, 4}, {0.2, 0.2, 0.7, 0.7});
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NDArray colors = NDArrayFactory::create<float>('c', {1, 1}, {0.95});
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//NDArray<float> ('c', {6}, {0.9f, .75f, .6f, .95f, .5f, .3f});
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NDArray expected = NDArrayFactory::create<float>('c', {1,9,9,1}, {
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1.1 , 2.1, 3.1 , 4.1 , 5.1 , 6.1 , 7.1 , 8.1 , 9.1 ,
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10.1 , 0.95, 0.95, 0.95, 0.95, 0.95, 16.1 , 17.1 , 18.1 ,
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19.1 , 0.95, 21.1, 22.1, 23.1, 0.95, 25.1 , 26.1 , 27.1 ,
|
||||
28.1 , 0.95, 30.1, 31.1, 32.1, 0.95, 34.1 , 35.1 , 36.1 ,
|
||||
37.1 , 0.95, 39.1, 40.1, 41.1, 0.95, 43.1 , 44.1 , 45.1 ,
|
||||
46.1 , 0.95, 0.95, 0.95, 0.95, 0.95, 52.1 , 53.1 , 54.1 ,
|
||||
55.1 , 56.1, 57.1 , 58.1 , 59.1 , 60.1 , 61.1 , 62.1 , 63.1 ,
|
||||
64.1 , 65.1, 66.1 , 67.1 , 68.1 , 69.1 , 70.1 , 71.1 , 72.1 ,
|
||||
73.1 , 74.1, 75.1 , 76.1 , 77.1 , 78.1 , 79.1 , 80.1 , 81.1 });
|
||||
images.linspace(1.1);
|
||||
nd4j::ops::draw_bounding_boxes op;
|
||||
auto results = op.execute({&images, &boxes, &colors}, {}, {});
|
||||
|
||||
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
||||
|
||||
auto result = results->at(0);
|
||||
// result->syncToHost();
|
||||
// result->printBuffer("Bounded boxes 2");
|
||||
// expected.printBuffer("Bounded expec 2");
|
||||
ASSERT_TRUE(expected.isSameShapeStrict(result));
|
||||
ASSERT_TRUE(expected.equalsTo(result));
|
||||
|
||||
delete results;
|
||||
}
|
||||
|
||||
////////////////////////////////////////////////////////////////////
|
||||
TEST_F(DeclarableOpsTests10, FakeQuantWithMinMaxVars_Test_1) {
|
||||
|
||||
|
|
|
|||
Loading…
Reference in New Issue