sandeep-krishnamurthy commented on a change in pull request #14014: [WIP] Export resize and support batch size URL: https://github.com/apache/incubator-mxnet/pull/14014#discussion_r251948372
########## File path: src/operator/image/resize-inl.h ########## @@ -0,0 +1,217 @@ +/* +* Licensed to the Apache Software Foundation (ASF) under one +* or more contributor license agreements. See the NOTICE file +* distributed with this work for additional information +* regarding copyright ownership. The ASF licenses this file +* to you 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. +*/ +/*! +* \file resize-inl.h +* \brief image resize operator using opencv and only support bilinear resize +* \author Jake Lee +*/ +#ifndef MXNET_OPERATOR_IMAGE_RESIZE_INL_H_ +#define MXNET_OPERATOR_IMAGE_RESIZE_INL_H_ + +#include <mxnet/base.h> +#include <vector> + +#include "../mxnet_op.h" +#include "../operator_common.h" +#include "image_utils.h" + +#if MXNET_USE_OPENCV + #include <opencv2/opencv.hpp> +#endif // MXNET_USE_OPENCV + +namespace mxnet { +namespace op { +namespace image { + +using namespace mshadow; + +#if MXNET_USE_CUDA +template<typename DType, typename T, typename Acctype> +void ResizeImplCUDA(Stream<gpu> *s, + const T input, + const T output); +#endif // MXNET_USE_CUDA + +struct ResizeParam : public dmlc::Parameter<ResizeParam> { + nnvm::Tuple<int> size; + bool keep_ratio; + int interp; + DMLC_DECLARE_PARAMETER(ResizeParam) { + DMLC_DECLARE_FIELD(size) + .set_default(nnvm::Tuple<int>()) + .describe("Size of new image. Could be (width, height) or (size)"); + DMLC_DECLARE_FIELD(keep_ratio) + .describe("Whether to resize the short edge or both edges to `size`, " + "if size is give as an integer.") + .set_default(false); + DMLC_DECLARE_FIELD(interp) + .set_default(1) + .describe("Interpolation method for resizing. By default uses bilinear interpolation" + "Options are INTER_NEAREST - a nearest-neighbor interpolation" + "INTER_LINEAR - a bilinear interpolation" + "INTER_AREA - resampling using pixel area relation" + "INTER_CUBIC - a bicubic interpolation over 4x4 pixel neighborhood" + "INTER_LANCZOS4 - a Lanczos interpolation over 8x8 pixel neighborhood" + "Note that the GPU version only support bilinear interpolation"); + } +}; +// handle the keep ratio param +inline SizeParam GetHeightAndWidth(int data_h, + int data_w, + const ResizeParam& param) { + CHECK((param.size.ndim() == 1) || (param.size.ndim() == 2)) + << "Input size dimension must be 1 or 2, but got " + << param.size.ndim(); + int resized_h; + int resized_w; + if (param.size.ndim() == 1) { + CHECK_GT(param.size[0], 0) + << "Input size should be greater than 0, but got " + << param.size[0]; + if (!param.keep_ratio) { + resized_h = param.size[0]; + resized_w = param.size[0]; + } else { + if (data_h > data_w) { + resized_w = param.size[0]; + resized_h = static_cast<int>(data_h * resized_w / data_w); + } else { + resized_h = param.size[0]; + resized_w = static_cast<int>(data_w * resized_h / data_h); + } + } + } else { + CHECK_GT(param.size[0], 0) + << "Input width should be greater than 0, but got " + << param.size[0]; + CHECK_GT(param.size[1], 0) + << "Input height should be greater than 0, but got " + << param.size[1]; + resized_h = param.size[1]; + resized_w = param.size[0]; + } + return SizeParam(resized_h, resized_w); +} + +inline bool ResizeShape(const nnvm::NodeAttrs& attrs, + std::vector<TShape> *in_attrs, + std::vector<TShape> *out_attrs) { + // input attrs should only be (h, w, c) or (n, h, w, c) + CHECK((in_attrs->at(0).ndim() == 3U) || (in_attrs->at(0).ndim() == 4U)) + << "Input image dimension should be 3 or 4 but got " + << in_attrs->at(0).ndim(); + const auto& ishape = (*in_attrs)[0]; + const ResizeParam& param = nnvm::get<ResizeParam>(attrs.parsed); + SizeParam size; + if (ishape.ndim() == 3) { + size = GetHeightAndWidth(ishape[H], ishape[W], param); + SHAPE_ASSIGN_CHECK(*out_attrs, 0, TShape({size.height, size.width, ishape[C]})); + } else { + size = GetHeightAndWidth(ishape[kH], ishape[kW], param); + SHAPE_ASSIGN_CHECK(*out_attrs, 0, + TShape({ishape[N], size.height, size.width, ishape[kC]})); + } + return true; +} + +inline void ResizeImpl(const std::vector<TBlob> &inputs, + const std::vector<TBlob> &outputs, + const int height, + const int width, + const int interp, + const int input_index = 0, + const int output_index = 0) { +#if MXNET_USE_OPENCV + CHECK_NE(inputs[0].type_flag_, mshadow::kFloat16) << "opencv image mat doesn't support fp16"; + CHECK((inputs[0].type_flag_ != mshadow::kInt32) || (inputs[0].type_flag_ != mshadow::kInt64)) + << "opencv resize doesn't support int32, int64"; + // mapping to opencv matrix element type according to channel + const int DTYPE[] = {CV_32F, CV_64F, -1, CV_8U, CV_32S}; + if (inputs[0].ndim() == 3) { + const int cv_type = CV_MAKETYPE(DTYPE[inputs[0].type_flag_], inputs[0].shape_[C]); + cv::Mat buf(inputs[0].shape_[H], inputs[0].shape_[W], cv_type, inputs[0].dptr_); + cv::Mat dst(outputs[0].shape_[H], outputs[0].shape_[W], cv_type, outputs[0].dptr_); + cv::resize(buf, dst, cv::Size(width, height), 0, 0, interp); + CHECK(!dst.empty()); + CHECK_EQ(static_cast<void*>(dst.ptr()), outputs[0].dptr_); + } else { + const int cv_type = CV_MAKETYPE(DTYPE[inputs[0].type_flag_], inputs[0].shape_[kC]); + MSHADOW_TYPE_SWITCH(outputs[0].type_flag_, DType, { + cv::Mat buf(inputs[0].shape_[kH], inputs[0].shape_[kW], cv_type, + inputs[0].dptr<DType>() + input_index); + cv::Mat dst(outputs[0].shape_[kH], outputs[0].shape_[kW], cv_type, + outputs[0].dptr<DType>() + output_index); + cv::resize(buf, dst, cv::Size(width, height), 0, 0, interp); + CHECK(!dst.empty()); + CHECK_EQ(static_cast<void*>(dst.ptr()), outputs[0].dptr<DType>() + output_index); + }); + } +#else + LOG(FATAL) << "Build with USE_OPENCV=1 for image resize operator."; +#endif // MXNET_USE_OPENCV +} + +template <typename xpu> +inline void Resize(const nnvm::NodeAttrs &attrs, + const OpContext &ctx, + const std::vector<TBlob> &inputs, + const std::vector<OpReqType> &req, + const std::vector<TBlob> &outputs) { + CHECK_EQ(outputs.size(), 1U); + const ResizeParam& param = nnvm::get<ResizeParam>(attrs.parsed); + SizeParam size; +#if MXNET_USE_CUDA + if (std::is_same<xpu, gpu>::value) { + CHECK(param.interp == 1) << "GPU version only support bilinear interpolation"; Review comment: Will be useful to also say, interp should be 1 for using Resize on GPU. ---------------------------------------------------------------- This is an automated message from the Apache Git Service. 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