Refine and fix some code for faster-rcnn. (#13135)
* Fix bug in generate_proposals_op. * Fix data type for RoIs. * Refine and fix rpn_target_assign_op. * Add the missing file bbox_util.h * Rename BoxEncoder to BoxToDeltafix-develop-build.sh
qingqing01
7 years ago
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GitHub
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/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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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,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License. */
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#pragma once
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#include "paddle/fluid/framework/eigen.h"
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#include "paddle/fluid/framework/tensor.h"
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namespace paddle {
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namespace operators {
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/*
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* transform that computes target bounding-box regression deltas
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* given proposal boxes and ground-truth boxes.
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*/
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template <typename T>
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inline void BoxToDelta(const int box_num, const framework::Tensor& ex_boxes,
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const framework::Tensor& gt_boxes, const T* weights,
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const bool normalized, framework::Tensor* box_delta) {
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auto ex_boxes_et = framework::EigenTensor<T, 2>::From(ex_boxes);
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auto gt_boxes_et = framework::EigenTensor<T, 2>::From(gt_boxes);
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auto trg = framework::EigenTensor<T, 2>::From(*box_delta);
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T ex_w, ex_h, ex_ctr_x, ex_ctr_y, gt_w, gt_h, gt_ctr_x, gt_ctr_y;
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for (int64_t i = 0; i < box_num; ++i) {
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ex_w = ex_boxes_et(i, 2) - ex_boxes_et(i, 0) + (normalized == false);
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ex_h = ex_boxes_et(i, 3) - ex_boxes_et(i, 1) + (normalized == false);
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ex_ctr_x = ex_boxes_et(i, 0) + 0.5 * ex_w;
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ex_ctr_y = ex_boxes_et(i, 1) + 0.5 * ex_h;
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gt_w = gt_boxes_et(i, 2) - gt_boxes_et(i, 0) + (normalized == false);
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gt_h = gt_boxes_et(i, 3) - gt_boxes_et(i, 1) + (normalized == false);
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gt_ctr_x = gt_boxes_et(i, 0) + 0.5 * gt_w;
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gt_ctr_y = gt_boxes_et(i, 1) + 0.5 * gt_h;
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trg(i, 0) = (gt_ctr_x - ex_ctr_x) / ex_w;
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trg(i, 1) = (gt_ctr_y - ex_ctr_y) / ex_h;
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trg(i, 2) = std::log(gt_w / ex_w);
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trg(i, 3) = std::log(gt_h / ex_h);
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if (weights) {
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trg(i, 0) = trg(i, 0) / weights[0];
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trg(i, 1) = trg(i, 1) / weights[1];
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trg(i, 2) = trg(i, 2) / weights[2];
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trg(i, 3) = trg(i, 3) / weights[3];
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}
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}
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}
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template <typename T>
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void Gather(const T* in, const int in_stride, const int* index, const int num,
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T* out) {
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const int stride_bytes = in_stride * sizeof(T);
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for (int i = 0; i < num; ++i) {
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int id = index[i];
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memcpy(out + i * in_stride, in + id * in_stride, stride_bytes);
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}
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}
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} // namespace operators
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} // namespace paddle
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