// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved. // // Licensed 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. #include "fastdeploy/vision/keypointdet/pptinypose/pptinypose_utils.h" #define PI 3.1415926535 #define HALF_CIRCLE_DEGREE 180 namespace fastdeploy { namespace vision { namespace keypointdetection { cv::Point2f Get3dPoint(const cv::Point2f& a, const cv::Point2f& b) { cv::Point2f direct{a.x - b.x, a.y - b.y}; return cv::Point2f(a.x - direct.y, a.y + direct.x); } std::vector GetDir(const float src_point_x, const float src_point_y, const float rot_rad) { float sn = sin(rot_rad); float cs = cos(rot_rad); std::vector src_result{0.0, 0.0}; src_result[0] = src_point_x * cs - src_point_y * sn; src_result[1] = src_point_x * sn + src_point_y * cs; return src_result; } void AffineTransform(const float pt_x, const float pt_y, const cv::Mat& trans, std::vector* preds, const int p) { double new1[3] = {pt_x, pt_y, 1.0}; cv::Mat new_pt(3, 1, trans.type(), new1); cv::Mat w = trans * new_pt; (*preds)[p * 3 + 1] = static_cast(w.at(0, 0)); (*preds)[p * 3 + 2] = static_cast(w.at(1, 0)); } void GetAffineTransform(const std::vector& center, const std::vector& scale, const float rot, const std::vector& output_size, cv::Mat* trans, const int inv) { float src_w = scale[0]; float dst_w = static_cast(output_size[0]); float dst_h = static_cast(output_size[1]); float rot_rad = rot * PI / HALF_CIRCLE_DEGREE; std::vector src_dir = GetDir(-0.5 * src_w, 0, rot_rad); std::vector dst_dir{-0.5f * dst_w, 0.0}; cv::Point2f srcPoint2f[3], dstPoint2f[3]; srcPoint2f[0] = cv::Point2f(center[0], center[1]); srcPoint2f[1] = cv::Point2f(center[0] + src_dir[0], center[1] + src_dir[1]); srcPoint2f[2] = Get3dPoint(srcPoint2f[0], srcPoint2f[1]); dstPoint2f[0] = cv::Point2f(dst_w * 0.5, dst_h * 0.5); dstPoint2f[1] = cv::Point2f(dst_w * 0.5 + dst_dir[0], dst_h * 0.5 + dst_dir[1]); dstPoint2f[2] = Get3dPoint(dstPoint2f[0], dstPoint2f[1]); if (inv == 0) { (*trans) = cv::getAffineTransform(srcPoint2f, dstPoint2f); } else { (*trans) = cv::getAffineTransform(dstPoint2f, srcPoint2f); } } void TransformPreds(std::vector& coords, const std::vector& center, const std::vector& scale, const std::vector& output_size, const std::vector& dim, std::vector* target_coords) { cv::Mat trans(2, 3, CV_64FC1); GetAffineTransform(center, scale, 0, output_size, &trans, 1); for (int p = 0; p < dim[1]; ++p) { AffineTransform(coords[p * 2], coords[p * 2 + 1], trans, target_coords, p); } } void GetFinalPredictions(const std::vector& heatmap, const std::vector& dim, const std::vector& idxout, const std::vector& center, const std::vector scale, std::vector* preds, const bool DARK) { std::vector coords(dim[1] * 2); int heatmap_height = dim[2]; int heatmap_width = dim[3]; for (int j = 0; j < dim[1]; ++j) { int index = j * dim[2] * dim[3]; int idx = idxout[j]; (*preds)[j * 3] = heatmap[index + idx]; coords[j * 2] = idx % heatmap_width; coords[j * 2 + 1] = idx / heatmap_width; int px = int(coords[j * 2] + 0.5); int py = int(coords[j * 2 + 1] + 0.5); if (DARK && px > 1 && px < heatmap_width - 2) { utils::DarkParse(heatmap, dim, &coords, px, py, index, j); } else { if (px > 0 && px < heatmap_width - 1) { float diff_x = heatmap[index + py * dim[3] + px + 1] - heatmap[index + py * dim[3] + px - 1]; coords[j * 2] += diff_x > 0 ? 1 : -1 * 0.25; } if (py > 0 && py < heatmap_height - 1) { float diff_y = heatmap[index + (py + 1) * dim[3] + px] - heatmap[index + (py - 1) * dim[3] + px]; coords[j * 2 + 1] += diff_y > 0 ? 1 : -1 * 0.25; } } } std::vector img_size{heatmap_width, heatmap_height}; TransformPreds(coords, center, scale, img_size, dim, preds); } } // namespace detection } // namespace vision } // namespace fastdeploy