mirror of
https://github.com/PaddlePaddle/FastDeploy.git
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73 lines
2.7 KiB
C++
73 lines
2.7 KiB
C++
// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved. //NOLINT
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//
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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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//
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// http://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,
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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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#include "fastdeploy/vision/detection/contrib/rknpu2/utils.h"
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namespace fastdeploy {
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namespace vision {
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namespace detection {
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float Clamp(float val, int min, int max) {
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return val > min ? (val < max ? val : max) : min;
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}
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static float CalculateOverlap(float xmin0, float ymin0, float xmax0,
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float ymax0, float xmin1, float ymin1,
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float xmax1, float ymax1) {
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float w = fmax(0.f, fmin(xmax0, xmax1) - fmax(xmin0, xmin1) + 1.0);
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float h = fmax(0.f, fmin(ymax0, ymax1) - fmax(ymin0, ymin1) + 1.0);
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float i = w * h;
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float u = (xmax0 - xmin0 + 1.0) * (ymax0 - ymin0 + 1.0) +
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(xmax1 - xmin1 + 1.0) * (ymax1 - ymin1 + 1.0) - i;
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return u <= 0.f ? 0.f : (i / u);
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}
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int NMS(int valid_count, std::vector<float>& output_locations,
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std::vector<int>& class_id, std::vector<int>& order, float threshold,
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bool class_agnostic) {
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// printf("class_agnostic: %d\n", class_agnostic);
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for (int i = 0; i < valid_count; ++i) {
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if (order[i] == -1) {
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continue;
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}
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int n = order[i];
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for (int j = i + 1; j < valid_count; ++j) {
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int m = order[j];
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if (m == -1) {
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continue;
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}
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if (!class_agnostic && class_id[n] != class_id[m]) {
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continue;
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}
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float xmin0 = output_locations[n * 4 + 0];
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float ymin0 = output_locations[n * 4 + 1];
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float xmax0 = output_locations[n * 4 + 0] + output_locations[n * 4 + 2];
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float ymax0 = output_locations[n * 4 + 1] + output_locations[n * 4 + 3];
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float xmin1 = output_locations[m * 4 + 0];
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float ymin1 = output_locations[m * 4 + 1];
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float xmax1 = output_locations[m * 4 + 0] + output_locations[m * 4 + 2];
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float ymax1 = output_locations[m * 4 + 1] + output_locations[m * 4 + 3];
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float iou = CalculateOverlap(xmin0, ymin0, xmax0, ymax0, xmin1, ymin1,
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xmax1, ymax1);
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if (iou > threshold) {
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order[j] = -1;
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}
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}
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}
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return 0;
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}
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} // namespace detection
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} // namespace vision
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} // namespace fastdeploy
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