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Align fastdeploy prediction precision with yolov5 (#11)
* Align fastdeploy prediction precision with yolov5 * Change name of Sort function to SortDetectionResult * Add stride max_wh is_mini_pad property in __init__.py and unify format of getting image width and length * Change mergesort.cc to sort_det_res.cc
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// 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. | ||
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#include "fastdeploy/vision/utils/utils.h" | ||
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namespace fastdeploy { | ||
namespace vision { | ||
namespace utils { | ||
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void Merge(DetectionResult* result, size_t low, size_t mid, size_t high) { | ||
std::vector<std::array<float, 4>>& boxes = result->boxes; | ||
std::vector<float>& scores = result->scores; | ||
std::vector<int32_t>& label_ids = result->label_ids; | ||
std::vector<std::array<float, 4>> temp_boxes(boxes); | ||
std::vector<float> temp_scores(scores); | ||
std::vector<int32_t> temp_label_ids(label_ids); | ||
size_t i = low; | ||
size_t j = mid + 1; | ||
size_t k = i; | ||
for (; i <= mid && j <= high; k++) { | ||
if (temp_scores[i] >= temp_scores[j]) { | ||
scores[k] = temp_scores[i]; | ||
label_ids[k] = temp_label_ids[i]; | ||
boxes[k] = temp_boxes[i]; | ||
i++; | ||
} else { | ||
scores[k] = temp_scores[j]; | ||
label_ids[k] = temp_label_ids[j]; | ||
boxes[k] = temp_boxes[j]; | ||
j++; | ||
} | ||
} | ||
while (i <= mid) { | ||
scores[k] = temp_scores[i]; | ||
label_ids[k] = temp_label_ids[i]; | ||
boxes[k] = temp_boxes[i]; | ||
k++; | ||
i++; | ||
} | ||
while (j <= high) { | ||
scores[k] = temp_scores[j]; | ||
label_ids[k] = temp_label_ids[j]; | ||
boxes[k] = temp_boxes[j]; | ||
k++; | ||
j++; | ||
} | ||
} | ||
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void MergeSort(DetectionResult* result, size_t low, size_t high) { | ||
if (low < high) { | ||
size_t mid = (high - low) / 2 + low; | ||
MergeSort(result, low, mid); | ||
MergeSort(result, mid + 1, high); | ||
Merge(result, low, mid, high); | ||
} | ||
} | ||
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void SortDetectionResult(DetectionResult* result) { | ||
size_t low = 0; | ||
size_t high = result->scores.size() - 1; | ||
MergeSort(result, low, high); | ||
} | ||
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} // namespace utils | ||
} // namespace vision | ||
} // namespace fastdeploy |
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