| // |
| // Copyright © 2020 Arm Ltd and Contributors. All rights reserved. |
| // SPDX-License-Identifier: MIT |
| // |
| |
| #include "YoloResultDecoder.hpp" |
| |
| #include "NonMaxSuppression.hpp" |
| |
| #include <cassert> |
| #include <stdexcept> |
| |
| namespace od |
| { |
| |
| DetectedObjects YoloResultDecoder::Decode(const common::InferenceResults<float>& networkResults, |
| const common::Size& outputFrameSize, |
| const common::Size& resizedFrameSize, |
| const std::vector<std::string>& labels) |
| { |
| |
| // Yolo v3 network outputs 1 tensor |
| if (networkResults.size() != 1) |
| { |
| throw std::runtime_error("Number of outputs from Yolo model doesn't equal 1"); |
| } |
| auto element_step = m_boxElements + m_confidenceElements + m_numClasses; |
| |
| float longEdgeInput = std::max(resizedFrameSize.m_Width, resizedFrameSize.m_Height); |
| float longEdgeOutput = std::max(outputFrameSize.m_Width, outputFrameSize.m_Height); |
| const float resizeFactor = longEdgeOutput/longEdgeInput; |
| |
| DetectedObjects detectedObjects; |
| DetectedObjects resultsAfterNMS; |
| |
| for (const common::InferenceResult<float>& result : networkResults) |
| { |
| for (unsigned int i = 0; i < m_numBoxes; ++i) |
| { |
| const float* cur_box = &result[i * element_step]; |
| // Objectness score |
| if (cur_box[4] > m_objectThreshold) |
| { |
| for (unsigned int classIndex = 0; classIndex < m_numClasses; ++classIndex) |
| { |
| const float class_prob = cur_box[4] * cur_box[5 + classIndex]; |
| |
| // class confidence |
| |
| if (class_prob > m_ClsThreshold) |
| { |
| DetectedObject detectedObject; |
| |
| detectedObject.SetScore(class_prob); |
| |
| float topLeftX = cur_box[0] * resizeFactor; |
| float topLeftY = cur_box[1] * resizeFactor; |
| float botRightX = cur_box[2] * resizeFactor; |
| float botRightY = cur_box[3] * resizeFactor; |
| |
| assert(botRightX > topLeftX); |
| assert(botRightY > topLeftY); |
| |
| detectedObject.SetBoundingBox({static_cast<int>(topLeftX), |
| static_cast<int>(topLeftY), |
| static_cast<unsigned int>(botRightX-topLeftX), |
| static_cast<unsigned int>(botRightY-topLeftY)}); |
| if(labels.size() > classIndex) |
| { |
| detectedObject.SetLabel(labels.at(classIndex)); |
| } |
| else |
| { |
| detectedObject.SetLabel(std::to_string(classIndex)); |
| } |
| detectedObject.SetId(classIndex); |
| detectedObjects.emplace_back(detectedObject); |
| } |
| } |
| } |
| } |
| |
| std::vector<int> keepIndiciesAfterNMS = od::NonMaxSuppression(detectedObjects, m_NmsThreshold); |
| |
| for (const int ind: keepIndiciesAfterNMS) |
| { |
| resultsAfterNMS.emplace_back(detectedObjects[ind]); |
| } |
| } |
| |
| return resultsAfterNMS; |
| } |
| |
| YoloResultDecoder::YoloResultDecoder(float NMSThreshold, float ClsThreshold, float ObjectThreshold) |
| : m_NmsThreshold(NMSThreshold), m_ClsThreshold(ClsThreshold), m_objectThreshold(ObjectThreshold) {} |
| |
| }// namespace od |
| |
| |
| |