inference-engine/src/inference_engine/shape_infer/built-in/ie_region_yolo_shape_infer.hpp

   1 // Copyright (C) 2018-2019 Intel Corporation
   2 // SPDX-License-Identifier: Apache-2.0
   3 //
   4
   5 #pragma once
   6
   7 #include <description_buffer.hpp>
   8 #include "ie_built_in_impl.hpp"
   9 #include <ie_layers.h>
  10 #include <map>
  11 #include <memory>
  12 #include <string>
  13 #include <vector>
  14
  15 namespace InferenceEngine {
  16 namespace ShapeInfer {
  17
  18 /**
  19  *@brief Implementation of Shape inference for RegionYolo layer
  20  */
  21 class RegionYoloShapeProp : public BuiltInShapeInferImpl {
  22 public:
  23     explicit RegionYoloShapeProp(const std::string& type) : BuiltInShapeInferImpl(type) {}
  24
  25     void inferShapesImpl(const std::vector<Blob::CPtr>& inBlobs,
  26                          const std::map<std::string, std::string>& params,
  27                          const std::map<std::string, Blob::Ptr>& blobs,
  28                          std::vector<SizeVector>& outShapes) override {
  29         LayerParams lp{};
  30         CNNLayer layer(lp);
  31         layer.params = params;
  32         int classes;
  33         int coords;
  34         int num;
  35         bool do_softmax;
  36         std::vector<int> mask;
  37         classes = layer.GetParamAsInt("classes", 1);
  38         coords = layer.GetParamAsInt("coords", 1);
  39         num = layer.GetParamAsInt("num", 1);
  40         do_softmax = static_cast<bool>(layer.GetParamAsInt("do_softmax", 1));
  41         mask = layer.GetParamAsInts("mask", {});
  42         unsigned int axis = layer.GetParamAsUInt("axis", 1);
  43         int end_axis = layer.GetParamAsInt("end_axis", 1);
  44         if (end_axis < 0) end_axis += inShapes[0].size();
  45
  46         SizeVector outShape;
  47         if (do_softmax) {
  48             size_t flat_dim = 1;
  49             for (size_t i = 0; i < axis; i++) {
  50                 outShape.push_back(inShapes[0][i]);
  51             }
  52             for (size_t i = axis; i < end_axis + 1; i++) {
  53                 flat_dim *= inShapes[0][i];
  54             }
  55             outShape.push_back(flat_dim);
  56             for (size_t i = end_axis + 1; i < inShapes[0].size(); i++) {
  57                 outShape.push_back(inShapes[0][i]);
  58             }
  59         } else {
  60             outShape = {inShapes[0][0], (classes + coords + 1) * mask.size(), inShapes[0][2], inShapes[0][3]};
  61         }
  62         outShapes.push_back({outShape});
  63     }
  64 };
  65
  66 }  // namespace ShapeInfer
  67 }  // namespace InferenceEngine