From 7234ed8c3d07c76963eb3bce9530994421ad7e67 Mon Sep 17 00:00:00 2001
From: Isabella Gottardi <isabella.gottardi@arm.com>
Date: Tue, 27 Nov 2018 08:51:10 +0000
Subject: COMPMID-1808: Add Detection Output Layer to the GraphAPI
 COMPMID-1710: Integrate Detection ouput in MobilenetSSD graph example

Change-Id: I384d1eb492ef14ece58f2023ad7bbc16f834450b
Reviewed-on: https://review.mlplatform.org/356
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Pablo Marquez <pablo.tello@arm.com>
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>
---
 utils/GraphUtils.h | 63 ++++++++++++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 63 insertions(+)

(limited to 'utils/GraphUtils.h')

diff --git a/utils/GraphUtils.h b/utils/GraphUtils.h
index d7f24afdd8..131378e5bd 100644
--- a/utils/GraphUtils.h
+++ b/utils/GraphUtils.h
@@ -283,6 +283,36 @@ private:
     size_t           _positive_samples_top5;
 };
 
+/** Detection output accessor class */
+class DetectionOutputAccessor final : public graph::ITensorAccessor
+{
+public:
+    /** Constructor
+     *
+     * @param[in]  labels_path        Path to labels text file.
+     * @param[in]  imgs_tensor_shapes Network input images tensor shapes.
+     * @param[out] output_stream      (Optional) Output stream
+     */
+    DetectionOutputAccessor(const std::string &labels_path, std::vector<TensorShape> &imgs_tensor_shapes, std::ostream &output_stream = std::cout);
+    /** Allow instances of this class to be move constructed */
+    DetectionOutputAccessor(DetectionOutputAccessor &&) = default;
+    /** Prevent instances of this class from being copied (As this class contains pointers) */
+    DetectionOutputAccessor(const DetectionOutputAccessor &) = delete;
+    /** Prevent instances of this class from being copied (As this class contains pointers) */
+    DetectionOutputAccessor &operator=(const DetectionOutputAccessor &) = delete;
+
+    // Inherited methods overriden:
+    bool access_tensor(ITensor &tensor) override;
+
+private:
+    template <typename T>
+    void access_predictions_tensor(ITensor &tensor);
+
+    std::vector<std::string> _labels;
+    std::vector<TensorShape> _tensor_shapes;
+    std::ostream            &_output_stream;
+};
+
 /** Result accessor class */
 class TopNPredictionsAccessor final : public graph::ITensorAccessor
 {
@@ -472,6 +502,39 @@ inline std::unique_ptr<graph::ITensorAccessor> get_output_accessor(const arm_com
         return arm_compute::support::cpp14::make_unique<TopNPredictionsAccessor>(graph_parameters.labels, top_n, output_stream);
     }
 }
+/** Generates appropriate output accessor according to the specified graph parameters
+ *
+ * @note If the output accessor is requested to validate the graph then ValidationOutputAccessor is generated
+ *       else if output_accessor_file is empty will generate a DummyAccessor else will generate a TopNPredictionsAccessor
+ *
+ * @param[in]  graph_parameters Graph parameters
+ * @param[in]  tensor_shapes    Network input images tensor shapes.
+ * @param[in]  is_validation    (Optional) Validation flag (default = false)
+ * @param[out] output_stream    (Optional) Output stream (default = std::cout)
+ *
+ * @return An appropriate tensor accessor
+ */
+inline std::unique_ptr<graph::ITensorAccessor> get_detection_output_accessor(const arm_compute::utils::CommonGraphParams &graph_parameters,
+                                                                             std::vector<TensorShape>                     tensor_shapes,
+                                                                             bool                                         is_validation = false,
+                                                                             std::ostream                                &output_stream = std::cout)
+{
+    if(!graph_parameters.validation_file.empty())
+    {
+        return arm_compute::support::cpp14::make_unique<ValidationOutputAccessor>(graph_parameters.validation_file,
+                                                                                  output_stream,
+                                                                                  graph_parameters.validation_range_start,
+                                                                                  graph_parameters.validation_range_end);
+    }
+    else if(graph_parameters.labels.empty())
+    {
+        return arm_compute::support::cpp14::make_unique<DummyAccessor>(0);
+    }
+    else
+    {
+        return arm_compute::support::cpp14::make_unique<DetectionOutputAccessor>(graph_parameters.labels, tensor_shapes, output_stream);
+    }
+}
 /** Generates appropriate npy output accessor according to the specified npy_path
  *
  * @note If npy_path is empty will generate a DummyAccessor else will generate a NpyAccessor
-- 
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