COMPMID-1849: Add DetectorPostProcess operator

Part1 - Rework of CPPNonMaximumSuppression

Change-Id: I2b34fbd12188db49b0ac050a12312494eeefd819
Signed-off-by: Isabella Gottardi <isabella.gottardi@arm.com>
Reviewed-on: https://review.mlplatform.org/c/1585
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Michele Di Giorgio <michele.digiorgio@arm.com>

1 files changed, 0 insertions, 50 deletions

diff --git a/arm_compute/runtime/CPP/functions/CPPDetectionOutputLayer.h b/arm_compute/runtime/CPP/functions/CPPDetectionOutputLayer.h
index 8c610f3ec2..71be8a0ad8 100644
--- a/arm_compute/runtime/CPP/functions/CPPDetectionOutputLayer.h
+++ b/arm_compute/runtime/CPP/functions/CPPDetectionOutputLayer.h
@@ -39,56 +39,6 @@ using NormalizedBBox = std::array<float, 4>;
 // LabelBBox used for map label and bounding box
 using LabelBBox = std::map<int, std::vector<NormalizedBBox>>;
 
-/** CPP Function to perform non maximum suppression on the bounding boxes and scores
- *
- */
-class CPPNonMaximumSuppression : public IFunction
-{
-public:
-    /** Default constructor */
-    CPPNonMaximumSuppression();
-    /** Configure the function to perform non maximal suppression
-     *
-     * @param[in]  bboxes          The input bounding boxes. Data types supported: F32.
-     * @param[in]  scores          The corresponding input confidence. Same as @p scores.
-     * @param[out] indices         The kept indices of bboxes after nms. Data types supported: S32.
-     * @param[in]  max_output_size An integer tensor representing the maximum number of boxes to be selected by non max suppression.
-     * @param[in]  score_threshold The threshold used to filter detection results.
-     * @param[in]  nms_threshold   The threshold used in non maximum suppression.
-     *
-     */
-    void configure(const ITensor *bboxes, const ITensor *scores, ITensor *indices, unsigned int max_output_size, const float score_threshold, const float nms_threshold);
-
-    /** Static function to check if given arguments will lead to a valid configuration of @ref CPPNonMaximumSuppression
-     *
-     * @param[in]  bboxes          The input bounding boxes. Data types supported: F32.
-     * @param[in]  scores          The corresponding input confidence. Same as @p scores.
-     * @param[out] indices         The kept indices of bboxes after nms. Data types supported: S32.
-     * @param[in]  max_output_size An integer tensor representing the maximum number of boxes to be selected by non max suppression.
-     * @param[in]  score_threshold The threshold used to filter detection results.
-     * @param[in]  nms_threshold   The threshold used in non maximum suppression.
-     *
-     */
-    static Status validate(const ITensorInfo *bboxes, const ITensorInfo *scores, const ITensorInfo *indices, unsigned int max_output_size,
-                           const float score_threshold, const float nms_threshold);
-
-    // Inherited methods overridden:
-    void run() override;
-    /** Prevent instances of this class from being copied (As this class contains pointers) */
-    CPPNonMaximumSuppression(const CPPNonMaximumSuppression &) = delete;
-    /** Prevent instances of this class from being copied (As this class contains pointers) */
-    CPPNonMaximumSuppression &operator=(const CPPNonMaximumSuppression &) = delete;
-
-private:
-    const ITensor *_bboxes;
-    const ITensor *_scores;
-    ITensor       *_indices;
-    unsigned int   _max_output_size;
-
-    float _score_threshold;
-    float _nms_threshold;
-};
-
 /** CPP Function to generate the detection output based on location and confidence
  * predictions by doing non maximum suppression.
  *