// Copyright (c) 2018, ETH Zurich and UNC Chapel Hill.
// All rights reserved.
//
// Redistribution and use in source and binary forms, with or without
// modification, are permitted provided that the following conditions are met:
//
//     * Redistributions of source code must retain the above copyright
//       notice, this list of conditions and the following disclaimer.
//
//     * Redistributions in binary form must reproduce the above copyright
//       notice, this list of conditions and the following disclaimer in the
//       documentation and/or other materials provided with the distribution.
//
//     * Neither the name of ETH Zurich and UNC Chapel Hill nor the names of
//       its contributors may be used to endorse or promote products derived
//       from this software without specific prior written permission.
//
// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDERS OR CONTRIBUTORS BE
// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
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// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
// POSSIBILITY OF SUCH DAMAGE.
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// Author: Johannes L. Schoenberger (jsch-at-demuc-dot-de)

#ifndef COLMAP_SRC_FEATURE_UTILS_H_
#define COLMAP_SRC_FEATURE_UTILS_H_

#include "feature/types.h"

namespace colmap {

// Convert feature keypoints to vector of points.
std::vector<Eigen::Vector2d> FeatureKeypointsToPointsVector(
    const FeatureKeypoints& keypoints);

// L2-normalize feature descriptor, where each row represents one feature.
Eigen::MatrixXf L2NormalizeFeatureDescriptors(
    const Eigen::MatrixXf& descriptors);

// L1-Root-normalize feature descriptors, where each row represents one feature.
// See "Three things everyone should know to improve object retrieval",
// Relja Arandjelovic and Andrew Zisserman, CVPR 2012.
Eigen::MatrixXf L1RootNormalizeFeatureDescriptors(
    const Eigen::MatrixXf& descriptors);

// Convert normalized floating point feature descriptor to unsigned byte
// representation by linear scaling from range [0, 0.5] to [0, 255]. Truncation
// to a maximum value of 0.5 is used to avoid precision loss and follows the
// common practice of representing SIFT vectors.
FeatureDescriptors FeatureDescriptorsToUnsignedByte(
    const Eigen::MatrixXf& descriptors);

// Extract the descriptors corresponding to the largest-scale features.
void ExtractTopScaleFeatures(FeatureKeypoints* keypoints,
                             FeatureDescriptors* descriptors,
                             const size_t num_features);

}  // namespace colmap

#endif  // COLMAP_SRC_FEATURE_UTILS_H_
