opticflow_calculator.c

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/*
 * Copyright (C) 2014 Hann Woei Ho
 *               2015 Freek van Tienen <freek.v.tienen@gmail.com>
 *               2016 Kimberly McGuire <k.n.mcguire@tudelft.nl
 *
 * This file is part of Paparazzi.
 *
 * Paparazzi is free software; you can redistribute it and/or modify
 * it under the terms of the GNU General Public License as published by
 * the Free Software Foundation; either version 2, or (at your option)
 * any later version.
 *
 * Paparazzi is distributed in the hope that it will be useful,
 * but WITHOUT ANY WARRANTY; without even the implied warranty of
 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
 * GNU General Public License for more details.
 *
 * You should have received a copy of the GNU General Public License
 * along with Paparazzi; see the file COPYING.  If not, see
 * <http://www.gnu.org/licenses/>.
 */
 
#include "std.h"
 
#include <stdio.h>
#include <string.h>
#include <stdlib.h>
 
// Own Header
#include "opticflow_calculator.h"
 
// Computer Vision
#include "lib/vision/image.h"
#include "lib/vision/lucas_kanade.h"
#include "lib/vision/fast_rosten.h"
#include "lib/vision/act_fast.h"
#include "lib/vision/edge_flow.h"
#include "lib/vision/undistortion.h"
#include "size_divergence.h"
#include "linear_flow_fit.h"
#include "modules/sonar/agl_dist.h"
 
// to get the definition of front_camera / bottom_camera
#include BOARD_CONFIG
 
// whether to show the flow and corners:
#define OPTICFLOW_SHOW_CORNERS 0
 
#define EXHAUSTIVE_FAST 0
#define ACT_FAST 1
// TODO: these are now adapted, but perhaps later could be a setting:
uint16_t n_time_steps[2] = {10, 10};
uint16_t n_agents[2] = {25, 25};
 
// What methods are run to determine divergence, lateral flow, etc.
// SIZE_DIV looks at line sizes and only calculates divergence
#define SIZE_DIV 1
// LINEAR_FIT makes a linear optical flow field fit and extracts a lot of information:
// relative velocities in x, y, z (divergence / time to contact), the slope of the surface, and the surface roughness.
#define LINEAR_FIT 1
 
#ifndef OPTICFLOW_CORNER_METHOD
#define OPTICFLOW_CORNER_METHOD ACT_FAST
#endif
 
#ifndef OPTICFLOW_CORNER_METHOD_CAMERA2
#define OPTICFLOW_CORNER_METHOD_CAMERA2 ACT_FAST
#endif
PRINT_CONFIG_VAR(OPTICFLOW_CORNER_METHOD)
PRINT_CONFIG_VAR(OPTICFLOW_CORNER_METHOD_CAMERA2)
 
/* Set the default values */
#ifndef OPTICFLOW_MAX_TRACK_CORNERS
#define OPTICFLOW_MAX_TRACK_CORNERS 25
#endif
 
#ifndef OPTICFLOW_MAX_TRACK_CORNERS_CAMERA2
#define OPTICFLOW_MAX_TRACK_CORNERS_CAMERA2 25
#endif
PRINT_CONFIG_VAR(OPTICFLOW_MAX_TRACK_CORNERS)
PRINT_CONFIG_VAR(OPTICFLOW_MAX_TRACK_CORNERS_CAMERA2)
 
#ifndef OPTICFLOW_WINDOW_SIZE
#define OPTICFLOW_WINDOW_SIZE 10
#endif
 
#ifndef OPTICFLOW_WINDOW_SIZE_CAMERA2
#define OPTICFLOW_WINDOW_SIZE_CAMERA2 10
#endif
PRINT_CONFIG_VAR(OPTICFLOW_WINDOW_SIZE)
PRINT_CONFIG_VAR(OPTICFLOW_WINDOW_SIZE_CAMERA2)
 
#ifndef OPTICFLOW_SEARCH_DISTANCE
#define OPTICFLOW_SEARCH_DISTANCE 20
#endif
 
#ifndef OPTICFLOW_SEARCH_DISTANCE_CAMERA2
#define OPTICFLOW_SEARCH_DISTANCE_CAMERA2 20
#endif
PRINT_CONFIG_VAR(OPTICFLOW_SEARCH_DISTANCE)
PRINT_CONFIG_VAR(OPTICFLOW_SEARCH_DISTANCE_CAMERA2)
 
#ifndef OPTICFLOW_SUBPIXEL_FACTOR
#define OPTICFLOW_SUBPIXEL_FACTOR 10
#endif
 
#ifndef OPTICFLOW_SUBPIXEL_FACTOR_CAMERA2
#define OPTICFLOW_SUBPIXEL_FACTOR_CAMERA2 10
#endif
PRINT_CONFIG_VAR(OPTICFLOW_SUBPIXEL_FACTOR)
PRINT_CONFIG_VAR(OPTICFLOW_SUBPIXEL_FACTOR_CAMERA2)
 
#ifndef OPTICFLOW_RESOLUTION_FACTOR
#define OPTICFLOW_RESOLUTION_FACTOR 100
#endif
 
#ifndef OPTICFLOW_RESOLUTION_FACTOR_CAMERA2
#define OPTICFLOW_RESOLUTION_FACTOR_CAMERA2 100
#endif
PRINT_CONFIG_VAR(OPTICFLOW_RESOLUTION_FACTOR)
PRINT_CONFIG_VAR(OPTICFLOW_RESOLUTION_FACTOR_CAMERA2)
 
#ifndef OPTICFLOW_MAX_ITERATIONS
#define OPTICFLOW_MAX_ITERATIONS 10
#endif
 
#ifndef OPTICFLOW_MAX_ITERATIONS_CAMERA2
#define OPTICFLOW_MAX_ITERATIONS_CAMERA2 10
#endif
PRINT_CONFIG_VAR(OPTICFLOW_MAX_ITERATIONS)
PRINT_CONFIG_VAR(OPTICFLOW_MAX_ITERATIONS_CAMERA2)
 
#ifndef OPTICFLOW_THRESHOLD_VEC
#define OPTICFLOW_THRESHOLD_VEC 2
#endif
 
#ifndef OPTICFLOW_THRESHOLD_VEC_CAMERA2
#define OPTICFLOW_THRESHOLD_VEC_CAMERA2 2
#endif
PRINT_CONFIG_VAR(OPTICFLOW_THRESHOLD_VEC)
PRINT_CONFIG_VAR(OPTICFLOW_THRESHOLD_VEC_CAMERA2)
 
#ifndef OPTICFLOW_PYRAMID_LEVEL
#define OPTICFLOW_PYRAMID_LEVEL 2
#endif
 
#ifndef OPTICFLOW_PYRAMID_LEVEL_CAMERA2
#define OPTICFLOW_PYRAMID_LEVEL_CAMERA2 2
#endif
PRINT_CONFIG_VAR(OPTICFLOW_PYRAMID_LEVEL)
PRINT_CONFIG_VAR(OPTICFLOW_PYRAMID_LEVEL_CAMERA2)
 
#ifndef OPTICFLOW_FAST9_ADAPTIVE
#define OPTICFLOW_FAST9_ADAPTIVE TRUE
#endif
 
#ifndef OPTICFLOW_FAST9_ADAPTIVE_CAMERA2
#define OPTICFLOW_FAST9_ADAPTIVE_CAMERA2 TRUE
#endif
PRINT_CONFIG_VAR(OPTICFLOW_FAST9_ADAPTIVE)
PRINT_CONFIG_VAR(OPTICFLOW_FAST9_ADAPTIVE_CAMERA2)
 
#ifndef OPTICFLOW_FAST9_THRESHOLD
#define OPTICFLOW_FAST9_THRESHOLD 20
#endif
 
#ifndef OPTICFLOW_FAST9_THRESHOLD_CAMERA2
#define OPTICFLOW_FAST9_THRESHOLD_CAMERA2 20
#endif
PRINT_CONFIG_VAR(OPTICFLOW_FAST9_THRESHOLD)
PRINT_CONFIG_VAR(OPTICFLOW_FAST9_THRESHOLD_CAMERA2)
 
#ifndef OPTICFLOW_FAST9_MIN_DISTANCE
#define OPTICFLOW_FAST9_MIN_DISTANCE 10
#endif
 
#ifndef OPTICFLOW_FAST9_MIN_DISTANCE_CAMERA2
#define OPTICFLOW_FAST9_MIN_DISTANCE_CAMERA2 10
#endif
PRINT_CONFIG_VAR(OPTICFLOW_FAST9_MIN_DISTANCE)
PRINT_CONFIG_VAR(OPTICFLOW_FAST9_MIN_DISTANCE_CAMERA2)
 
#ifndef OPTICFLOW_FAST9_PADDING
#define OPTICFLOW_FAST9_PADDING 20
#endif
 
#ifndef OPTICFLOW_FAST9_PADDING_CAMERA2
#define OPTICFLOW_FAST9_PADDING_CAMERA2 20
#endif
PRINT_CONFIG_VAR(OPTICFLOW_FAST9_PADDING)
PRINT_CONFIG_VAR(OPTICFLOW_FAST9_PADDING_CAMERA2)
 
// thresholds FAST9 that are currently not set from the GCS:
#define FAST9_LOW_THRESHOLD 5
#define FAST9_HIGH_THRESHOLD 60
 
 
#ifndef OPTICFLOW_METHOD
#define OPTICFLOW_METHOD 0
#endif
 
#ifndef OPTICFLOW_METHOD_CAMERA2
#define OPTICFLOW_METHOD_CAMERA2 0
#endif
PRINT_CONFIG_VAR(OPTICFLOW_METHOD)
PRINT_CONFIG_VAR(OPTICFLOW_METHOD_CAMERA2)
 
#if OPTICFLOW_METHOD > 1
#error WARNING: Both Lukas Kanade and EdgeFlow are NOT selected camera1
#endif
 
#if OPTICFLOW_METHOD_CAMERA2 > 1
#error WARNING: Both Lukas Kanade and EdgeFlow are NOT selected camera2
#endif
 
#ifndef OPTICFLOW_DEROTATION
#define OPTICFLOW_DEROTATION TRUE
#endif
 
#ifndef OPTICFLOW_DEROTATION_CAMERA2
#define OPTICFLOW_DEROTATION_CAMERA2 TRUE
#endif
PRINT_CONFIG_VAR(OPTICFLOW_DEROTATION)
PRINT_CONFIG_VAR(OPTICFLOW_DEROTATION_CAMERA2)
 
#ifndef OPTICFLOW_DEROTATION_CORRECTION_FACTOR_X
#define OPTICFLOW_DEROTATION_CORRECTION_FACTOR_X 1.0
#endif
 
#ifndef OPTICFLOW_DEROTATION_CORRECTION_FACTOR_X_CAMERA2
#define OPTICFLOW_DEROTATION_CORRECTION_FACTOR_X_CAMERA2 1.0
#endif
PRINT_CONFIG_VAR(OPTICFLOW_DEROTATION_CORRECTION_FACTOR_X)
PRINT_CONFIG_VAR(OPTICFLOW_DEROTATION_CORRECTION_FACTOR_X_CAMERA2)
 
#ifndef OPTICFLOW_DEROTATION_CORRECTION_FACTOR_Y
#define OPTICFLOW_DEROTATION_CORRECTION_FACTOR_Y 1.0
#endif
 
#ifndef OPTICFLOW_DEROTATION_CORRECTION_FACTOR_Y_CAMERA2
#define OPTICFLOW_DEROTATION_CORRECTION_FACTOR_Y_CAMERA2 1.0
#endif
PRINT_CONFIG_VAR(OPTICFLOW_DEROTATION_CORRECTION_FACTOR_Y)
PRINT_CONFIG_VAR(OPTICFLOW_DEROTATION_CORRECTION_FACTOR_Y_CAMERA2)
 
#ifndef OPTICFLOW_MEDIAN_FILTER
#define OPTICFLOW_MEDIAN_FILTER FALSE
#endif
 
#ifndef OPTICFLOW_MEDIAN_FILTER_CAMERA2
#define OPTICFLOW_MEDIAN_FILTER_CAMERA2 FALSE
#endif
PRINT_CONFIG_VAR(OPTICFLOW_MEDIAN_FILTER)
PRINT_CONFIG_VAR(OPTICFLOW_MEDIAN_FILTER_CAMERA2)
 
#ifndef OPTICFLOW_FEATURE_MANAGEMENT
#define OPTICFLOW_FEATURE_MANAGEMENT 0
#endif
 
#ifndef OPTICFLOW_FEATURE_MANAGEMENT_CAMERA2
#define OPTICFLOW_FEATURE_MANAGEMENT_CAMERA2 0
#endif
PRINT_CONFIG_VAR(OPTICFLOW_FEATURE_MANAGEMENT)
PRINT_CONFIG_VAR(OPTICFLOW_FEATURE_MANAGEMENT_CAMERA2)
 
#ifndef OPTICFLOW_FAST9_REGION_DETECT
#define OPTICFLOW_FAST9_REGION_DETECT 1
#endif
 
#ifndef OPTICFLOW_FAST9_REGION_DETECT_CAMERA2
#define OPTICFLOW_FAST9_REGION_DETECT_CAMERA2 1
#endif
PRINT_CONFIG_VAR(OPTICFLOW_FAST9_REGION_DETECT)
PRINT_CONFIG_VAR(OPTICFLOW_FAST9_REGION_DETECT_CAMERA2)
 
#ifndef OPTICFLOW_FAST9_NUM_REGIONS
#define OPTICFLOW_FAST9_NUM_REGIONS 9
#endif
 
#ifndef OPTICFLOW_FAST9_NUM_REGIONS_CAMERA2
#define OPTICFLOW_FAST9_NUM_REGIONS_CAMERA2 9
#endif
PRINT_CONFIG_VAR(OPTICFLOW_FAST9_NUM_REGIONS)
PRINT_CONFIG_VAR(OPTICFLOW_FAST9_NUM_REGIONS_CAMERA2)
 
#ifndef OPTICFLOW_ACTFAST_LONG_STEP
#define OPTICFLOW_ACTFAST_LONG_STEP 10
#endif
 
#ifndef OPTICFLOW_ACTFAST_LONG_STEP_CAMERA2
#define OPTICFLOW_ACTFAST_LONG_STEP_CAMERA2 10
#endif
PRINT_CONFIG_VAR(OPTICFLOW_ACTFAST_LONG_STEP)
PRINT_CONFIG_VAR(OPTICFLOW_ACTFAST_LONG_STEP_CAMERA2)
 
#ifndef OPTICFLOW_ACTFAST_SHORT_STEP
#define OPTICFLOW_ACTFAST_SHORT_STEP 2
#endif
 
#ifndef OPTICFLOW_ACTFAST_SHORT_STEP_CAMERA2
#define OPTICFLOW_ACTFAST_SHORT_STEP_CAMERA2 2
#endif
PRINT_CONFIG_VAR(OPTICFLOW_ACTFAST_SHORT_STEP)
PRINT_CONFIG_VAR(OPTICFLOW_ACTFAST_SHORT_STEP_CAMERA2)
 
#ifndef OPTICFLOW_ACTFAST_GRADIENT_METHOD
#define OPTICFLOW_ACTFAST_GRADIENT_METHOD 1
#endif
 
#ifndef OPTICFLOW_ACTFAST_GRADIENT_METHOD_CAMERA2
#define OPTICFLOW_ACTFAST_GRADIENT_METHOD_CAMERA2 1
#endif
PRINT_CONFIG_VAR(OPTICFLOW_ACTFAST_GRADIENT_METHOD)
PRINT_CONFIG_VAR(OPTICFLOW_ACTFAST_GRADIENT_METHOD_CAMERA2)
 
#ifndef OPTICFLOW_ACTFAST_MIN_GRADIENT
#define OPTICFLOW_ACTFAST_MIN_GRADIENT 10
#endif
 
#ifndef OPTICFLOW_ACTFAST_MIN_GRADIENT_CAMERA2
#define OPTICFLOW_ACTFAST_MIN_GRADIENT_CAMERA2 10
#endif
PRINT_CONFIG_VAR(OPTICFLOW_ACTFAST_MIN_GRADIENT)
PRINT_CONFIG_VAR(OPTICFLOW_ACTFAST_MIN_GRADIENT_CAMERA2)
 
// Defaults for ARdrone
#ifndef OPTICFLOW_BODY_TO_CAM_PHI
#define OPTICFLOW_BODY_TO_CAM_PHI 0
#endif
#ifndef OPTICFLOW_BODY_TO_CAM_THETA
#define OPTICFLOW_BODY_TO_CAM_THETA 0
#endif
#ifndef OPTICFLOW_BODY_TO_CAM_PSI
#define OPTICFLOW_BODY_TO_CAM_PSI -M_PI_2
#endif
 
#ifndef OPTICFLOW_BODY_TO_CAM_PHI_CAMERA2
#define OPTICFLOW_BODY_TO_CAM_PHI_CAMERA2 0
#endif
#ifndef OPTICFLOW_BODY_TO_CAM_THETA_CAMERA2
#define OPTICFLOW_BODY_TO_CAM_THETA_CAMERA2 0
#endif
#ifndef OPTICFLOW_BODY_TO_CAM_PSI_CAMERA2
#define OPTICFLOW_BODY_TO_CAM_PSI_CAMERA2 -M_PI_2
#endif
 
// Tracking back flow to make the accepted flow vectors more robust:
// Default is false, as it does take extra processing time
#ifndef OPTICFLOW_TRACK_BACK
#define OPTICFLOW_TRACK_BACK FALSE
#endif
 
#ifndef OPTICFLOW_TRACK_BACK_CAMERA2
#define OPTICFLOW_TRACK_BACK_CAMERA2 FALSE
#endif
PRINT_CONFIG_VAR(OPTICFLOW_TRACK_BACK)
PRINT_CONFIG_VAR(OPTICFLOW_TRACK_BACK_CAMERA2)
 
// Whether to draw the flow on the image:
// False by default, since it changes the image and costs time.
#ifndef OPTICFLOW_SHOW_FLOW
#define OPTICFLOW_SHOW_FLOW FALSE
#endif
 
#ifndef OPTICFLOW_SHOW_FLOW_CAMERA2
#define OPTICFLOW_SHOW_FLOW_CAMERA2 FALSE
#endif
PRINT_CONFIG_VAR(OPTICFLOW_SHOW_FLOW)
PRINT_CONFIG_VAR(OPTICFLOW_SHOW_FLOW_CAMERA2)
 
 
//Include median filter
#include "filters/median_filter.h"
struct MedianFilter3Float vel_filt;
struct FloatRMat body_to_cam[2];
 
/* Functions only used here */
static uint32_t timeval_diff(struct timeval *starttime, struct timeval *finishtime);
static int cmp_flow(const void *a, const void *b);
static int cmp_array(const void *a, const void *b);
static void manage_flow_features(struct image_t *img, struct opticflow_t *opticflow,
                                 struct opticflow_result_t *result);
 
static struct flow_t *predict_flow_vectors(struct flow_t *flow_vectors, uint16_t n_points, float phi_diff,
    float theta_diff, float psi_diff, struct opticflow_t *opticflow);
void opticflow_calc_init(struct opticflow_t opticflow[])
{
  /* Set the default values */
  opticflow[0].method = OPTICFLOW_METHOD; //0 = LK_fast9, 1 = Edgeflow
  opticflow[0].window_size = OPTICFLOW_WINDOW_SIZE;
  opticflow[0].search_distance = OPTICFLOW_SEARCH_DISTANCE;
  opticflow[0].derotation = OPTICFLOW_DEROTATION; //0 = OFF, 1 = ON
  opticflow[0].derotation_correction_factor_x = OPTICFLOW_DEROTATION_CORRECTION_FACTOR_X;
  opticflow[0].derotation_correction_factor_y = OPTICFLOW_DEROTATION_CORRECTION_FACTOR_Y;
  opticflow[0].track_back = OPTICFLOW_TRACK_BACK;
  opticflow[0].show_flow = OPTICFLOW_SHOW_FLOW;
  opticflow[0].max_track_corners = OPTICFLOW_MAX_TRACK_CORNERS;
  opticflow[0].subpixel_factor = OPTICFLOW_SUBPIXEL_FACTOR;
  if (opticflow[0].subpixel_factor == 0) {
    opticflow[0].subpixel_factor = 10;
  }
  opticflow[0].resolution_factor = OPTICFLOW_RESOLUTION_FACTOR;
  opticflow[0].max_iterations = OPTICFLOW_MAX_ITERATIONS;
  opticflow[0].threshold_vec = OPTICFLOW_THRESHOLD_VEC;
  opticflow[0].pyramid_level = OPTICFLOW_PYRAMID_LEVEL;
  opticflow[0].median_filter = OPTICFLOW_MEDIAN_FILTER;
  opticflow[0].feature_management = OPTICFLOW_FEATURE_MANAGEMENT;
  opticflow[0].fast9_region_detect = OPTICFLOW_FAST9_REGION_DETECT;
  opticflow[0].fast9_num_regions = OPTICFLOW_FAST9_NUM_REGIONS;
 
  opticflow[0].fast9_adaptive = OPTICFLOW_FAST9_ADAPTIVE;
  opticflow[0].fast9_threshold = OPTICFLOW_FAST9_THRESHOLD;
  opticflow[0].fast9_min_distance = OPTICFLOW_FAST9_MIN_DISTANCE;
  opticflow[0].fast9_padding = OPTICFLOW_FAST9_PADDING;
  opticflow[0].fast9_rsize = FAST9_MAX_CORNERS;
  opticflow[0].fast9_ret_corners = calloc(opticflow[0].fast9_rsize, sizeof(struct point_t));
 
  opticflow[0].corner_method = OPTICFLOW_CORNER_METHOD;
  opticflow[0].actfast_long_step = OPTICFLOW_ACTFAST_LONG_STEP;
  opticflow[0].actfast_short_step = OPTICFLOW_ACTFAST_SHORT_STEP;
  opticflow[0].actfast_min_gradient = OPTICFLOW_ACTFAST_MIN_GRADIENT;
  opticflow[0].actfast_gradient_method = OPTICFLOW_ACTFAST_GRADIENT_METHOD;
 
  opticflow[0].camera = &OPTICFLOW_CAMERA;
  opticflow[0].id = 0;
 
  struct FloatEulers euler_cam1 = {OPTICFLOW_BODY_TO_CAM_PHI, OPTICFLOW_BODY_TO_CAM_THETA, OPTICFLOW_BODY_TO_CAM_PSI};
  float_rmat_of_eulers(&body_to_cam[0], &euler_cam1);
 
#ifdef OPTICFLOW_CAMERA2
  opticflow[1].method = OPTICFLOW_METHOD_CAMERA2; //0 = LK_fast9, 1 = Edgeflow
  opticflow[1].window_size = OPTICFLOW_WINDOW_SIZE_CAMERA2;
  opticflow[1].search_distance = OPTICFLOW_SEARCH_DISTANCE_CAMERA2;
  opticflow[1].derotation = OPTICFLOW_DEROTATION_CAMERA2; //0 = OFF, 1 = ON
  opticflow[1].derotation_correction_factor_x = OPTICFLOW_DEROTATION_CORRECTION_FACTOR_X_CAMERA2;
  opticflow[1].derotation_correction_factor_y = OPTICFLOW_DEROTATION_CORRECTION_FACTOR_Y_CAMERA2;
  opticflow[1].track_back = OPTICFLOW_TRACK_BACK_CAMERA2;
  opticflow[1].show_flow = OPTICFLOW_SHOW_FLOW_CAMERA2;
  opticflow[1].max_track_corners = OPTICFLOW_MAX_TRACK_CORNERS_CAMERA2;
  opticflow[1].subpixel_factor = OPTICFLOW_SUBPIXEL_FACTOR_CAMERA2;
  if (opticflow[1].subpixel_factor == 0) {
    opticflow[1].subpixel_factor = 10;
  }
  opticflow[1].resolution_factor = OPTICFLOW_RESOLUTION_FACTOR_CAMERA2;
  opticflow[1].max_iterations = OPTICFLOW_MAX_ITERATIONS_CAMERA2;
  opticflow[1].threshold_vec = OPTICFLOW_THRESHOLD_VEC_CAMERA2;
  opticflow[1].pyramid_level = OPTICFLOW_PYRAMID_LEVEL_CAMERA2;
  opticflow[1].median_filter = OPTICFLOW_MEDIAN_FILTER_CAMERA2;
  opticflow[1].feature_management = OPTICFLOW_FEATURE_MANAGEMENT_CAMERA2;
  opticflow[1].fast9_region_detect = OPTICFLOW_FAST9_REGION_DETECT_CAMERA2;
  opticflow[1].fast9_num_regions = OPTICFLOW_FAST9_NUM_REGIONS_CAMERA2;
 
  opticflow[1].fast9_adaptive = OPTICFLOW_FAST9_ADAPTIVE_CAMERA2;
  opticflow[1].fast9_threshold = OPTICFLOW_FAST9_THRESHOLD_CAMERA2;
  opticflow[1].fast9_min_distance = OPTICFLOW_FAST9_MIN_DISTANCE_CAMERA2;
  opticflow[1].fast9_padding = OPTICFLOW_FAST9_PADDING_CAMERA2;
  opticflow[1].fast9_rsize = FAST9_MAX_CORNERS;
  opticflow[1].fast9_ret_corners = calloc(opticflow[0].fast9_rsize, sizeof(struct point_t));
 
  opticflow[1].corner_method = OPTICFLOW_CORNER_METHOD_CAMERA2;
  opticflow[1].actfast_long_step = OPTICFLOW_ACTFAST_LONG_STEP_CAMERA2;
  opticflow[1].actfast_short_step = OPTICFLOW_ACTFAST_SHORT_STEP_CAMERA2;
  opticflow[1].actfast_min_gradient = OPTICFLOW_ACTFAST_MIN_GRADIENT_CAMERA2;
  opticflow[1].actfast_gradient_method = OPTICFLOW_ACTFAST_GRADIENT_METHOD_CAMERA2;
 
  opticflow[1].camera = &OPTICFLOW_CAMERA2;
  opticflow[1].id = 1;
 
  struct FloatEulers euler_cam2 = {OPTICFLOW_BODY_TO_CAM_PHI_CAMERA2, OPTICFLOW_BODY_TO_CAM_THETA_CAMERA2,
      OPTICFLOW_BODY_TO_CAM_PSI_CAMERA2};
  float_rmat_of_eulers(&body_to_cam[1], &euler_cam2);
#endif
}
bool calc_fast9_lukas_kanade(struct opticflow_t *opticflow, struct image_t *img,
                             struct opticflow_result_t *result)
{
  if (opticflow->just_switched_method) {
    // Create the image buffers
    image_create(&opticflow->img_gray, img->w, img->h, IMAGE_GRAYSCALE);
    image_create(&opticflow->prev_img_gray, img->w, img->h, IMAGE_GRAYSCALE);
 
    // Set the previous values
    opticflow->got_first_img = false;
 
    // Init median filters with zeros
    InitMedianFilterVect3Float(vel_filt, MEDIAN_DEFAULT_SIZE);
  }
 
  // Convert image to grayscale
  image_to_grayscale(img, &opticflow->img_gray);
 
  if (!opticflow->got_first_img) {
    image_copy(&opticflow->img_gray, &opticflow->prev_img_gray);
    opticflow->got_first_img = true;
    return false;
  }
 
  // variables for linear flow fit:
  float error_threshold;
  int n_iterations_RANSAC, n_samples_RANSAC, success_fit;
  struct linear_flow_fit_info fit_info;
 
  // Update FPS for information
  float dt = timeval_diff(&(opticflow->prev_img_gray.ts), &(img->ts));
  if (dt > 1e-5) {
    result->fps = 1000.f / dt;
  } else {
    return false;
  }
 
  // *************************************************************************************
  // Corner detection
  // *************************************************************************************
 
  // if feature_management is selected and tracked corners drop below a threshold, redetect
  if ((opticflow->feature_management) && (result->corner_cnt < opticflow->max_track_corners / 2)) {
    manage_flow_features(img, opticflow, result);
  } else if (!opticflow->feature_management) {
    // needs to be set to 0 because result is now static
    result->corner_cnt = 0;
    if (opticflow->corner_method == EXHAUSTIVE_FAST) {
      // FAST corner detection
      // TODO: There is something wrong with fast9_detect destabilizing FPS. This problem is reduced with putting min_distance
      // to 0 (see defines), however a more permanent solution should be considered
      fast9_detect(&opticflow->prev_img_gray, opticflow->fast9_threshold, opticflow->fast9_min_distance,
                   opticflow->fast9_padding, opticflow->fast9_padding, &result->corner_cnt, &opticflow->fast9_rsize,
                   &opticflow->fast9_ret_corners, NULL);
    } else if (opticflow->corner_method == ACT_FAST) {
      // ACT-FAST corner detection:
      act_fast(&opticflow->prev_img_gray, opticflow->fast9_threshold, &result->corner_cnt,
               &opticflow->fast9_ret_corners, n_agents[opticflow->id], n_time_steps[opticflow->id],
               opticflow->actfast_long_step, opticflow->actfast_short_step, opticflow->actfast_min_gradient,
               opticflow->actfast_gradient_method, opticflow->id);
    }
 
    // Adaptive threshold
    if (opticflow->fast9_adaptive) {
 
      // This works well for exhaustive FAST, but drives the threshold to the minimum for ACT-FAST:
      // Decrease and increase the threshold based on previous values
      if (result->corner_cnt < opticflow->max_track_corners / 2) {
        // make detections easier:
        if (opticflow->fast9_threshold > FAST9_LOW_THRESHOLD) {
          opticflow->fast9_threshold--;
        }
 
        if (opticflow->corner_method == ACT_FAST && n_agents[opticflow->id] < opticflow->fast9_rsize) {
          n_time_steps[opticflow->id]++;
          n_agents[opticflow->id]++;
        }
 
      } else if (result->corner_cnt > opticflow->max_track_corners * 2) {
 
        if (opticflow->fast9_threshold < FAST9_HIGH_THRESHOLD) {
          opticflow->fast9_threshold++;
        }
 
        if (opticflow->corner_method == ACT_FAST && n_time_steps[opticflow->id] > 5 && n_agents[opticflow->id] > 10) {
          n_time_steps[opticflow->id]--;
          n_agents[opticflow->id]--;
        }
      }
    }
  }
 
#if OPTICFLOW_SHOW_CORNERS
  image_show_points(img, opticflow->fast9_ret_corners, result->corner_cnt);
#endif
 
  // Check if we found some corners to track
  if (result->corner_cnt < 1) {
    // Clear the result otherwise the previous values will be returned for this frame too
    VECT3_ASSIGN(result->vel_cam, 0, 0, 0);
    VECT3_ASSIGN(result->vel_body, 0, 0, 0);
    result->div_size = 0;
    result->divergence = 0;
    result->noise_measurement = 5.0;
 
    image_switch(&opticflow->img_gray, &opticflow->prev_img_gray);
    return false;
  }
 
  // *************************************************************************************
  // Corner Tracking
  // *************************************************************************************
 
  // Execute a Lucas Kanade optical flow
  result->tracked_cnt = result->corner_cnt;
  uint8_t keep_bad_points = 0;
  struct flow_t *vectors = opticFlowLK(&opticflow->img_gray, &opticflow->prev_img_gray, opticflow->fast9_ret_corners,
                                       &result->tracked_cnt,
                                       opticflow->window_size / 2, opticflow->subpixel_factor, opticflow->max_iterations,
                                       opticflow->threshold_vec, opticflow->max_track_corners, opticflow->pyramid_level, keep_bad_points);
 
 
  if (opticflow->track_back) {
    // TODO: Watch out!
    // We track the flow back and give badly back-tracked vectors a high error,
    // but we do not yet remove these vectors, nor use the errors in any other function than showing the flow.
 
    // initialize corners at the tracked positions:
    for (int i = 0; i < result->tracked_cnt; i++) {
      opticflow->fast9_ret_corners[i].x = (uint32_t)(vectors[i].pos.x + vectors[i].flow_x) / opticflow->subpixel_factor;
      opticflow->fast9_ret_corners[i].y = (uint32_t)(vectors[i].pos.y + vectors[i].flow_y) / opticflow->subpixel_factor;
    }
 
    // present the images in the opposite order:
    keep_bad_points = 1;
    uint16_t back_track_cnt = result->tracked_cnt;
    struct flow_t *back_vectors = opticFlowLK(&opticflow->prev_img_gray, &opticflow->img_gray, opticflow->fast9_ret_corners,
                                  &back_track_cnt,
                                  opticflow->window_size / 2, opticflow->subpixel_factor, opticflow->max_iterations,
                                  opticflow->threshold_vec, opticflow->max_track_corners, opticflow->pyramid_level, keep_bad_points);
 
    // printf("Tracked %d points back.\n", back_track_cnt);
    int32_t back_x, back_y, diff_x, diff_y, dist_squared;
    int32_t back_track_threshold = 200;
 
    for (int i = 0; i < result->tracked_cnt; i++) {
      if (back_vectors[i].error < LARGE_FLOW_ERROR) {
        back_x = (int32_t)(back_vectors[i].pos.x + back_vectors[i].flow_x);
        back_y = (int32_t)(back_vectors[i].pos.y + back_vectors[i].flow_y);
        diff_x = back_x - vectors[i].pos.x;
        diff_y = back_y - vectors[i].pos.y;
        dist_squared = diff_x * diff_x + diff_y * diff_y;
        // printf("Vector %d: x,y = %d, %d, back x, y = %d, %d, back tracking error %d\n", i, vectors[i].pos.x, vectors[i].pos.y, back_x, back_y, dist_squared);
        if (dist_squared > back_track_threshold) {
          vectors[i].error = LARGE_FLOW_ERROR;
        }
      } else {
        vectors[i].error = LARGE_FLOW_ERROR;
      }
    }
 
    free(back_vectors);
  }
 
  if (opticflow->show_flow) {
    uint8_t color[4] = {0, 0, 0, 0};
    uint8_t bad_color[4] = {0, 0, 0, 0};
    image_show_flow_color(img, vectors, result->tracked_cnt, opticflow->subpixel_factor, color, bad_color);
  }
 
  static int n_samples = 100;
  // Estimate size divergence:
  if (SIZE_DIV) {
    result->div_size = get_size_divergence(vectors, result->tracked_cnt, n_samples);// * result->fps;
  } else {
    result->div_size = 0.0f;
  }
 
  if (LINEAR_FIT) {
    // Linear flow fit (normally derotation should be performed before):
    error_threshold = 10.0f;
    n_iterations_RANSAC = 20;
    n_samples_RANSAC = 5;
    success_fit = analyze_linear_flow_field(vectors, result->tracked_cnt, error_threshold, n_iterations_RANSAC,
                                            n_samples_RANSAC, img->w, img->h, &fit_info);
 
    if (!success_fit) {
      fit_info.divergence = 0.0f;
      fit_info.surface_roughness = 0.0f;
    }
 
    result->divergence = fit_info.divergence;
    result->surface_roughness = fit_info.surface_roughness;
  } else {
    result->divergence = 0.0f;
    result->surface_roughness = 0.0f;
  }
 
  // Get the median flow
  qsort(vectors, result->tracked_cnt, sizeof(struct flow_t), cmp_flow);
  if (result->tracked_cnt == 0) {
    // We got no flow
    result->flow_x = 0;
    result->flow_y = 0;
 
    free(vectors);
    image_switch(&opticflow->img_gray, &opticflow->prev_img_gray);
    return false;
  } else if (result->tracked_cnt % 2) {
    // Take the median point
    result->flow_x = vectors[result->tracked_cnt / 2].flow_x;
    result->flow_y = vectors[result->tracked_cnt / 2].flow_y;
  } else {
    // Take the average of the 2 median points
    result->flow_x = (vectors[result->tracked_cnt / 2 - 1].flow_x + vectors[result->tracked_cnt / 2].flow_x) / 2.f;
    result->flow_y = (vectors[result->tracked_cnt / 2 - 1].flow_y + vectors[result->tracked_cnt / 2].flow_y) / 2.f;
  }
 
  // TODO scale flow to rad/s here
 
  // ***************
  // Flow Derotation
  // ***************
 
  float diff_flow_x = 0.f;
  float diff_flow_y = 0.f;
 
  if (opticflow->derotation && result->tracked_cnt > 5) {
 
    float rotation_threshold = M_PI / 180.0f;
    if (fabs(opticflow->img_gray.eulers.phi - opticflow->prev_img_gray.eulers.phi) > rotation_threshold
        || fabs(opticflow->img_gray.eulers.theta - opticflow->prev_img_gray.eulers.theta) > rotation_threshold) {
 
      // do not apply the derotation if the rotation rates are too high:
      result->flow_der_x = 0.0f;
      result->flow_der_y = 0.0f;
 
    } else {
 
      // determine the roll, pitch, yaw differencces between the images.
      float phi_diff = opticflow->img_gray.eulers.phi - opticflow->prev_img_gray.eulers.phi;
      float theta_diff = opticflow->img_gray.eulers.theta - opticflow->prev_img_gray.eulers.theta;
      float psi_diff = opticflow->img_gray.eulers.psi - opticflow->prev_img_gray.eulers.psi;
 
      if (strcmp(opticflow->camera->dev_name, bottom_camera.dev_name) == 0) {
        // bottom cam: just subtract a scaled version of the roll and pitch difference from the global flow vector:
        diff_flow_x = phi_diff * opticflow->camera->camera_intrinsics.focal_x; // phi_diff works better than (cam_state->rates.p)
        diff_flow_y = theta_diff * opticflow->camera->camera_intrinsics.focal_y;
        result->flow_der_x = result->flow_x - diff_flow_x * opticflow->subpixel_factor *
                             opticflow->derotation_correction_factor_x;
        result->flow_der_y = result->flow_y - diff_flow_y * opticflow->subpixel_factor *
                             opticflow->derotation_correction_factor_y;
      } else {
        // frontal cam, predict individual flow vectors:
        struct flow_t *predicted_flow_vectors = predict_flow_vectors(vectors, result->tracked_cnt, phi_diff, theta_diff,
                                                psi_diff, opticflow);
        if (opticflow->show_flow) {
          uint8_t color[4] = {255, 255, 255, 255};
          uint8_t bad_color[4] = {255, 255, 255, 255};
          image_show_flow_color(img, predicted_flow_vectors, result->tracked_cnt, opticflow->subpixel_factor, color, bad_color);
        }
 
        for (int i = 0; i < result->tracked_cnt; i++) {
          // subtract the flow:
          vectors[i].flow_x -= predicted_flow_vectors[i].flow_x;
          vectors[i].flow_y -= predicted_flow_vectors[i].flow_y;
        }
 
        // vectors have to be re-sorted after derotation:
        qsort(vectors, result->tracked_cnt, sizeof(struct flow_t), cmp_flow);
 
        if (result->tracked_cnt % 2) {
          // Take the median point
          result->flow_der_x = vectors[result->tracked_cnt / 2].flow_x;
          result->flow_der_y = vectors[result->tracked_cnt / 2].flow_y;
        } else {
          // Take the average of the 2 median points
          result->flow_der_x = (vectors[result->tracked_cnt / 2 - 1].flow_x + vectors[result->tracked_cnt / 2].flow_x) / 2.f;
          result->flow_der_y = (vectors[result->tracked_cnt / 2 - 1].flow_y + vectors[result->tracked_cnt / 2].flow_y) / 2.f;
        }
      }
    }
  }
  result->camera_id = opticflow->id;
 
  // Velocity calculation
  // Right now this formula is under assumption that the flow only exist in the center axis of the camera.
  // TODO: Calculate the velocity more sophisticated, taking into account the drone's angle and the slope of the ground plane.
  // TODO: This is actually only correct for the bottom camera:
  result->vel_cam.x = (float)result->flow_der_x * result->fps * agl_dist_value_filtered /
                      (opticflow->subpixel_factor * opticflow->camera->camera_intrinsics.focal_x);
  result->vel_cam.y = (float)result->flow_der_y * result->fps * agl_dist_value_filtered /
                      (opticflow->subpixel_factor * opticflow->camera->camera_intrinsics.focal_y);
  result->vel_cam.z = result->divergence * result->fps * agl_dist_value_filtered;
 
  //Apply a  median filter to the velocity if wanted
  if (opticflow->median_filter == true) {
    UpdateMedianFilterVect3Float(vel_filt, result->vel_cam);
  }
 
  // Determine quality of noise measurement for state filter
  //TODO develop a noise model based on groundtruth
  //result->noise_measurement = 1 - (float)result->tracked_cnt / ((float)opticflow->max_track_corners * 1.25f);
  result->noise_measurement = 0.25;
 
  // *************************************************************************************
  // Next Loop Preparation
  // *************************************************************************************
  if (opticflow->feature_management) {
    result->corner_cnt = result->tracked_cnt;
    //get the new positions of the corners and the "residual" subpixel positions
    for (uint16_t i = 0; i < result->tracked_cnt; i++) {
      opticflow->fast9_ret_corners[i].x = (uint32_t)((vectors[i].pos.x + (float)vectors[i].flow_x) /
                                          opticflow->subpixel_factor);
      opticflow->fast9_ret_corners[i].y = (uint32_t)((vectors[i].pos.y + (float)vectors[i].flow_y) /
                                          opticflow->subpixel_factor);
      opticflow->fast9_ret_corners[i].x_sub = (uint16_t)((vectors[i].pos.x + vectors[i].flow_x) % opticflow->subpixel_factor);
      opticflow->fast9_ret_corners[i].y_sub = (uint16_t)((vectors[i].pos.y + vectors[i].flow_y) % opticflow->subpixel_factor);
      opticflow->fast9_ret_corners[i].count = vectors[i].pos.count;
    }
  }
  free(vectors);
  image_switch(&opticflow->img_gray, &opticflow->prev_img_gray);
  return true;
}
 
/*
 * Predict flow vectors by means of the rotation rates:
 */
static struct flow_t *predict_flow_vectors(struct flow_t *flow_vectors, uint16_t n_points, float phi_diff,
    float theta_diff, float psi_diff, struct opticflow_t *opticflow)
{
 
  // reserve memory for the predicted flow vectors:
  struct flow_t *predicted_flow_vectors = malloc(sizeof(struct flow_t) * n_points);
 
  float K[9] = {opticflow->camera->camera_intrinsics.focal_x, 0.0f, opticflow->camera->camera_intrinsics.center_x,
                0.0f, opticflow->camera->camera_intrinsics.focal_y, opticflow->camera->camera_intrinsics.center_y,
                0.0f, 0.0f, 1.0f
               };
  // TODO: make an option to not do distortion / undistortion (Dhane_k = 1)
  float k = opticflow->camera->camera_intrinsics.Dhane_k;
 
  float A, B, C; // as in Longuet-Higgins
 
  if (strcmp(opticflow->camera->dev_name, front_camera.dev_name) == 0) {
    // specific for the x,y swapped Bebop 2 images:
    A = -psi_diff;
    B = theta_diff;
    C = phi_diff;
  } else {
    A = theta_diff;
    B = phi_diff;
    C = psi_diff;
  }
 
  float x_n, y_n;
  float x_n_new, y_n_new, x_pix_new, y_pix_new;
  float predicted_flow_x, predicted_flow_y;
  for (uint16_t i = 0; i < n_points; i++) {
    // the from-coordinate is always the same:
    predicted_flow_vectors[i].pos.x = flow_vectors[i].pos.x;
    predicted_flow_vectors[i].pos.y = flow_vectors[i].pos.y;
 
    bool success = distorted_pixels_to_normalized_coords((float)flow_vectors[i].pos.x / opticflow->subpixel_factor,
                   (float)flow_vectors[i].pos.y / opticflow->subpixel_factor, &x_n, &y_n, k, K);
    if (success) {
      // predict flow as in a linear pinhole camera model:
      predicted_flow_x = A * x_n * y_n - B * x_n * x_n - B + C * y_n;
      predicted_flow_y = -C * x_n + A + A * y_n * y_n - B * x_n * y_n;
 
      x_n_new = x_n + predicted_flow_x;
      y_n_new = y_n + predicted_flow_y;
 
      success = normalized_coords_to_distorted_pixels(x_n_new, y_n_new, &x_pix_new, &y_pix_new, k, K);
 
      if (success) {
        predicted_flow_vectors[i].flow_x = (int16_t)(x_pix_new * opticflow->subpixel_factor - (float)flow_vectors[i].pos.x);
        predicted_flow_vectors[i].flow_y = (int16_t)(y_pix_new * opticflow->subpixel_factor - (float)flow_vectors[i].pos.y);
        predicted_flow_vectors[i].error = 0;
      } else {
        predicted_flow_vectors[i].flow_x = 0;
        predicted_flow_vectors[i].flow_y = 0;
        predicted_flow_vectors[i].error = LARGE_FLOW_ERROR;
      }
    } else {
      predicted_flow_vectors[i].flow_x = 0;
      predicted_flow_vectors[i].flow_y = 0;
      predicted_flow_vectors[i].error = LARGE_FLOW_ERROR;
    }
  }
  return predicted_flow_vectors;
}
 
 
/* manage_flow_features - Update list of corners to be tracked by LK
 * Remembers previous points and tries to find new points in less dense
 * areas of the image first.
 *
 */
static void manage_flow_features(struct image_t *img, struct opticflow_t *opticflow, struct opticflow_result_t *result)
{
  // first check if corners have not moved too close together due to flow:
  int16_t c1 = 0;
  while (c1 < (int16_t)result->corner_cnt - 1) {
    bool exists = false;
    for (int16_t i = c1 + 1; i < result->corner_cnt; i++) {
      if (abs((int16_t)opticflow->fast9_ret_corners[c1].x - (int16_t)opticflow->fast9_ret_corners[i].x) <
          opticflow->fast9_min_distance / 2
          && abs((int16_t)opticflow->fast9_ret_corners[c1].y - (int16_t)opticflow->fast9_ret_corners[i].y) <
          opticflow->fast9_min_distance / 2) {
        // if too close, replace the corner with the last one in the list:
        opticflow->fast9_ret_corners[c1].x = opticflow->fast9_ret_corners[result->corner_cnt - 1].x;
        opticflow->fast9_ret_corners[c1].y = opticflow->fast9_ret_corners[result->corner_cnt - 1].y;
        opticflow->fast9_ret_corners[c1].count = opticflow->fast9_ret_corners[result->corner_cnt - 1].count;
        opticflow->fast9_ret_corners[c1].x_sub = opticflow->fast9_ret_corners[result->corner_cnt - 1].x_sub;
        opticflow->fast9_ret_corners[c1].y_sub = opticflow->fast9_ret_corners[result->corner_cnt - 1].y_sub;
 
        // decrease the number of corners:
        result->corner_cnt--;
        exists = true;
        // no further checking required for the removed corner
        break;
      }
    }
    // if the corner has been replaced, the new corner in position c1 has to be checked again:
    if (!exists) { c1++; }
  }
 
  // no need for "per region" re-detection when there are no previous corners
  if ((!opticflow->fast9_region_detect) || (result->corner_cnt == 0)) {
    fast9_detect(&opticflow->prev_img_gray, opticflow->fast9_threshold, opticflow->fast9_min_distance,
                 opticflow->fast9_padding, opticflow->fast9_padding, &result->corner_cnt,
                 &opticflow->fast9_rsize,
                 &opticflow->fast9_ret_corners,
                 NULL);
  } else {
    // allocating memory and initializing the 2d array that holds the number of corners per region and its index (for the sorting)
    uint16_t **region_count = calloc(opticflow->fast9_num_regions, sizeof(uint16_t *));
    for (uint16_t i = 0; i < opticflow->fast9_num_regions; i++) {
      region_count[i] = calloc(2, sizeof(uint16_t));
      region_count[i][0] = 0;
      region_count[i][1] = i;
    }
    uint16_t root_regions = (uint16_t)sqrtf((float)opticflow->fast9_num_regions);
    int region_index;
    for (uint16_t i = 0; i < result->corner_cnt; i++) {
      region_index = (opticflow->fast9_ret_corners[i].x * root_regions / img->w
                      + root_regions * (opticflow->fast9_ret_corners[i].y * root_regions / img->h));
      region_index = (region_index < opticflow->fast9_num_regions) ? region_index : opticflow->fast9_num_regions - 1;
      region_count[region_index][0]++;
    }
 
    //sorting region_count array according to first column (number of corners).
    qsort(region_count, opticflow->fast9_num_regions, sizeof(region_count[0]), cmp_array);
 
    uint16_t roi[4];
    // Detecting corners from the region with the less to the one with the most, until a desired total is reached.
    for (uint16_t i = 0; i < opticflow->fast9_num_regions && result->corner_cnt < 2 * opticflow->max_track_corners; i++) {
      // Find the boundaries of the region of interest
      roi[0] = (region_count[i][1] % root_regions) * (img->w / root_regions);
      roi[1] = (region_count[i][1] / root_regions) * (img->h / root_regions);
      roi[2] = roi[0] + (img->w / root_regions);
      roi[3] = roi[1] + (img->h / root_regions);
 
      struct point_t *new_corners = calloc(opticflow->fast9_rsize, sizeof(struct point_t));
      uint16_t new_count = 0;
 
      fast9_detect(&opticflow->prev_img_gray, opticflow->fast9_threshold, opticflow->fast9_min_distance,
                   opticflow->fast9_padding, opticflow->fast9_padding, &new_count,
                   &opticflow->fast9_rsize, &new_corners, roi);
 
      // check that no identified points already exist in list
      for (uint16_t j = 0; j < new_count; j++) {
        bool exists = false;
        for (uint16_t k = 0; k < result->corner_cnt; k++) {
          if (abs((int16_t)new_corners[j].x - (int16_t)opticflow->fast9_ret_corners[k].x) < (int16_t)opticflow->fast9_min_distance
              && abs((int16_t)new_corners[j].y - (int16_t)opticflow->fast9_ret_corners[k].y) < (int16_t)
              opticflow->fast9_min_distance) {
            exists = true;
            break;
          }
        }
        if (!exists) {
          opticflow->fast9_ret_corners[result->corner_cnt].x = new_corners[j].x;
          opticflow->fast9_ret_corners[result->corner_cnt].y = new_corners[j].y;
          opticflow->fast9_ret_corners[result->corner_cnt].count = 0;
          opticflow->fast9_ret_corners[result->corner_cnt].x_sub = 0;
          opticflow->fast9_ret_corners[result->corner_cnt].y_sub = 0;
          result->corner_cnt++;
 
          if (result->corner_cnt >= opticflow->fast9_rsize) {
            break;
          }
        }
      }
 
      free(new_corners);
    }
    for (uint16_t i = 0; i < opticflow->fast9_num_regions; i++) {
      free(region_count[i]);
    }
    free(region_count);
  }
}
 
bool calc_edgeflow_tot(struct opticflow_t *opticflow, struct image_t *img,
                       struct opticflow_result_t *result)
{
  // Define Static Variables
  static struct edge_hist_t edge_hist[MAX_HORIZON];
  static uint8_t current_frame_nr = 0;
  struct edge_flow_t edgeflow;
  static uint8_t previous_frame_offset[2] = {1, 1};
 
  // Define Normal variables
  struct edgeflow_displacement_t displacement;
  displacement.x = calloc(img->w, sizeof(int32_t));
  displacement.y = calloc(img->h, sizeof(int32_t));
  // If the methods just switched to this one, reintialize the
  // array of edge_hist structure.
  if (opticflow->just_switched_method == 1 && edge_hist[0].x == NULL) {
    int i;
    for (i = 0; i < MAX_HORIZON; i++) {
      edge_hist[i].x = calloc(img->w, sizeof(int32_t));
      edge_hist[i].y = calloc(img->h, sizeof(int32_t));
      FLOAT_EULERS_ZERO(edge_hist[i].eulers);
    }
  }
  uint16_t disp_range;
  if (opticflow->search_distance < DISP_RANGE_MAX) {
    disp_range = opticflow->search_distance;
  } else {
    disp_range = DISP_RANGE_MAX;
  }
 
  uint16_t window_size;
 
  if (opticflow->window_size < MAX_WINDOW_SIZE) {
    window_size = opticflow->window_size;
  } else {
    window_size = MAX_WINDOW_SIZE;
  }
 
  uint16_t RES = opticflow->resolution_factor;
 
  //......................Calculating EdgeFlow..................... //
 
  // Calculate current frame's edge histogram
  int32_t *edge_hist_x = edge_hist[current_frame_nr].x;
  int32_t *edge_hist_y = edge_hist[current_frame_nr].y;
  calculate_edge_histogram(img, edge_hist_x, 'x', 0);
  calculate_edge_histogram(img, edge_hist_y, 'y', 0);
 
 
  // Copy frame time and angles of image to calculated edge histogram
  edge_hist[current_frame_nr].frame_time = img->ts;
  edge_hist[current_frame_nr].eulers = img->eulers;
 
  // Calculate which previous edge_hist to compare with the current
  uint8_t previous_frame_nr[2];
  calc_previous_frame_nr(result, opticflow, current_frame_nr, previous_frame_offset, previous_frame_nr);
 
  //Select edge histogram from the previous frame nr
  int32_t *prev_edge_histogram_x = edge_hist[previous_frame_nr[0]].x;
  int32_t *prev_edge_histogram_y = edge_hist[previous_frame_nr[1]].y;
 
  //Calculate the corresponding derotation of the two frames
  int16_t der_shift_x = 0;
  int16_t der_shift_y = 0;
  if (opticflow->derotation) {
    der_shift_x = (int16_t)((edge_hist[current_frame_nr].eulers.phi - edge_hist[previous_frame_nr[0]].eulers.phi) *
                            opticflow->camera->camera_intrinsics.focal_x * opticflow->derotation_correction_factor_x);
    der_shift_y = (int16_t)((edge_hist[current_frame_nr].eulers.theta - edge_hist[previous_frame_nr[1]].eulers.theta) *
                            opticflow->camera->camera_intrinsics.focal_y * opticflow->derotation_correction_factor_y);
  }
 
  // Estimate pixel wise displacement of the edge histograms for x and y direction
  calculate_edge_displacement(edge_hist_x, prev_edge_histogram_x,
                              displacement.x, img->w,
                              window_size, disp_range,  der_shift_x);
  calculate_edge_displacement(edge_hist_y, prev_edge_histogram_y,
                              displacement.y, img->h,
                              window_size, disp_range, der_shift_y);
 
  // Fit a line on the pixel displacement to estimate
  // the global pixel flow and divergence (RES is resolution)
  line_fit(displacement.x, &edgeflow.div_x,
           &edgeflow.flow_x, img->w,
           window_size + disp_range, RES);
  line_fit(displacement.y, &edgeflow.div_y,
           &edgeflow.flow_y, img->h,
           window_size + disp_range, RES);
 
  /* Save Resulting flow in results
   * Warning: The flow detected here is different in sign
   * and size, therefore this will be divided with
   * the same subpixel factor and multiplied by -1 to make it
   * on par with the LK algorithm in opticalflow_calculator.c
   * */
  edgeflow.flow_x = -1 * edgeflow.flow_x;
  edgeflow.flow_y = -1 * edgeflow.flow_y;
 
  edgeflow.flow_x = (int16_t)edgeflow.flow_x / previous_frame_offset[0];
  edgeflow.flow_y = (int16_t)edgeflow.flow_y / previous_frame_offset[1];
 
  result->flow_x = (int16_t)edgeflow.flow_x / RES;
  result->flow_y = (int16_t)edgeflow.flow_y / RES;
 
  //Fill up the results optic flow to be on par with LK_fast9
  result->flow_der_x =  result->flow_x;
  result->flow_der_y =  result->flow_y;
  result->corner_cnt = getAmountPeaks(edge_hist_x, 500, img->w);
  result->tracked_cnt = getAmountPeaks(edge_hist_x, 500, img->w);
  result->divergence = -1.0 * (float)edgeflow.div_x /
                       RES; // Also multiply the divergence with -1.0 to make it on par with the LK algorithm of
  result->div_size = result->divergence;  // Fill the div_size with the divergence to atleast get some divergenge measurement when switching from LK to EF
  result->camera_id = opticflow->id;
  result->surface_roughness = 0.0f;
  //......................Calculating VELOCITY ..................... //
 
  /*Estimate fps per direction
   * This is the fps with adaptive horizon for subpixel flow, which is not similar
   * to the loop speed of the algorithm. The faster the quadcopter flies
   * the higher it becomes
  */
  float fps_x = 0;
  float fps_y = 0;
  float time_diff_x = (float)(timeval_diff(&edge_hist[previous_frame_nr[0]].frame_time, &img->ts)) / 1000.;
  float time_diff_y = (float)(timeval_diff(&edge_hist[previous_frame_nr[1]].frame_time, &img->ts)) / 1000.;
  fps_x = 1 / (time_diff_x);
  fps_y = 1 / (time_diff_y);
 
  result->fps = fps_x;
 
  // TODO scale flow to rad/s here
 
  // Calculate velocity
  result->vel_cam.x = edgeflow.flow_x * fps_x * agl_dist_value_filtered * opticflow->camera->camera_intrinsics.focal_x /
                      RES;
  result->vel_cam.y = edgeflow.flow_y * fps_y * agl_dist_value_filtered * opticflow->camera->camera_intrinsics.focal_y /
                      RES;
  result->vel_cam.z = result->divergence * fps_x * agl_dist_value_filtered;
 
  //Apply a  median filter to the velocity if wanted
  if (opticflow->median_filter == true) {
    UpdateMedianFilterVect3Float(vel_filt, result->vel_cam);
  }
 
  result->noise_measurement = 0.2;
  if (opticflow->show_flow) {
    draw_edgeflow_img(img, edgeflow, prev_edge_histogram_x, edge_hist_x);
  }
  // Increment and wrap current time frame
  current_frame_nr = (current_frame_nr + 1) % MAX_HORIZON;
  // Free alloc'd variables
  free(displacement.x);
  free(displacement.y);
  return true;
}
 
 
bool opticflow_calc_frame(struct opticflow_t *opticflow, struct image_t *img,
                          struct opticflow_result_t *result)
{
  bool flow_successful = false;
  // A switch counter that checks in the loop if the current method is similar,
  // to the previous (for reinitializing structs)
  static int8_t switch_counter[2] = {-1, -1};
  if (switch_counter[opticflow->id] != opticflow->method) {
    opticflow->just_switched_method = true;
    switch_counter[opticflow->id] = opticflow->method;
    // Clear the static result
    memset(result, 0, sizeof(struct opticflow_result_t));
  } else {
    opticflow->just_switched_method = false;
  }
 
  // Switch between methods (0 = fast9/lukas-kanade, 1 = EdgeFlow)
  if (opticflow->method == 0) {
    flow_successful = calc_fast9_lukas_kanade(opticflow, img, result);
  } else if (opticflow->method == 1) {
    flow_successful = calc_edgeflow_tot(opticflow, img, result);
  }
  /* Rotate velocities from camera frame coordinates to body coordinates for control
  * IMPORTANT!!! This frame to body orientation should be the case for the Parrot
  * ARdrone and Bebop, however this can be different for other quadcopters
  * ALWAYS double check!
  */
  float_rmat_transp_vmult(&result->vel_body, &body_to_cam[opticflow->id], &result->vel_cam);
 
  return flow_successful;
}
 
static uint32_t timeval_diff(struct timeval *starttime, struct timeval *finishtime)
{
  uint32_t msec;
  msec = (finishtime->tv_sec - starttime->tv_sec) * 1000;
  msec += (finishtime->tv_usec - starttime->tv_usec) / 1000;
  return msec;
}
 
static int cmp_flow(const void *a, const void *b)
{
  const struct flow_t *a_p = (const struct flow_t *)a;
  const struct flow_t *b_p = (const struct flow_t *)b;
  return (a_p->flow_x * a_p->flow_x + a_p->flow_y * a_p->flow_y) - (b_p->flow_x * b_p->flow_x + b_p->flow_y *
         b_p->flow_y);
}
 
static int cmp_array(const void *a, const void *b)
{
  const uint16_t *pa = (const uint16_t *)a;
  const uint16_t *pb = (const uint16_t *)b;
  return pa[0] - pb[0];
}