lowpass.c

/*
  This file is part of darktable,
  Copyright (C) 2011-2023 darktable developers.

  darktable 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 3 of the License, or
  (at your option) any later version.

  darktable 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 darktable.  If not, see <http://www.gnu.org/licenses/>.
*/

#ifdef HAVE_CONFIG_H
#include "config.h"
#endif
#include "bauhaus/bauhaus.h"
#include "common/bilateral.h"
#include "common/bilateralcl.h"
#include "common/debug.h"
#include "common/gaussian.h"
#include "common/imagebuf.h"
#include "common/math.h"
#include "common/opencl.h"
#include "control/control.h"
#include "develop/develop.h"
#include "develop/imageop.h"
#include "develop/imageop_math.h"
#include "develop/imageop_gui.h"
#include "develop/tiling.h"
#include "gui/accelerators.h"
#include "gui/gtk.h"
#include "gui/presets.h"
#include "iop/iop_api.h"
#include <assert.h>
#include <gtk/gtk.h>
#include <stdlib.h>
#include <string.h>

#include <inttypes.h>

DT_MODULE_INTROSPECTION(4, dt_iop_lowpass_params_t)

typedef enum dt_iop_lowpass_algo_t
{
  LOWPASS_ALGO_GAUSSIAN, // $DESCRIPTION: "gaussian"
  LOWPASS_ALGO_BILATERAL // $DESCRIPTION: "bilateral filter"
} dt_iop_lowpass_algo_t;

typedef struct dt_iop_lowpass_params_t
{
  dt_gaussian_order_t order; // $DEFAULT: 0
  float radius;     // $MIN: 0.1 $MAX: 500.0 $DEFAULT: 10.0
  float contrast;   // $MIN: -3.0 $MAX: 3.0 $DEFAULT: 1.0
  float brightness; // $MIN: -3.0 $MAX: 3.0 $DEFAULT: 0.0
  float saturation; // $MIN: -3.0 $MAX: 3.0 $DEFAULT: 1.0
  dt_iop_lowpass_algo_t lowpass_algo; // $DEFAULT: LOWPASS_ALGO_GAUSSIAN $DESCRIPTION: "soften with"
  int unbound; // $DEFAULT: 1
} dt_iop_lowpass_params_t;


typedef struct dt_iop_lowpass_gui_data_t
{
  GtkWidget *radius;
  GtkWidget *contrast;
  GtkWidget *brightness;
  GtkWidget *saturation;
  GtkWidget *order;
  GtkWidget *lowpass_algo;
} dt_iop_lowpass_gui_data_t;

typedef struct dt_iop_lowpass_data_t
{
  dt_gaussian_order_t order;
  float radius;
  float contrast;
  float brightness;
  float saturation;
  dt_iop_lowpass_algo_t lowpass_algo;
  int unbound;
  float ctable[0x10000];      // precomputed look-up table for contrast curve
  float cunbounded_coeffs[3]; // approximation for extrapolation of contrast curve
  float ltable[0x10000];      // precomputed look-up table for brightness curve
  float lunbounded_coeffs[3]; // approximation for extrapolation of brightness curve
} dt_iop_lowpass_data_t;

typedef struct dt_iop_lowpass_global_data_t
{
  int kernel_lowpass_mix;
} dt_iop_lowpass_global_data_t;


const char *name()
{
  return _("lowpass");
}

const char **description(struct dt_iop_module_t *self)
{
  return dt_iop_set_description(self, _("isolate low frequencies in the image"),
                                      _("creative"),
                                      _("linear or non-linear, Lab, scene-referred"),
                                      _("frequential, Lab"),
                                      _("special, Lab, scene-referred"));
}

int flags()
{
  return IOP_FLAGS_INCLUDE_IN_STYLES | IOP_FLAGS_SUPPORTS_BLENDING | IOP_FLAGS_ALLOW_TILING;
}

int default_group()
{
  return IOP_GROUP_EFFECT | IOP_GROUP_EFFECTS;
}

dt_iop_colorspace_type_t default_colorspace(dt_iop_module_t *self,
                                            dt_dev_pixelpipe_t *pipe,
                                            dt_dev_pixelpipe_iop_t *piece)
{
  return IOP_CS_LAB;
}

int legacy_params(dt_iop_module_t *self,
                  const void *const old_params,
                  const int old_version,
                  void **new_params,
                  int32_t *new_params_size,
                  int *new_version)
{
  typedef struct dt_iop_lowpass_params_v4_t
  {
    dt_gaussian_order_t order;
    float radius;
    float contrast;
    float brightness;
    float saturation;
    dt_iop_lowpass_algo_t lowpass_algo;
    int unbound;
  } dt_iop_lowpass_params_v4_t;

  if(old_version == 1)
  {
    typedef struct dt_iop_lowpass_params_v1_t
    {
      dt_gaussian_order_t order;
      float radius;
      float contrast;
      float saturation;
    } dt_iop_lowpass_params_v1_t;

    const dt_iop_lowpass_params_v1_t *old = old_params;
    dt_iop_lowpass_params_v4_t *new =
      (dt_iop_lowpass_params_v4_t *)malloc(sizeof(dt_iop_lowpass_params_v4_t));
    new->order = old->order;
    new->radius = fabs(old->radius);
    new->contrast = old->contrast;
    new->saturation = old->saturation;
    new->brightness = 0.0f;
    new->lowpass_algo = old->radius < 0.0f ? LOWPASS_ALGO_BILATERAL : LOWPASS_ALGO_GAUSSIAN;
    new->unbound = 0;

    *new_params = new;
    *new_params_size = sizeof(dt_iop_lowpass_params_v4_t);
    *new_version = 4;
    return 0;
  }
  if(old_version == 2)
  {
    typedef struct dt_iop_lowpass_params_v2_t
    {
      dt_gaussian_order_t order;
      float radius;
      float contrast;
      float brightness;
      float saturation;
    } dt_iop_lowpass_params_v2_t;

    const dt_iop_lowpass_params_v2_t *old = old_params;
    dt_iop_lowpass_params_v4_t *new =
      (dt_iop_lowpass_params_v4_t *)malloc(sizeof(dt_iop_lowpass_params_v4_t));
    new->order = old->order;
    new->radius = fabs(old->radius);
    new->contrast = old->contrast;
    new->saturation = old->saturation;
    new->brightness = old->brightness;
    new->lowpass_algo = old->radius < 0.0f ? LOWPASS_ALGO_BILATERAL : LOWPASS_ALGO_GAUSSIAN;
    new->unbound = 0;

    *new_params = new;
    *new_params_size = sizeof(dt_iop_lowpass_params_v4_t);
    *new_version = 4;
    return 0;
  }
  if(old_version == 3)
  {
    typedef struct dt_iop_lowpass_params_v3_t
    {
      dt_gaussian_order_t order;
      float radius;
      float contrast;
      float brightness;
      float saturation;
      int unbound;
    } dt_iop_lowpass_params_v3_t;

    const dt_iop_lowpass_params_v3_t *old = old_params;
    dt_iop_lowpass_params_v4_t *new =
      (dt_iop_lowpass_params_v4_t *)malloc(sizeof(dt_iop_lowpass_params_v4_t));
    new->order = old->order;
    new->radius = fabs(old->radius);
    new->contrast = old->contrast;
    new->saturation = old->saturation;
    new->brightness = old->brightness;
    new->lowpass_algo = old->radius < 0.0f ? LOWPASS_ALGO_BILATERAL : LOWPASS_ALGO_GAUSSIAN;
    new->unbound = old->unbound;

    *new_params = new;
    *new_params_size = sizeof(dt_iop_lowpass_params_v4_t);
    *new_version = 4;
    return 0;
  }
  return 1;
}


#ifdef HAVE_OPENCL
int process_cl(struct dt_iop_module_t *self,
               dt_dev_pixelpipe_iop_t *piece,
               cl_mem dev_in,
               cl_mem dev_out,
               const dt_iop_roi_t *const roi_in,
               const dt_iop_roi_t *const roi_out)
{
  dt_iop_lowpass_data_t *d = (dt_iop_lowpass_data_t *)piece->data;
  dt_iop_lowpass_global_data_t *gd = (dt_iop_lowpass_global_data_t *)self->global_data;

  cl_int err = DT_OPENCL_DEFAULT_ERROR;
  const int devid = piece->pipe->devid;

  const int width = roi_in->width;
  const int height = roi_in->height;
  const int channels = piece->colors;

  const float radius = fmax(0.1f, d->radius);
  const float sigma = radius * roi_in->scale / piece->iscale;
  const float saturation = d->saturation;
  const int order = d->order;
  const int unbound = d->unbound;

  cl_mem dev_cm = NULL;
  cl_mem dev_ccoeffs = NULL;
  cl_mem dev_lm = NULL;
  cl_mem dev_lcoeffs = NULL;
  cl_mem dev_tmp = NULL;

  dt_gaussian_cl_t *g = NULL;
  dt_bilateral_cl_t *b = NULL;

  float Labmax[] = { 100.0f, 128.0f, 128.0f, 1.0f };
  float Labmin[] = { 0.0f, -128.0f, -128.0f, 0.0f };

  if(unbound)
  {
    for(int k = 0; k < 4; k++) Labmax[k] = FLT_MAX;
    for(int k = 0; k < 4; k++) Labmin[k] = -FLT_MAX;
  }

  if(d->lowpass_algo == LOWPASS_ALGO_GAUSSIAN)
  {
    g = dt_gaussian_init_cl(devid, width, height, channels, Labmax, Labmin, sigma, order);
    if(!g) goto error;
    err = dt_gaussian_blur_cl(g, dev_in, dev_out);
    if(err != CL_SUCCESS) goto error;
    dt_gaussian_free_cl(g);
    g = NULL;
  }
  else
  {
    const float sigma_r = 100.0f; // does not depend on scale
    const float sigma_s = sigma;
    const float detail = -1.0f; // we want the bilateral base layer

    b = dt_bilateral_init_cl(devid, width, height, sigma_s, sigma_r);
    if(!b) goto error;
    err = dt_bilateral_splat_cl(b, dev_in);
    if(err != CL_SUCCESS) goto error;
    err = dt_bilateral_blur_cl(b);
    if(err != CL_SUCCESS) goto error;
    err = dt_bilateral_slice_cl(b, dev_in, dev_out, detail);
    if(err != CL_SUCCESS) goto error;
    dt_bilateral_free_cl(b);
    b = NULL; // make sure we don't clean it up twice
  }

  err = DT_OPENCL_SYSMEM_ALLOCATION;
  dev_tmp = dt_opencl_alloc_device(devid, width, height, sizeof(float) * 4);
  if(dev_tmp == NULL) goto error;

  dev_cm = dt_opencl_copy_host_to_device(devid, d->ctable, 256, 256, sizeof(float));
  if(dev_cm == NULL) goto error;

  dev_ccoeffs = dt_opencl_copy_host_to_device_constant(devid, sizeof(float) * 3, d->cunbounded_coeffs);
  if(dev_ccoeffs == NULL) goto error;

  dev_lm = dt_opencl_copy_host_to_device(devid, d->ltable, 256, 256, sizeof(float));
  if(dev_lm == NULL) goto error;

  dev_lcoeffs = dt_opencl_copy_host_to_device_constant(devid, sizeof(float) * 3, d->lunbounded_coeffs);
  if(dev_lcoeffs == NULL) goto error;

  size_t origin[] = { 0, 0, 0 };
  size_t region[] = { width, height, 1 };
  err = dt_opencl_enqueue_copy_image(devid, dev_out, dev_tmp, origin, origin, region);
  if(err != CL_SUCCESS) goto error;

  err = dt_opencl_enqueue_kernel_2d_args(devid, gd->kernel_lowpass_mix, width, height,
    CLARG(dev_tmp), CLARG(dev_out), CLARG(width), CLARG(height), CLARG(saturation), CLARG(dev_cm),
    CLARG(dev_ccoeffs), CLARG(dev_lm), CLARG(dev_lcoeffs), CLARG(unbound));

error:
  if(g) dt_gaussian_free_cl(g);
  if(b) dt_bilateral_free_cl(b);

  dt_opencl_release_mem_object(dev_tmp);
  dt_opencl_release_mem_object(dev_lcoeffs);
  dt_opencl_release_mem_object(dev_lm);
  dt_opencl_release_mem_object(dev_ccoeffs);
  dt_opencl_release_mem_object(dev_cm);
  return err;
}
#endif

void tiling_callback(struct dt_iop_module_t *self,
                     struct dt_dev_pixelpipe_iop_t *piece,
                     const dt_iop_roi_t *roi_in,
                     const dt_iop_roi_t *roi_out,
                     struct dt_develop_tiling_t *tiling)
{
  dt_iop_lowpass_data_t *d = (dt_iop_lowpass_data_t *)piece->data;

  const float radius = fmax(0.1f, d->radius);
  const float sigma = radius * roi_in->scale / piece->iscale;
  const float sigma_r = 100.0f; // does not depend on scale
  const float sigma_s = sigma;

  const int width = roi_in->width;
  const int height = roi_in->height;
  const int channels = piece->colors;

  const size_t basebuffer = sizeof(float) * channels * width * height;

  if(d->lowpass_algo == LOWPASS_ALGO_BILATERAL)
  {
    // bilateral filter
    tiling->factor = 2.0f + fmax(1.0f, (float)dt_bilateral_memory_use(width, height, sigma_s, sigma_r) / basebuffer);
    tiling->maxbuf
        = fmax(1.0f, (float)dt_bilateral_singlebuffer_size(width, height, sigma_s, sigma_r) / basebuffer);
  }
  else
  {
    // gaussian blur
    tiling->factor = 2.0f + fmax(1.0f, (float)dt_gaussian_memory_use(width, height, channels) / basebuffer);
#ifdef HAVE_OPENCL
    tiling->factor_cl = 2.0f + fmax(1.0f, (float)dt_gaussian_memory_use_cl(width, height, channels) / basebuffer);
#endif
    tiling->maxbuf = fmax(1.0f, (float)dt_gaussian_singlebuffer_size(width, height, channels) / basebuffer);
  }
  tiling->overhead = 0;
  tiling->overlap = ceilf(4 * sigma);
  tiling->xalign = 1;
  tiling->yalign = 1;
  return;
}

void process(struct dt_iop_module_t *self,
             dt_dev_pixelpipe_iop_t *piece,
             const void *const ivoid,
             void *const ovoid,
             const dt_iop_roi_t *const roi_in,
             const dt_iop_roi_t *const roi_out)
{
  if(!dt_iop_have_required_input_format(4 /*we need full-color pixels*/, self, piece->colors,
                                        ivoid, ovoid, roi_in, roi_out))
    return;

  dt_iop_lowpass_data_t *data = (dt_iop_lowpass_data_t *)piece->data;
  const float *const restrict in = (float *)ivoid;
  float *const out = (float *)ovoid;

  const size_t width = roi_in->width;
  const size_t height = roi_in->height;

  const float radius = fmax(0.1f, data->radius);
  const float sigma = radius * roi_in->scale / piece->iscale;
  const int order = data->order;
  const int unbound = data->unbound;

  dt_aligned_pixel_t Labmax = { 100.0f, 128.0f, 128.0f, 1.0f };
  dt_aligned_pixel_t Labmin = { 0.0f, -128.0f, -128.0f, 0.0f };

  if(unbound)
  {
    for_four_channels(c)
    {
      Labmax[c] = FLT_MAX;
      Labmin[c] = -FLT_MAX;
    }
  }

  if(data->lowpass_algo == LOWPASS_ALGO_GAUSSIAN)
  {
    dt_gaussian_t *g = dt_gaussian_init(width, height, 4, Labmax, Labmin, sigma, order);
    if(!g)
    {
      dt_iop_copy_image_roi(out, in, piece->colors, roi_in, roi_out);
      return;
    }
    dt_gaussian_blur_4c(g, in, out);
    dt_gaussian_free(g);
  }
  else
  {
    const float sigma_r = 100.0f; // d->sigma_r; // does not depend on scale
    const float sigma_s = sigma;
    const float detail = -1.0f; // we want the bilateral base layer

    dt_bilateral_t *b = dt_bilateral_init(width, height, sigma_s, sigma_r);
    if(!b)
    {
      dt_iop_copy_image_roi(out, in, piece->colors, roi_in, roi_out);
      return;
    }
    dt_bilateral_splat(b, in);
    dt_bilateral_blur(b);
    dt_bilateral_slice(b, in, out, detail);
    dt_bilateral_free(b);
  }

  const size_t npixels = width * height;
  const float saturation = data->saturation;

#ifdef _OPENMP
#pragma omp parallel for default(none) \
  dt_omp_firstprivate(npixels, Labmax, Labmin, in, out, data, saturation) \
  schedule(static)
#endif
  for(size_t k = 0; k < 4*npixels; k += 4)
  {
    // apply contrast and brightness curves to L channel
    out[k + 0] = (out[k + 0] < 100.0f)
                      ? data->ctable[CLAMP((int)(out[k + 0] / 100.0f * 0x10000ul), 0, 0xffff)]
                      : dt_iop_eval_exp(data->cunbounded_coeffs, out[k + 0] / 100.0f);
    out[k + 0] = (out[k + 0] < 100.0f)
                      ? data->ltable[CLAMP((int)(out[k + 0] / 100.0f * 0x10000ul), 0, 0xffff)]
                      : dt_iop_eval_exp(data->lunbounded_coeffs, out[k + 0] / 100.0f);
    // the following will not clip in unbound case (see definition of Labmax/Labmin)
    out[k + 1] = CLAMPF(out[k + 1] * saturation, Labmin[1], Labmax[1]);
    out[k + 2] = CLAMPF(out[k + 2] * saturation, Labmin[2], Labmax[2]);
    // copy alpha channel to output
    out[k + 3] = in[k + 3];
  }
}

void commit_params(struct dt_iop_module_t *self,
                   dt_iop_params_t *p1,
                   dt_dev_pixelpipe_t *pipe,
                   dt_dev_pixelpipe_iop_t *piece)
{
  dt_iop_lowpass_params_t *p = (dt_iop_lowpass_params_t *)p1;
  dt_iop_lowpass_data_t *d = (dt_iop_lowpass_data_t *)piece->data;
  d->order = p->order;
  d->radius = p->radius;
  d->contrast = p->contrast;
  d->brightness = p->brightness;
  d->saturation = p->saturation;
  d->lowpass_algo = p->lowpass_algo;
  d->unbound = p->unbound;

#ifdef HAVE_OPENCL
  if(d->lowpass_algo == LOWPASS_ALGO_BILATERAL)
    piece->process_cl_ready = (piece->process_cl_ready && !dt_opencl_avoid_atomics(pipe->devid));
#endif


  // generate precomputed contrast curve
  if(fabs(d->contrast) <= 1.0f)
  {
    // linear curve for contrast up to +/- 1
    for(int k = 0; k < 0x10000; k++) d->ctable[k] = d->contrast * (100.0f * k / 0x10000 - 50.0f) + 50.0f;
  }
  else
  {
    // sigmoidal curve for contrast above +/-1 1
    // going from (0,0) to (1,100) or (0,100) to (1,0), respectively
    const float boost = 5.0f;
    const float contrastm1sq = boost * (fabs(d->contrast) - 1.0f) * (fabs(d->contrast) - 1.0f);
    const float contrastscale = copysign(sqrtf(1.0f + contrastm1sq), d->contrast);
    float *const ctable = d->ctable;
#ifdef _OPENMP
#pragma omp parallel for default(none) \
    dt_omp_firstprivate(contrastm1sq, contrastscale, ctable)      \
    schedule(static)
#endif
    for(size_t k = 0; k < 0x10000; k++)
    {
      const float kx2m1 = 2.0f * (float)k / 0x10000 - 1.0f;
      ctable[k] = 50.0f * (contrastscale * kx2m1 / sqrtf(1.0f + contrastm1sq * kx2m1 * kx2m1) + 1.0f);
    }
  }

  // now the extrapolation stuff for the contrast curve:
  const float xc[4] = { 0.7f, 0.8f, 0.9f, 1.0f };
  const float yc[4] = { d->ctable[CLAMP((int)(xc[0] * 0x10000ul), 0, 0xffff)],
                        d->ctable[CLAMP((int)(xc[1] * 0x10000ul), 0, 0xffff)],
                        d->ctable[CLAMP((int)(xc[2] * 0x10000ul), 0, 0xffff)],
                        d->ctable[CLAMP((int)(xc[3] * 0x10000ul), 0, 0xffff)] };
  dt_iop_estimate_exp(xc, yc, 4, d->cunbounded_coeffs);


  // generate precomputed brightness curve
  const float gamma = (d->brightness >= 0.0f) ? 1.0f / (1.0f + d->brightness) : (1.0f - d->brightness);

  float *const ltable = d->ltable;
#ifdef _OPENMP
#pragma omp parallel for default(none) \
  dt_omp_firstprivate(gamma, ltable)          \
  schedule(static)
#endif
  for(size_t k = 0; k < 0x10000; k++)
  {
    ltable[k] = 100.0f * powf((float)k / 0x10000, gamma);
  }

  // now the extrapolation stuff for the brightness curve:
  const float xl[4] = { 0.7f, 0.8f, 0.9f, 1.0f };
  const float yl[4] = { d->ltable[CLAMP((int)(xl[0] * 0x10000ul), 0, 0xffff)],
                        d->ltable[CLAMP((int)(xl[1] * 0x10000ul), 0, 0xffff)],
                        d->ltable[CLAMP((int)(xl[2] * 0x10000ul), 0, 0xffff)],
                        d->ltable[CLAMP((int)(xl[3] * 0x10000ul), 0, 0xffff)] };
  dt_iop_estimate_exp(xl, yl, 4, d->lunbounded_coeffs);
}

void init_pipe(struct dt_iop_module_t *self,
               dt_dev_pixelpipe_t *pipe,
               dt_dev_pixelpipe_iop_t *piece)
{
  dt_iop_lowpass_data_t *d = (dt_iop_lowpass_data_t *)calloc(1, sizeof(dt_iop_lowpass_data_t));
  piece->data = (void *)d;
  for(int k = 0; k < 0x10000; k++) d->ctable[k] = d->ltable[k] = 100.0f * k / 0x10000; // identity
}

void cleanup_pipe(struct dt_iop_module_t *self,
                  dt_dev_pixelpipe_t *pipe,
                  dt_dev_pixelpipe_iop_t *piece)
{
  free(piece->data);
  piece->data = NULL;
}

void init_global(dt_iop_module_so_t *module)
{
  const int program = 6; // gaussian.cl, from programs.conf
  dt_iop_lowpass_global_data_t *gd
      = (dt_iop_lowpass_global_data_t *)malloc(sizeof(dt_iop_lowpass_global_data_t));
  module->data = gd;
  gd->kernel_lowpass_mix = dt_opencl_create_kernel(program, "lowpass_mix");
}

void init_presets(dt_iop_module_so_t *self)
{
  dt_database_start_transaction(darktable.db);

  dt_gui_presets_add_generic(_("local contrast mask"), self->op, self->version(),
                             &(dt_iop_lowpass_params_t){ 0, 50.0f, -1.0f, 0.0f, 0.0f, LOWPASS_ALGO_GAUSSIAN, 1 },
                             sizeof(dt_iop_lowpass_params_t), 1, DEVELOP_BLEND_CS_RGB_DISPLAY);

  dt_database_release_transaction(darktable.db);
}

void cleanup_global(dt_iop_module_so_t *module)
{
  dt_iop_lowpass_global_data_t *gd = (dt_iop_lowpass_global_data_t *)module->data;
  dt_opencl_free_kernel(gd->kernel_lowpass_mix);
  free(module->data);
  module->data = NULL;
}

void gui_init(struct dt_iop_module_t *self)
{
  dt_iop_lowpass_gui_data_t *g = IOP_GUI_ALLOC(lowpass);

  g->radius = dt_bauhaus_slider_from_params(self, N_("radius"));
  g->lowpass_algo = dt_bauhaus_combobox_from_params(self, "lowpass_algo");
  g->contrast = dt_bauhaus_slider_from_params(self, N_("contrast"));
  g->brightness = dt_bauhaus_slider_from_params(self, N_("brightness"));
  g->saturation = dt_bauhaus_slider_from_params(self, N_("saturation"));

  gtk_widget_set_tooltip_text(g->radius, _("radius of gaussian/bilateral blur"));
  gtk_widget_set_tooltip_text(g->contrast, _("contrast of lowpass filter"));
  gtk_widget_set_tooltip_text(g->brightness, _("brightness adjustment of lowpass filter"));
  gtk_widget_set_tooltip_text(g->saturation, _("color saturation of lowpass filter"));
  gtk_widget_set_tooltip_text(g->lowpass_algo, _("which filter to use for blurring"));
}

// clang-format off
// modelines: These editor modelines have been set for all relevant files by tools/update_modelines.py
// vim: shiftwidth=2 expandtab tabstop=2 cindent
// kate: tab-indents: off; indent-width 2; replace-tabs on; indent-mode cstyle; remove-trailing-spaces modified;
// clang-format on