/* crop an image down to a specified size by removing boring parts
 *
 * Adapted from sharp's smartcrop feature, with kind permission.
 *
 * 1/3/17
 * 	- first version, from sharp
 * 14/3/17
 * 	- revised attention smartcrop
 * 8/6/17
 * 	- revised again
 * 15/9/18 lovell
 * 	- move shrink to start of processing
 * 22/9/18 jcupitt
 * 	- add low and high
 * 19/3/20 jcupitt
 * 	- add all
 * 26/11/22 ejoebstl
 *  - expose location of interest when using attention based cropping
 */

/*

	This file is part of VIPS.

	VIPS is free software; you can redistribute it and/or modify
	it under the terms of the GNU Lesser General Public License as published by
	the Free Software Foundation; either version 2 of the License, or
	(at your option) any later version.

	This program 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 Lesser General Public License for more details.

	You should have received a copy of the GNU Lesser General Public License
	along with this program; if not, write to the Free Software
	Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA
	02110-1301  USA

 */

/*

	These files are distributed with VIPS - http://www.vips.ecs.soton.ac.uk

 */

/*
#define VIPS_DEBUG
 */

#ifdef HAVE_CONFIG_H
#include <config.h>
#endif /*HAVE_CONFIG_H*/
#include <glib/gi18n-lib.h>

#include <stdio.h>
#include <string.h>
#include <stdlib.h>

#include <vips/vips.h>
#include <vips/debug.h>

#include "pconversion.h"

#include "bandary.h"

typedef struct _VipsSmartcrop {
	VipsConversion parent_instance;

	VipsImage *in;
	int width;
	int height;
	VipsInteresting interesting;
	gboolean premultiplied;

	int attention_x;
	int attention_y;

} VipsSmartcrop;

typedef VipsConversionClass VipsSmartcropClass;

G_DEFINE_TYPE(VipsSmartcrop, vips_smartcrop, VIPS_TYPE_CONVERSION);

static int
vips_smartcrop_score(VipsSmartcrop *smartcrop, VipsImage *in,
	int left, int top, int width, int height, double *score)
{
	VipsImage **t = (VipsImage **)
		vips_object_local_array(VIPS_OBJECT(smartcrop), 2);

	if (vips_extract_area(in, &t[0], left, top, width, height, NULL) ||
		vips_hist_find(t[0], &t[1], NULL) ||
		vips_hist_entropy(t[1], score, NULL))
		return -1;

	return 0;
}

/* Entropy-style smartcrop. Repeatedly discard low interest areas. This should
 * be faster for very large images.
 */
static int
vips_smartcrop_entropy(VipsSmartcrop *smartcrop,
	VipsImage *in, int *left, int *top)
{
	int max_slice_size;
	int width;
	int height;

	*left = 0;
	*top = 0;
	width = in->Xsize;
	height = in->Ysize;

	/* How much do we trim by each iteration? Aim for 8 steps in the axis
	 * that needs trimming most.
	 */
	max_slice_size = VIPS_MAX(
		ceil((width - smartcrop->width) / 8.0),
		ceil((height - smartcrop->height) / 8.0));

	/* Repeatedly take a slice off width and height until we
	 * reach the target.
	 */
	while (width > smartcrop->width ||
		height > smartcrop->height) {
		const int slice_width =
			VIPS_MIN(width - smartcrop->width, max_slice_size);
		const int slice_height =
			VIPS_MIN(height - smartcrop->height, max_slice_size);

		if (slice_width > 0) {
			double left_score;
			double right_score;

			if (vips_smartcrop_score(smartcrop, in,
					*left, *top,
					slice_width, height, &left_score))
				return -1;

			if (vips_smartcrop_score(smartcrop, in,
					*left + width - slice_width, *top,
					slice_width, height, &right_score))
				return -1;

			width -= slice_width;
			if (left_score < right_score)
				*left += slice_width;
		}

		if (slice_height > 0) {
			double top_score;
			double bottom_score;

			if (vips_smartcrop_score(smartcrop, in,
					*left, *top,
					width, slice_height, &top_score))
				return -1;

			if (vips_smartcrop_score(smartcrop, in,
					*left, *top + height - slice_height,
					width, slice_height, &bottom_score))
				return -1;

			height -= slice_height;
			if (top_score < bottom_score)
				*top += slice_height;
		}
	}

	return 0;
}

/* Calculate sqrt(b1^2 + b2^2 ...)
 */
static int
pythagoras(VipsSmartcrop *smartcrop, VipsImage *in, VipsImage **out)
{
	VipsImage **t = (VipsImage **)
		vips_object_local_array(VIPS_OBJECT(smartcrop),
			2 * in->Bands + 1);

	int i;

	for (i = 0; i < in->Bands; i++)
		if (vips_extract_band(in, &t[i], i, NULL))
			return -1;

	for (i = 0; i < in->Bands; i++)
		if (vips_multiply(t[i], t[i], &t[i + in->Bands], NULL))
			return -1;

	if (vips_sum(&t[in->Bands], &t[2 * in->Bands], in->Bands, NULL) ||
		vips_pow_const1(t[2 * in->Bands], out, 0.5, NULL))
		return -1;

	return 0;
}

static int
vips_smartcrop_attention(VipsSmartcrop *smartcrop,
	VipsImage *in, int *left, int *top, int *attention_x, int *attention_y)
{
	/* From smartcrop.js.
	 */
	static double skin_vector[] = { -0.78, -0.57, -0.44 };
	static double ones[] = { 1.0, 1.0, 1.0 };

	VipsImage **t = (VipsImage **)
		vips_object_local_array(VIPS_OBJECT(smartcrop), 24);

	double hscale;
	double vscale;
	double sigma;
	double max;
	int x_pos;
	int y_pos;

	/* The size we shrink to gives the precision with which we can place
	 * the crop
	 */
	hscale = 32.0 / in->Xsize;
	vscale = 32.0 / in->Ysize;
	sigma = sqrt(pow(smartcrop->width * hscale, 2) +
		pow(smartcrop->height * vscale, 2));
	sigma = VIPS_MAX(sigma / 10, 1.0);

	if (vips_resize(in, &t[17], hscale,
			"vscale", vscale,
			NULL))
		return -1;

	/* Simple edge detect.
	 */
	if (!(t[21] = vips_image_new_matrixv(3, 3,
			  0.0, -1.0, 0.0,
			  -1.0, 4.0, -1.0,
			  0.0, -1.0, 0.0)))
		return -1;

	/* Convert to XYZ and just use the first three bands.
	 */
	if (vips_colourspace(t[17], &t[0], VIPS_INTERPRETATION_XYZ, NULL) ||
		vips_extract_band(t[0], &t[1], 0, "n", 3, NULL))
		return -1;

	/* Edge detect on Y.
	 */
	if (vips_extract_band(t[1], &t[2], 1, NULL) ||
		vips_conv(t[2], &t[3], t[21],
			"precision", VIPS_PRECISION_INTEGER,
			NULL) ||
		vips_linear1(t[3], &t[4], 5.0, 0.0, NULL) ||
		vips_abs(t[4], &t[14], NULL))
		return -1;

	/* Look for skin colours. Taken from smartcrop.js.
	 */
	if (
		/* Normalise to magnitude of colour in XYZ.
		 */
		pythagoras(smartcrop, t[1], &t[5]) ||
		vips_divide(t[1], t[5], &t[6], NULL) ||

		/* Distance from skin point.
		 */
		vips_linear(t[6], &t[7], ones, skin_vector, 3, NULL) ||
		pythagoras(smartcrop, t[7], &t[8]) ||

		/* Rescale to 100 - 0 score.
		 */
		vips_linear1(t[8], &t[9], -100.0, 100.0, NULL) ||

		/* Ignore dark areas.
		 */
		vips_more_const1(t[2], &t[10], 5.0, NULL) ||
		!(t[11] = vips_image_new_from_image1(t[10], 0.0)) ||
		vips_ifthenelse(t[10], t[9], t[11], &t[15], NULL))
		return -1;

	/* Look for saturated areas.
	 */
	if (vips_colourspace(t[1], &t[12],
			VIPS_INTERPRETATION_LAB, NULL) ||
		vips_extract_band(t[12], &t[13], 1, NULL) ||
		vips_ifthenelse(t[10], t[13], t[11], &t[16], NULL))
		return -1;

	/* Sum, blur and find maxpos.
	 *
	 * The amount of blur is related to the size of the crop
	 * area: how large an area we want to consider for the scoring
	 * function.
	 */

	if (vips_sum(&t[14], &t[18], 3, NULL) ||
		vips_gaussblur(t[18], &t[19], sigma, NULL) ||
		vips_max(t[19], &max, "x", &x_pos, "y", &y_pos, NULL))
		return -1;

	/* Transform back into image coordinates.
	 */
	*attention_x = x_pos / hscale;
	*attention_y = y_pos / vscale;

	/* Centre the crop over the max.
	 */
	*left = VIPS_CLIP(0,
		*attention_x - smartcrop->width / 2,
		in->Xsize - smartcrop->width);
	*top = VIPS_CLIP(0,
		*attention_y - smartcrop->height / 2,
		in->Ysize - smartcrop->height);

	return 0;
}

static int
vips_smartcrop_build(VipsObject *object)
{
	VipsObjectClass *class = VIPS_OBJECT_GET_CLASS(object);
	VipsConversion *conversion = VIPS_CONVERSION(object);
	VipsSmartcrop *smartcrop = (VipsSmartcrop *) object;
	VipsImage **t = (VipsImage **) vips_object_local_array(object, 2);

	VipsImage *in;
	int left;
	int top;

	int attention_x = 0;
	int attention_y = 0;

	if (VIPS_OBJECT_CLASS(vips_smartcrop_parent_class)->build(object))
		return -1;

	if (smartcrop->width > smartcrop->in->Xsize ||
		smartcrop->height > smartcrop->in->Ysize ||
		smartcrop->width <= 0 || smartcrop->height <= 0) {
		vips_error(class->nickname, "%s", _("bad extract area"));
		return -1;
	}

	in = smartcrop->in;

	/* If there's an alpha, we have to premultiply before searching for
	 * content. There could be stuff in transparent areas which we don't
	 * want to consider.
	 */
	if (vips_image_hasalpha(in) && !smartcrop->premultiplied) {
		if (vips_premultiply(in, &t[0], NULL))
			return -1;
		in = t[0];
	}

	switch (smartcrop->interesting) {
	case VIPS_INTERESTING_NONE:
	case VIPS_INTERESTING_LOW:
		left = 0;
		top = 0;
		break;

	case VIPS_INTERESTING_CENTRE:
		left = (in->Xsize - smartcrop->width) / 2;
		top = (in->Ysize - smartcrop->height) / 2;
		break;

	case VIPS_INTERESTING_ENTROPY:
		if (vips_smartcrop_entropy(smartcrop, in, &left, &top))
			return -1;
		break;

	case VIPS_INTERESTING_ATTENTION:
		if (vips_smartcrop_attention(smartcrop, in,
				&left, &top,
				&attention_x, &attention_y))
			return -1;
		break;

	case VIPS_INTERESTING_HIGH:
		left = in->Xsize - smartcrop->width;
		top = in->Ysize - smartcrop->height;
		break;

	case VIPS_INTERESTING_ALL:
		left = 0;
		top = 0;
		smartcrop->width = in->Xsize;
		smartcrop->height = in->Ysize;
		break;

	default:
		g_assert_not_reached();

		/* Stop a compiler warning.
		 */
		left = 0;
		top = 0;
		break;
	}

	g_object_set(smartcrop,
		"attention_x", attention_x,
		"attention_y", attention_y,
		NULL);

	if (vips_extract_area(smartcrop->in, &t[1],
			left, top,
			smartcrop->width, smartcrop->height, NULL) ||
		vips_image_write(t[1], conversion->out))
		return -1;

	return 0;
}

static void
vips_smartcrop_class_init(VipsSmartcropClass *class)
{
	GObjectClass *gobject_class = G_OBJECT_CLASS(class);
	VipsObjectClass *vobject_class = VIPS_OBJECT_CLASS(class);

	VIPS_DEBUG_MSG("vips_smartcrop_class_init\n");

	gobject_class->set_property = vips_object_set_property;
	gobject_class->get_property = vips_object_get_property;

	vobject_class->nickname = "smartcrop";
	vobject_class->description = _("extract an area from an image");
	vobject_class->build = vips_smartcrop_build;

	VIPS_ARG_IMAGE(class, "input", 0,
		_("Input"),
		_("Input image"),
		VIPS_ARGUMENT_REQUIRED_INPUT,
		G_STRUCT_OFFSET(VipsSmartcrop, in));

	VIPS_ARG_INT(class, "width", 4,
		_("Width"),
		_("Width of extract area"),
		VIPS_ARGUMENT_REQUIRED_INPUT,
		G_STRUCT_OFFSET(VipsSmartcrop, width),
		1, VIPS_MAX_COORD, 1);

	VIPS_ARG_INT(class, "height", 5,
		_("Height"),
		_("Height of extract area"),
		VIPS_ARGUMENT_REQUIRED_INPUT,
		G_STRUCT_OFFSET(VipsSmartcrop, height),
		1, VIPS_MAX_COORD, 1);

	VIPS_ARG_ENUM(class, "interesting", 6,
		_("Interesting"),
		_("How to measure interestingness"),
		VIPS_ARGUMENT_OPTIONAL_INPUT,
		G_STRUCT_OFFSET(VipsSmartcrop, interesting),
		VIPS_TYPE_INTERESTING, VIPS_INTERESTING_ATTENTION);

	VIPS_ARG_INT(class, "attention_x", 2,
		_("Attention x"),
		_("Horizontal position of attention centre"),
		VIPS_ARGUMENT_OPTIONAL_OUTPUT,
		G_STRUCT_OFFSET(VipsSmartcrop, attention_x),
		0, VIPS_MAX_COORD, 0);

	VIPS_ARG_INT(class, "attention_y", 3,
		_("Attention y"),
		_("Vertical position of attention centre"),
		VIPS_ARGUMENT_OPTIONAL_OUTPUT,
		G_STRUCT_OFFSET(VipsSmartcrop, attention_y),
		0, VIPS_MAX_COORD, 0);

	VIPS_ARG_BOOL(class, "premultiplied", 7,
		_("Premultiplied"),
		_("Input image already has premultiplied alpha"),
		VIPS_ARGUMENT_OPTIONAL_INPUT,
		G_STRUCT_OFFSET(VipsSmartcrop, premultiplied),
		FALSE);
}

static void
vips_smartcrop_init(VipsSmartcrop *smartcrop)
{
	smartcrop->interesting = VIPS_INTERESTING_ATTENTION;
	smartcrop->premultiplied = FALSE;
}

/**
 * vips_smartcrop: (method)
 * @in: input image
 * @out: (out): output image
 * @width: width of area to extract
 * @height: height of area to extract
 * @...: %NULL-terminated list of optional named arguments
 *
 * Optional arguments:
 *
 * * @interesting: #VipsInteresting to use to find interesting areas (default: #VIPS_INTERESTING_ATTENTION)
 * * @premultiplied: %gboolean, input image already has premultiplied alpha
 * * @attention_x: %gint, horizontal position of attention centre when using attention based cropping
 * * @attention_y: %gint, vertical position of attention centre when using attention based cropping
 *
 * Crop an image down to a specified width and height by removing boring parts.
 *
 * Use @interesting to pick the method vips uses to decide which bits of the
 * image should be kept.
 *
 * You can test xoffset / yoffset on @out to find the location of the crop
 * within the input image.
 *
 * See also: vips_extract_area().
 *
 * Returns: 0 on success, -1 on error.
 */
int
vips_smartcrop(VipsImage *in, VipsImage **out, int width, int height, ...)
{
	va_list ap;
	int result;

	va_start(ap, height);
	result = vips_call_split("smartcrop", ap, in, out, width, height);
	va_end(ap);

	return result;
}
