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ccv-src/lib/ccv_bbf.c  view on Meta::CPAN

}

static inline double _ccv_bbf_error_rate(ccv_bbf_feature_t* feature, unsigned char** posdata, int posnum, unsigned char** negdata, int negnum, ccv_size_t size, double* pw, double* nw)
{
	int i;
	int steps[] = { _ccv_width_padding(size.width),
					_ccv_width_padding(size.width >> 1),
					_ccv_width_padding(size.width >> 2) };
	int isizs0 = steps[0] * size.height;
	int isizs01 = isizs0 + steps[1] * (size.height >> 1);
	double error = 0;
	for (i = 0; i < posnum; i++)
	{
		unsigned char* u8[] = { posdata[i], posdata[i] + isizs0, posdata[i] + isizs01 };
		if (!_ccv_run_bbf_feature(feature, steps, u8))
			error += pw[i];
	}
	for (i = 0; i < negnum; i++)
	{
		unsigned char* u8[] = { negdata[i], negdata[i] + isizs0, negdata[i] + isizs01 };
		if ( _ccv_run_bbf_feature(feature, steps, u8))
			error += nw[i];
	}
	return error;
}

#define less_than(fit1, fit2, aux) ((fit1).fitness >= (fit2).fitness)
static CCV_IMPLEMENT_QSORT(_ccv_bbf_genetic_qsort, ccv_bbf_gene_t, less_than)
#undef less_than

static ccv_bbf_feature_t _ccv_bbf_genetic_optimize(unsigned char** posdata, int posnum, unsigned char** negdata, int negnum, int ftnum, ccv_size_t size, double* pw, double* nw)
{
	ccv_bbf_feature_t best;
	/* seed (random method) */
	gsl_rng_env_setup();
	gsl_rng* rng = gsl_rng_alloc(gsl_rng_default);
	union { unsigned long int li; double db; } dbli;
	dbli.db = pw[0] + nw[0];
	gsl_rng_set(rng, dbli.li);
	int i, j;
	int pnum = ftnum * 100;
	assert(pnum > 0);
	ccv_bbf_gene_t* gene = (ccv_bbf_gene_t*)ccmalloc(pnum * sizeof(ccv_bbf_gene_t));
	int rows[] = { size.height, size.height >> 1, size.height >> 2 };
	int cols[] = { size.width, size.width >> 1, size.width >> 2 };
	for (i = 0; i < pnum; i++)
		_ccv_bbf_randomize_gene(rng, &gene[i], rows, cols);
	unsigned int timer = _ccv_bbf_time_measure();
#ifdef USE_OPENMP
#pragma omp parallel for private(i) schedule(dynamic)
#endif
	for (i = 0; i < pnum; i++)
		gene[i].error = _ccv_bbf_error_rate(&gene[i].feature, posdata, posnum, negdata, negnum, size, pw, nw);
	timer = _ccv_bbf_time_measure() - timer;
	for (i = 0; i < pnum; i++)
		_ccv_bbf_genetic_fitness(&gene[i]);
	double best_err = 1;
	int rnum = ftnum * 39; /* number of randomize */
	int mnum = ftnum * 40; /* number of mutation */
	int hnum = ftnum * 20; /* number of hybrid */
	/* iteration stop crit : best no change in 40 iterations */
	int it = 0, t;
	for (t = 0 ; it < 40; ++it, ++t)
	{
		int min_id = 0;
		double min_err = gene[0].error;
		for (i = 1; i < pnum; i++)
			if (gene[i].error < min_err)
			{
				min_id = i;
				min_err = gene[i].error;
			}
		min_err = gene[min_id].error = _ccv_bbf_error_rate(&gene[min_id].feature, posdata, posnum, negdata, negnum, size, pw, nw);
		if (min_err < best_err)
		{
			best_err = min_err;
			memcpy(&best, &gene[min_id].feature, sizeof(best));
			PRINT(CCV_CLI_INFO, "best bbf feature with error %f\n|-size: %d\n|-positive point: ", best_err, best.size);
			for (i = 0; i < best.size; i++)
				PRINT(CCV_CLI_INFO, "(%d %d %d), ", best.px[i], best.py[i], best.pz[i]);
			PRINT(CCV_CLI_INFO, "\n|-negative point: ");
			for (i = 0; i < best.size; i++)
				PRINT(CCV_CLI_INFO, "(%d %d %d), ", best.nx[i], best.ny[i], best.nz[i]);
			PRINT(CCV_CLI_INFO, "\n");
			it = 0;
		}
		PRINT(CCV_CLI_INFO, "minimum error achieved in round %d(%d) : %f with %d ms\n", t, it, min_err, timer / 1000);
		_ccv_bbf_genetic_qsort(gene, pnum, 0);
		for (i = 0; i < ftnum; i++)
			++gene[i].age;
		for (i = ftnum; i < ftnum + mnum; i++)
		{
			int parent = gsl_rng_uniform_int(rng, ftnum);
			memcpy(gene + i, gene + parent, sizeof(ccv_bbf_gene_t));
			/* three mutation strategy : 1. add, 2. remove, 3. refine */
			int pnm, pn = gsl_rng_uniform_int(rng, 2);
			int* pnk[] = { &gene[i].pk, &gene[i].nk };
			int* pnx[] = { gene[i].feature.px, gene[i].feature.nx };
			int* pny[] = { gene[i].feature.py, gene[i].feature.ny };
			int* pnz[] = { gene[i].feature.pz, gene[i].feature.nz };
			int x, y, z;
			int victim, decay = 1;
			do {
				switch (gsl_rng_uniform_int(rng, 3))
				{
					case 0: /* add */
						if (gene[i].pk == CCV_BBF_POINT_MAX && gene[i].nk == CCV_BBF_POINT_MAX)
							break;
						while (*pnk[pn] + 1 > CCV_BBF_POINT_MAX)
							pn = gsl_rng_uniform_int(rng, 2);
						do {
							z = gsl_rng_uniform_int(rng, 3);
							x = gsl_rng_uniform_int(rng, cols[z]);
							y = gsl_rng_uniform_int(rng, rows[z]);
						} while (_ccv_bbf_exist_gene_feature(&gene[i], x, y, z));
						pnz[pn][*pnk[pn]] = z;
						pnx[pn][*pnk[pn]] = x;
						pny[pn][*pnk[pn]] = y;
						++(*pnk[pn]);
						gene[i].feature.size = ccv_max(gene[i].pk, gene[i].nk);
						decay = gene[i].age = 0;