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dpmcreate now can run
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but need more work to make sure it produces correct result
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@liuliu
liuliu committed May 5, 2012
1 parent 43d2e9a commit 2c0c83f
Showing 1 changed file with 49 additions and 33 deletions.
82 changes: 49 additions & 33 deletions lib/ccv_dpm.c
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Original file line number Diff line number Diff line change
Expand Up @@ -580,7 +580,7 @@ static void _ccv_dpm_collect_feature_vector(ccv_dpm_feature_vector_t* v, int x,
w_ptr = (float*)ccv_get_dense_matrix_cell_by(CCV_32F | CCV_C1, v->part[i].w, start_y - (iy - ry - pwh), 0, 0);
for (iy = start_y; iy < end_y; iy++)
{
memcpy(w_ptr + start_x * ch, h_ptr + start_x * ch, (end_x - start_x) * ch);
memcpy(w_ptr + (start_x - (ix - rx - pww)) * ch, h_ptr + start_x * ch, (end_x - start_x) * ch);
h_ptr += detail->cols * ch;
w_ptr += v->part[i].w->cols * ch;
}
Expand Down Expand Up @@ -835,45 +835,51 @@ void ccv_dpm_mixture_model_new(char** posfiles, ccv_rect_t* bboxes, int posnum,
ccfree(areas);
innum = 0;
_ccv_dpm_read_checkpoint(model, dir);
if (model->count > 0)
if (model->count <= 0)
{
printf("skipping root mixture model initialization\n");
ccfree(fn);
} else {
/* initialize root mixture model with liblinear */
model->count = params.components;
model->root = (ccv_dpm_root_classifier_t*)ccmalloc(sizeof(ccv_dpm_root_classifier_t) * model->count);
memset(model->root, 0, sizeof(ccv_dpm_root_classifier_t) * model->count);
printf("computing root mixture model dimensions: ");
}
printf("computing root mixture model dimensions: ");
fflush(stdout);
int* labels = (int*)ccmalloc(sizeof(int) * posnum);
int* rows = (int*)alloca(sizeof(int) * params.components);
int* cols = (int*)alloca(sizeof(int) * params.components);
for (i = 0; i < params.components; i++)
{
double aspect = 0;
for (j = innum; j < innum + mnum[i]; j++)
{
aspect += fn[j].value;
labels[fn[j].index] = i; // setup labels
}
aspect /= mnum[i];
cols[i] = ccv_max((int)(sqrtf(area / aspect) * aspect / CCV_DPM_WINDOW_SIZE + 0.5), 1);
rows[i] = ccv_max((int)(sqrtf(area / aspect) / CCV_DPM_WINDOW_SIZE + 0.5), 1);
if (i < params.components - 1)
printf("%dx%d, ", cols[i], rows[i]);
else
printf("%dx%d\n", cols[i], rows[i]);
fflush(stdout);
int* labels = (int*)ccmalloc(sizeof(int) * posnum);
for (i = 0; i < params.components; i++)
innum += mnum[i];
}
for (i = 0; i < params.components; i++)
{
if (model->root[i].root.w != 0)
{
double aspect = 0;
for (j = innum; j < innum + mnum[i]; j++)
{
aspect += fn[j].value;
labels[fn[j].index] = i; // setup labels
}
aspect /= mnum[i];
int cols = ccv_max((int)(sqrtf(area / aspect) * aspect / CCV_DPM_WINDOW_SIZE + 0.5), 1);
int rows = ccv_max((int)(sqrtf(area / aspect) / CCV_DPM_WINDOW_SIZE + 0.5), 1);
ccv_dpm_root_classifier_t* root_classifier = model->root + i;
root_classifier->root.w = ccv_dense_matrix_new(rows, cols, CCV_32F | 31, 0, 0);
if (i < params.components - 1)
printf("%dx%d, ", cols, rows);
else
printf("%dx%d\n", cols, rows);
fflush(stdout);
innum += mnum[i];
printf("skipping root mixture model initialization for model %d(%d)\n", i + 1, params.components);
continue;
}
ccfree(fn);
printf("initializing root mixture model\n");
for (i = 0; i < params.components; i++)
_ccv_dpm_initialize_root_classifier(rng, model->root + i, i, mnum[i], labels, posfiles, bboxes, posnum, bgfiles, bgnum, negnum, params.symmetric, params.grayscale);
ccfree(labels);
ccv_dpm_root_classifier_t* root_classifier = model->root + i;
root_classifier->root.w = ccv_dense_matrix_new(rows[i], cols[i], CCV_32F | 31, 0, 0);
printf("initializing root mixture model for model %d(%d)\n", i + 1, params.components);
_ccv_dpm_initialize_root_classifier(rng, root_classifier, i, mnum[i], labels, posfiles, bboxes, posnum, bgfiles, bgnum, negnum, params.symmetric, params.grayscale);
_ccv_dpm_write_checkpoint(model, dir);
}
ccfree(fn);
ccfree(labels);
if (params.components > 1)
{
/* TODO: coordinate-descent for lsvm */
Expand Down Expand Up @@ -903,23 +909,31 @@ void ccv_dpm_mixture_model_new(char** posfiles, ccv_rect_t* bboxes, int posnum,
{
unsigned int elapsed_time = _ccv_dpm_time_measure();
j = 0;
printf(" - collecting best responses from positive examples : 0%%");
fflush(stdout);
for (i = 0; i < posnum; i++)
{
printf("\b\b\b%2d%%", i * 100 / posnum);
fflush(stdout);
ccv_dense_matrix_t* image = 0;
ccv_read(posfiles[i], &image, (params.grayscale ? CCV_IO_GRAY : 0) | CCV_IO_ANY_FILE);
ccv_rect_t* bbox = bboxes + i;
ccv_dpm_feature_vector_t* v = _ccv_dpm_collect_best(rng, image, model, bbox[0], params.overlap, params.detector);
ccv_dpm_feature_vector_t* v = _ccv_dpm_collect_best(rng, image, model, bboxes[i], params.overlap, params.detector);
if (v != 0)
{
posv[j] = v;
j++;
}
ccv_matrix_free(image);
}
printf("\b\b\b100%%\n");
int posvn = j;
j = 0;
printf(" - collecting responses above threshold 0 from background examples : 0%%");
fflush(stdout);
for (i = 0; i < bgnum; i++)
{
printf("\b\b\b%2d%%", i * 100 / bgnum);
fflush(stdout);
ccv_dense_matrix_t* image = 0;
ccv_read(bgfiles[i], &image, (params.grayscale ? CCV_IO_GRAY : 0) | CCV_IO_ANY_FILE);
ccv_array_t* av = _ccv_dpm_collect_all(rng, image, model, params.detector, 0);
Expand All @@ -939,7 +953,9 @@ void ccv_dpm_mixture_model_new(char** posfiles, ccv_rect_t* bboxes, int posnum,
if (j >= negnum)
break;
}
printf("\b\b\b100%%\n");
int negvn = j;
printf(" - updating using stochastic gradient descent with %d positive examples and %d negative examples\n", posvn, negvn);
for (i = 0; i < posvn; i++)
_ccv_dpm_stochastic_gradient_descent(model, posv[i], 1, params.alpha, params.C * (posvn + negvn), params.symmetric);
for (i = 0; i < negvn; i++)
Expand All @@ -948,7 +964,7 @@ void ccv_dpm_mixture_model_new(char** posfiles, ccv_rect_t* bboxes, int posnum,
_ccv_dpm_feature_vector_free(posv[i]);
for (i = 0; i < negvn; i++)
_ccv_dpm_feature_vector_free(negv[i]);
printf("%d iteration takes %ums, %d more to go\n", t + 1, _ccv_dpm_time_measure() - elapsed_time, params.iterations - t - 1);
printf(" - %d iteration takes %ums, %d more to go\n", t + 1, _ccv_dpm_time_measure() - elapsed_time, params.iterations - t - 1);
}
ccfree(negv);
ccfree(posv);
Expand Down

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