void log(string prefix,SphericalOccupancyMap&SOM)
{
Mat vis_r, vis_t, vis_z, vis_match,message,vis_raw_z;
Mat zSlice = imclamp(SOM.get_OM(),t.z_min,t.z_max);
// vis
vis_raw_z = eq(SOM.get_OM());
vis_r = eq(r);
vis_t = eq(t.t);
vis_z = eq(zSlice);
Mat vis_t_full(vis_z.rows,vis_z.cols,DataType<Vec3b>::type,Scalar::all(255));
{
Mat src_roi = imroi(vis_t,Rect(Point(0,0),bb.size()));
Mat dst_roi = imroi(vis_t_full,bb);
src_roi.copyTo(dst_roi);
}
vis_match = im_merge(
imroi(vis_r,Rect(Point(0,0),vis_z.size())),
vis_z,
vis_t_full);
cv::rectangle(vis_match,bb.tl(),bb.br(),toScalar(BLUE));
message = image_text(safe_printf("resp = %",extrema(r).max));
vector<Mat> vs{vis_r,vis_t,vis_z,vis_match,vis_raw_z,message};
log_im(prefix,tileCat(vs));
}
void nes_cpu_adc_im(void) {
uint8_t immediate = cpu_get_op();
log_im("ADC", (uint8_t)(immediate));
uint16_t result = cpu.a + immediate + cpu_get_C();
if (~(cpu.a ^ immediate) & (cpu.a ^ lo(result)) & 0x80) cpu_set_V();
if (hi(result)) cpu_set_C(); else cpu_clr_C();
cpu.a = lo(result);
cpu_check_Z(cpu.a); cpu_check_N(cpu.a);
cpu.pc += 2;
}
void LibHandMetadata::log_metric_bb() const
{
// draw the metric bb
Mat metric_viz = imageeq("",Z.clone(),false,false);
Point bl(handBB.tl().x,handBB.br().y);
Point tr(handBB.br().x,handBB.tl().y);
cv::line(metric_viz,handBB.tl(),bl,toScalar(RED));
cv::line(metric_viz,handBB.br(),bl,toScalar(GREEN));
// compute edge lengths using law of cosines
double z = medianApx(Z,handBB,.5);
double t1 = camera.distance_angular(handBB.tl(),bl);
double d1 = camera.distance_geodesic(handBB.tl(),z,bl,z);
double t2 = camera.distance_angular(handBB.br(),bl);
double d2 = camera.distance_geodesic(handBB.br(),z,bl,z);
Mat text = vertCat(image_text(safe_printf("% cm % rad",d1,t1),RED),
image_text(safe_printf("% cm % rad",d2,t2),GREEN));
text = vertCat(text,image_text(safe_printf("% cm",z)));
log_im("MetricBBSides",vertCat(metric_viz,text));
}
vector<Scores> eval_model(int argc, char**argv,const Model_Builder&model_builder)
{
// train the model
shared_ptr<Model> model = train_model(model_builder);
// save the model.
if(g_params.option_is_set("WRITE_MODEL"))
{
FileStorage save_model(params::out_dir() + "/model.yml",FileStorage::WRITE);
save_model << "model";
bool model_wrote = model->write(save_model);
if(!model_wrote)
log_file << "warning: failed to write model!" << endl;
save_model.release();
}
// show the model
log_im("final_model",model->show("final model"));
//
// testing phase
//
// test on video
if(g_params.has_key("TEST_VIDEO"))
test_model_oni_video(*model);
// compute training error
//auto result = eval_on_dirs(model,
//vector<string>{params::synthetic_directory()});
// test on images
if(g_params.has_key("TEST_IMAGES"))
test_model_images(model);
// test on directories
//auto result = eval_on_dirs(model,testDirs = default_test_dirs(););
//return reuslt;
return vector<Scores>();
}
