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dmonitoring: improve yuvframe2tensor (#21996) 

* use Y,U,V

* use a pre-calculated table

* add variable use_snpe_model

* .dlc

* remove if
pull/22088/head
Dean Lee 2021-08-31 12:23:01 +08:00 committed by GitHub
parent 383ff35790
commit 784b3a2ac9
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GPG Key ID: 4AEE18F83AFDEB23
2 changed files with 13 additions and 15 deletions
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27
selfdrive/modeld/models/dmonitoring.cc
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@ -13,17 +13,14 @@
#define MODEL_HEIGHT 640
#define FULL_W 852 // should get these numbers from camerad
#if defined(QCOM) || defined(QCOM2)
#define input_lambda(x) (x - 128.f) * 0.0078125f
#else
#define input_lambda(x) x // for non SNPE running platforms, assume keras model instead has lambda layer
#endif
void dmonitoring_init(DMonitoringModelState* s) {
const char *model_path = Hardware::PC() ? "../../models/dmonitoring_model.dlc" : "../../models/dmonitoring_model_q.dlc";
int runtime = USE_DSP_RUNTIME;
s->m = new DefaultRunModel(model_path, &s->output[0], OUTPUT_SIZE, runtime);
s->is_rhd = Params().getBool("IsRHD");
const char *model_path = Hardware::PC() ? "../../models/dmonitoring_model.dlc" : "../../models/dmonitoring_model_q.dlc";
s->m = new DefaultRunModel(model_path, &s->output[0], OUTPUT_SIZE, USE_DSP_RUNTIME);
for (int x = 0; x < std::size(s->tensor); ++x) {
s->tensor[x] = (x - 128.f) * 0.0078125f;
}
}
template <class T>
@ -112,17 +109,17 @@ DMonitoringResult dmonitoring_eval_frame(DMonitoringModelState* s, void* stream_
for (int r = 0; r < MODEL_HEIGHT/2; r++) {
for (int c = 0; c < MODEL_WIDTH/2; c++) {
// Y_ul
net_input_buf[(r*MODEL_WIDTH/2) + c + (0*(MODEL_WIDTH/2)*(MODEL_HEIGHT/2))] = input_lambda(resized_buf[(2*r)*resized_width + (2*c)]);
net_input_buf[(r*MODEL_WIDTH/2) + c + (0*(MODEL_WIDTH/2)*(MODEL_HEIGHT/2))] = s->tensor[resized_y[(2*r)*resized_width + 2*c]];
// Y_dl
net_input_buf[(r*MODEL_WIDTH/2) + c + (1*(MODEL_WIDTH/2)*(MODEL_HEIGHT/2))] = input_lambda(resized_buf[(2*r+1)*resized_width + (2*c)]);
net_input_buf[(r*MODEL_WIDTH/2) + c + (1*(MODEL_WIDTH/2)*(MODEL_HEIGHT/2))] = s->tensor[resized_y[(2*r+1)*resized_width + 2*c]];
// Y_ur
net_input_buf[(r*MODEL_WIDTH/2) + c + (2*(MODEL_WIDTH/2)*(MODEL_HEIGHT/2))] = input_lambda(resized_buf[(2*r)*resized_width + (2*c+1)]);
net_input_buf[(r*MODEL_WIDTH/2) + c + (2*(MODEL_WIDTH/2)*(MODEL_HEIGHT/2))] = s->tensor[resized_y[(2*r)*resized_width + 2*c+1]];
// Y_dr
net_input_buf[(r*MODEL_WIDTH/2) + c + (3*(MODEL_WIDTH/2)*(MODEL_HEIGHT/2))] = input_lambda(resized_buf[(2*r+1)*resized_width + (2*c+1)]);
net_input_buf[(r*MODEL_WIDTH/2) + c + (3*(MODEL_WIDTH/2)*(MODEL_HEIGHT/2))] = s->tensor[resized_y[(2*r+1)*resized_width + 2*c+1]];
// U
net_input_buf[(r*MODEL_WIDTH/2) + c + (4*(MODEL_WIDTH/2)*(MODEL_HEIGHT/2))] = input_lambda(resized_buf[(resized_width*resized_height) + r*resized_width/2 + c]);
net_input_buf[(r*MODEL_WIDTH/2) + c + (4*(MODEL_WIDTH/2)*(MODEL_HEIGHT/2))] = s->tensor[resized_u[r*resized_width/2 + c]];
// V
net_input_buf[(r*MODEL_WIDTH/2) + c + (5*(MODEL_WIDTH/2)*(MODEL_HEIGHT/2))] = input_lambda(resized_buf[(resized_width*resized_height) + ((resized_width/2)*(resized_height/2)) + c + (r*resized_width/2)]);
net_input_buf[(r*MODEL_WIDTH/2) + c + (5*(MODEL_WIDTH/2)*(MODEL_HEIGHT/2))] = s->tensor[resized_v[r*resized_width/2 + c]];
}
}

1
selfdrive/modeld/models/dmonitoring.h
View File

@ -35,6 +35,7 @@ typedef struct DMonitoringModelState {
std::vector<uint8_t> cropped_buf;
std::vector<uint8_t> premirror_cropped_buf;
std::vector<float> net_input_buf;
float tensor[UINT8_MAX + 1];
} DMonitoringModelState;
void dmonitoring_init(DMonitoringModelState* s);