openpilot is an open source driver assistance system. openpilot performs the functions of Automated Lane Centering and Adaptive Cruise Control for over 200 supported car makes and models.
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#include <cstdio>
#include <cstdlib>
#include <mutex>
#include <eigen3/Eigen/Dense>
#include "cereal/messaging/messaging.h"
#include "cereal/visionipc/visionipc_client.h"
#include "selfdrive/common/clutil.h"
#include "selfdrive/common/params.h"
#include "selfdrive/common/swaglog.h"
#include "selfdrive/common/util.h"
#include "selfdrive/hardware/hw.h"
#include "selfdrive/modeld/models/driving.h"
ExitHandler do_exit;
// globals
bool live_calib_seen;
mat3 cur_transform;
std::mutex transform_lock;
void calibration_thread(bool wide_camera) {
set_thread_name("calibration");
set_realtime_priority(50);
SubMaster sm({"liveCalibration"});
/*
import numpy as np
from common.transformations.model import medmodel_frame_from_road_frame
medmodel_frame_from_ground = medmodel_frame_from_road_frame[:, (0, 1, 3)]
ground_from_medmodel_frame = np.linalg.inv(medmodel_frame_from_ground)
*/
Eigen::Matrix<float, 3, 3> ground_from_medmodel_frame;
ground_from_medmodel_frame <<
0.00000000e+00, 0.00000000e+00, 1.00000000e+00,
-1.09890110e-03, 0.00000000e+00, 2.81318681e-01,
-1.84808520e-20, 9.00738606e-04,-4.28751576e-02;
Eigen::Matrix<float, 3, 3> cam_intrinsics = Eigen::Matrix<float, 3, 3, Eigen::RowMajor>(wide_camera ? ecam_intrinsic_matrix.v : fcam_intrinsic_matrix.v);
const mat3 yuv_transform = get_model_yuv_transform();
while (!do_exit) {
sm.update(100);
if(sm.updated("liveCalibration")) {
auto extrinsic_matrix = sm["liveCalibration"].getLiveCalibration().getExtrinsicMatrix();
Eigen::Matrix<float, 3, 4> extrinsic_matrix_eigen;
for (int i = 0; i < 4*3; i++) {
extrinsic_matrix_eigen(i / 4, i % 4) = extrinsic_matrix[i];
}
auto camera_frame_from_road_frame = cam_intrinsics * extrinsic_matrix_eigen;
Eigen::Matrix<float, 3, 3> camera_frame_from_ground;
camera_frame_from_ground.col(0) = camera_frame_from_road_frame.col(0);
camera_frame_from_ground.col(1) = camera_frame_from_road_frame.col(1);
camera_frame_from_ground.col(2) = camera_frame_from_road_frame.col(3);
auto warp_matrix = camera_frame_from_ground * ground_from_medmodel_frame;
mat3 transform = {};
for (int i=0; i<3*3; i++) {
transform.v[i] = warp_matrix(i / 3, i % 3);
}
mat3 model_transform = matmul3(yuv_transform, transform);
std::lock_guard lk(transform_lock);
cur_transform = model_transform;
live_calib_seen = true;
}
}
}
void run_model(ModelState &model, VisionIpcClient &vipc_client) {
// messaging
PubMaster pm({"modelV2", "cameraOdometry"});
SubMaster sm({"lateralPlan", "roadCameraState"});
// setup filter to track dropped frames
FirstOrderFilter frame_dropped_filter(0., 10., 1. / MODEL_FREQ);
uint32_t frame_id = 0, last_vipc_frame_id = 0;
double last = 0;
int desire = -1;
uint32_t run_count = 0;
while (!do_exit) {
VisionIpcBufExtra extra = {};
VisionBuf *buf = vipc_client.recv(&extra);
if (buf == nullptr) continue;
transform_lock.lock();
mat3 model_transform = cur_transform;
const bool run_model_this_iter = live_calib_seen;
transform_lock.unlock();
// TODO: path planner timeout?
sm.update(0);
desire = ((int)sm["lateralPlan"].getLateralPlan().getDesire());
frame_id = sm["roadCameraState"].getRoadCameraState().getFrameId();
if (run_model_this_iter) {
run_count++;
float vec_desire[DESIRE_LEN] = {0};
if (desire >= 0 && desire < DESIRE_LEN) {
vec_desire[desire] = 1.0;
}
double mt1 = millis_since_boot();
ModelDataRaw model_buf = model_eval_frame(&model, buf->buf_cl, buf->width, buf->height,
model_transform, vec_desire);
double mt2 = millis_since_boot();
float model_execution_time = (mt2 - mt1) / 1000.0;
// tracked dropped frames
uint32_t vipc_dropped_frames = extra.frame_id - last_vipc_frame_id - 1;
float frames_dropped = frame_dropped_filter.update((float)std::min(vipc_dropped_frames, 10U));
if (run_count < 10) { // let frame drops warm up
frame_dropped_filter.reset(0);
frames_dropped = 0.;
}
float frame_drop_ratio = frames_dropped / (1 + frames_dropped);
model_publish(pm, extra.frame_id, frame_id, frame_drop_ratio, model_buf, extra.timestamp_eof, model_execution_time,
kj::ArrayPtr<const float>(model.output.data(), model.output.size()));
posenet_publish(pm, extra.frame_id, vipc_dropped_frames, model_buf, extra.timestamp_eof);
//printf("model process: %.2fms, from last %.2fms, vipc_frame_id %u, frame_id, %u, frame_drop %.3f\n", mt2 - mt1, mt1 - last, extra.frame_id, frame_id, frame_drop_ratio);
last = mt1;
last_vipc_frame_id = extra.frame_id;
}
}
}
int main(int argc, char **argv) {
set_realtime_priority(54);
if (Hardware::EON()) {
set_core_affinity(2);
} else if (Hardware::TICI()) {
set_core_affinity(7);
}
bool wide_camera = Hardware::TICI() ? Params().getBool("EnableWideCamera") : false;
// start calibration thread
std::thread thread = std::thread(calibration_thread, wide_camera);
// cl init
cl_device_id device_id = cl_get_device_id(CL_DEVICE_TYPE_DEFAULT);
cl_context context = CL_CHECK_ERR(clCreateContext(NULL, 1, &device_id, NULL, NULL, &err));
// init the models
ModelState model;
model_init(&model, device_id, context);
LOGW("models loaded, modeld starting");
VisionIpcClient vipc_client = VisionIpcClient("camerad", wide_camera ? VISION_STREAM_YUV_WIDE : VISION_STREAM_YUV_BACK, true, device_id, context);
while (!do_exit && !vipc_client.connect(false)) {
util::sleep_for(100);
}
// run the models
// vipc_client.connected is false only when do_exit is true
if (vipc_client.connected) {
const VisionBuf *b = &vipc_client.buffers[0];
LOGW("connected with buffer size: %d (%d x %d)", b->len, b->width, b->height);
run_model(model, vipc_client);
}
model_free(&model);
LOG("joining calibration thread");
thread.join();
CL_CHECK(clReleaseContext(context));
return 0;
}