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@ -6,7 +6,6 @@ import time |
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import ctypes |
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import ctypes |
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import numpy as np |
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import numpy as np |
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from pathlib import Path |
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from pathlib import Path |
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from setproctitle import setproctitle |
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from cereal import messaging |
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from cereal import messaging |
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from cereal.messaging import PubMaster, SubMaster |
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from cereal.messaging import PubMaster, SubMaster |
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@ -15,18 +14,16 @@ from openpilot.common.swaglog import cloudlog |
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from openpilot.common.params import Params |
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from openpilot.common.params import Params |
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from openpilot.common.realtime import set_realtime_priority |
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from openpilot.common.realtime import set_realtime_priority |
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from openpilot.selfdrive.modeld.runners import ModelRunner, Runtime |
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from openpilot.selfdrive.modeld.runners import ModelRunner, Runtime |
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from openpilot.selfdrive.modeld.models.commonmodel_pyx import sigmoid, CLContext |
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from openpilot.selfdrive.modeld.models.commonmodel_pyx import sigmoid |
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CALIB_LEN = 3 |
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CALIB_LEN = 3 |
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REG_SCALE = 0.25 |
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MODEL_WIDTH = 1440 |
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MODEL_WIDTH = 1440 |
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MODEL_HEIGHT = 960 |
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MODEL_HEIGHT = 960 |
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FEATURE_LEN = 512 |
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OUTPUT_SIZE = 84 |
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OUTPUT_SIZE = 84 + FEATURE_LEN |
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PROCESS_NAME = "selfdrive.modeld.dmonitoringmodeld" |
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SEND_RAW_PRED = os.getenv('SEND_RAW_PRED') |
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SEND_RAW_PRED = os.getenv('SEND_RAW_PRED') |
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MODEL_PATHS = { |
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MODEL_PATHS = { |
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ModelRunner.THNEED: Path(__file__).parent / 'models/dmonitoring_model.thneed', |
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ModelRunner.SNPE: Path(__file__).parent / 'models/dmonitoring_model_q.dlc', |
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ModelRunner.ONNX: Path(__file__).parent / 'models/dmonitoring_model.onnx'} |
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ModelRunner.ONNX: Path(__file__).parent / 'models/dmonitoring_model.onnx'} |
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class DriverStateResult(ctypes.Structure): |
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class DriverStateResult(ctypes.Structure): |
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@ -52,22 +49,21 @@ class DMonitoringModelResult(ctypes.Structure): |
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("driver_state_lhd", DriverStateResult), |
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("driver_state_lhd", DriverStateResult), |
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("driver_state_rhd", DriverStateResult), |
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("driver_state_rhd", DriverStateResult), |
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("poor_vision_prob", ctypes.c_float), |
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("poor_vision_prob", ctypes.c_float), |
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("wheel_on_right_prob", ctypes.c_float), |
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("wheel_on_right_prob", ctypes.c_float)] |
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("features", ctypes.c_float*FEATURE_LEN)] |
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class ModelState: |
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class ModelState: |
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inputs: dict[str, np.ndarray] |
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inputs: dict[str, np.ndarray] |
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output: np.ndarray |
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output: np.ndarray |
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model: ModelRunner |
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model: ModelRunner |
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def __init__(self, cl_ctx): |
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def __init__(self): |
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assert ctypes.sizeof(DMonitoringModelResult) == OUTPUT_SIZE * ctypes.sizeof(ctypes.c_float) |
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assert ctypes.sizeof(DMonitoringModelResult) == OUTPUT_SIZE * ctypes.sizeof(ctypes.c_float) |
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self.output = np.zeros(OUTPUT_SIZE, dtype=np.float32) |
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self.output = np.zeros(OUTPUT_SIZE, dtype=np.float32) |
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self.inputs = { |
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self.inputs = { |
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'input_img': np.zeros(MODEL_HEIGHT * MODEL_WIDTH, dtype=np.uint8), |
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'input_img': np.zeros(MODEL_HEIGHT * MODEL_WIDTH, dtype=np.uint8), |
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'calib': np.zeros(CALIB_LEN, dtype=np.float32)} |
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'calib': np.zeros(CALIB_LEN, dtype=np.float32)} |
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self.model = ModelRunner(MODEL_PATHS, self.output, Runtime.GPU, False, cl_ctx) |
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self.model = ModelRunner(MODEL_PATHS, self.output, Runtime.DSP, True, None) |
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self.model.addInput("input_img", None) |
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self.model.addInput("input_img", None) |
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self.model.addInput("calib", self.inputs['calib']) |
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self.model.addInput("calib", self.inputs['calib']) |
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@ -80,17 +76,17 @@ class ModelState: |
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input_data = self.inputs['input_img'].reshape(MODEL_HEIGHT, MODEL_WIDTH) |
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input_data = self.inputs['input_img'].reshape(MODEL_HEIGHT, MODEL_WIDTH) |
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input_data[:] = buf_data[v_offset:v_offset+MODEL_HEIGHT, h_offset:h_offset+MODEL_WIDTH] |
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input_data[:] = buf_data[v_offset:v_offset+MODEL_HEIGHT, h_offset:h_offset+MODEL_WIDTH] |
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self.model.setInputBuffer("input_img", self.inputs['input_img'].view(np.float32)) |
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t1 = time.perf_counter() |
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t1 = time.perf_counter() |
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self.model.setInputBuffer("input_img", self.inputs['input_img'].view(np.float32)) |
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self.model.execute() |
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self.model.execute() |
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t2 = time.perf_counter() |
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t2 = time.perf_counter() |
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return self.output, t2 - t1 |
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return self.output, t2 - t1 |
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def fill_driver_state(msg, ds_result: DriverStateResult): |
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def fill_driver_state(msg, ds_result: DriverStateResult): |
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msg.faceOrientation = list(ds_result.face_orientation) |
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msg.faceOrientation = [x * REG_SCALE for x in ds_result.face_orientation] |
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msg.faceOrientationStd = [math.exp(x) for x in ds_result.face_orientation_std] |
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msg.faceOrientationStd = [math.exp(x) for x in ds_result.face_orientation_std] |
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msg.facePosition = list(ds_result.face_position[:2]) |
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msg.facePosition = [x * REG_SCALE for x in ds_result.face_position[:2]] |
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msg.facePositionStd = [math.exp(x) for x in ds_result.face_position_std[:2]] |
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msg.facePositionStd = [math.exp(x) for x in ds_result.face_position_std[:2]] |
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msg.faceProb = sigmoid(ds_result.face_prob) |
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msg.faceProb = sigmoid(ds_result.face_prob) |
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msg.leftEyeProb = sigmoid(ds_result.left_eye_prob) |
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msg.leftEyeProb = sigmoid(ds_result.left_eye_prob) |
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@ -119,16 +115,14 @@ def get_driverstate_packet(model_output: np.ndarray, frame_id: int, location_ts: |
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def main(): |
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def main(): |
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gc.disable() |
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gc.disable() |
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setproctitle(PROCESS_NAME) |
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set_realtime_priority(1) |
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set_realtime_priority(1) |
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cl_context = CLContext() |
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model = ModelState() |
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model = ModelState(cl_context) |
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cloudlog.warning("models loaded, dmonitoringmodeld starting") |
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cloudlog.warning("models loaded, dmonitoringmodeld starting") |
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Params().put_bool("DmModelInitialized", True) |
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Params().put_bool("DmModelInitialized", True) |
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cloudlog.warning("connecting to driver stream") |
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cloudlog.warning("connecting to driver stream") |
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vipc_client = VisionIpcClient("camerad", VisionStreamType.VISION_STREAM_DRIVER, True, cl_context) |
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vipc_client = VisionIpcClient("camerad", VisionStreamType.VISION_STREAM_DRIVER, True) |
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while not vipc_client.connect(False): |
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while not vipc_client.connect(False): |
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time.sleep(0.1) |
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time.sleep(0.1) |
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assert vipc_client.is_connected() |
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assert vipc_client.is_connected() |
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