build: fix all pylint/mypy errors
This commit is contained in:
parent
4daf4d3c23
commit
55d8ce06c6
@ -5,10 +5,12 @@ import argparse
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import logging
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import os
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import signal
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import typing, types
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import depthai as dai
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import paho.mqtt.client as mqtt
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from . import depthai as cam
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from . import depthai as cam # pylint: disable=reimported
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logger = logging.getLogger(__name__)
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logging.basicConfig(level=logging.INFO)
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@ -54,7 +56,7 @@ def _parse_args_cli() -> argparse.Namespace:
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return args
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def _init_mqtt_client(broker_host: str, broker_port, user: str, password: str, client_id: str) -> mqtt.Client:
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def _init_mqtt_client(broker_host: str, broker_port: int, user: str, password: str, client_id: str) -> mqtt.Client:
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logger.info("Start part.py-robocar-oak-camera")
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client = mqtt.Client(client_id=client_id, clean_session=True, userdata=None, protocol=mqtt.MQTTv311)
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@ -85,10 +87,17 @@ def execute_from_command_line() -> None:
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objects_topic=args.mqtt_topic_robocar_objects,
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objects_threshold=args.objects_threshold)
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pipeline = dai.Pipeline()
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pipeline_controller = cam.PipelineController(frame_processor=frame_processor,
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object_processor=object_processor)
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object_processor=object_processor,
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object_node=cam.ObjectDetectionNN(pipeline=pipeline),
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camera=cam.CameraSource(pipeline=pipeline,
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img_width=args.image_width,
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img_height=args.image_width,
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))
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def sigterm_handler():
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def sigterm_handler(signum: int, frame: typing.Optional[
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types.FrameType]) -> None: # pylint: disable=unused-argument # need to implement handler signature
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logger.info("exit on SIGTERM")
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pipeline_controller.stop()
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@ -4,15 +4,17 @@ Camera event loop
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import abc
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import datetime
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import logging
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import pathlib
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import typing
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from dataclasses import dataclass
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import cv2
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import depthai as dai
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import events.events_pb2
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import events.events_pb2 as evt
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import numpy as np
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import numpy.typing as npt
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import paho.mqtt.client as mqtt
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from depthai import Device
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logger = logging.getLogger(__name__)
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@ -31,7 +33,7 @@ class ObjectProcessor:
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self._objects_topic = objects_topic
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self._objects_threshold = objects_threshold
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def process(self, in_nn: dai.NNData, frame_ref) -> None:
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def process(self, in_nn: dai.NNData, frame_ref: evt.FrameRef) -> None:
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"""
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Parse and publish result of NeuralNetwork result
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:param in_nn: NeuralNetwork result read from device
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@ -48,8 +50,8 @@ class ObjectProcessor:
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if boxes.shape[0] > 0:
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self._publish_objects(boxes, frame_ref, scores)
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def _publish_objects(self, boxes: npt.NDArray[np.float64], frame_ref, scores: npt.NDArray[np.float64]) -> None:
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objects_msg = events.events_pb2.ObjectsMessage()
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def _publish_objects(self, boxes: npt.NDArray[np.float64], frame_ref: evt.FrameRef, scores: npt.NDArray[np.float64]) -> None:
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objects_msg = evt.ObjectsMessage()
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objs = []
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for i in range(boxes.shape[0]):
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logger.debug("new object detected: %s", str(boxes[i]))
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@ -105,7 +107,7 @@ class FrameProcessor:
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byte_im = im_buf_arr.tobytes()
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now = datetime.datetime.now()
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frame_msg = events.events_pb2.FrameMessage()
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frame_msg = evt.FrameMessage()
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frame_msg.id.name = "robocar-oak-camera-oak"
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frame_msg.id.id = str(int(now.timestamp() * 1000))
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frame_msg.id.created_at.FromDatetime(now)
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@ -149,7 +151,7 @@ class ObjectDetectionNN:
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def __init__(self, pipeline: dai.Pipeline):
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# Define a neural network that will make predictions based on the source frames
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detection_nn = pipeline.createNeuralNetwork()
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detection_nn.setBlobPath(_NN_PATH)
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detection_nn.setBlobPath(pathlib.Path(_NN_PATH))
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detection_nn.setNumPoolFrames(4)
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detection_nn.input.setBlocking(False)
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detection_nn.setNumInferenceThreads(2)
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@ -230,7 +232,7 @@ class MqttConfig:
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class MqttSource(Source):
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"""Image source based onto mqtt stream"""
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def __init__(self, device: dai.Device, pipeline: dai.Pipeline, mqtt_config: MqttConfig):
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def __init__(self, device: Device, pipeline: dai.Pipeline, mqtt_config: MqttConfig):
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self._mqtt_config = mqtt_config
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self._client = mqtt.Client()
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self._client.user_data_set(mqtt_config)
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@ -264,7 +266,7 @@ class MqttSource(Source):
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# pylint: disable=unused-argument
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def _on_message(self, _: mqtt.Client, user_data: MqttConfig, msg: mqtt.MQTTMessage) -> None:
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frame_msg = events.events_pb2.FrameMessage()
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frame_msg = evt.FrameMessage()
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frame_msg.ParseFromString(msg.payload)
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frame = np.asarray(frame_msg.frame, dtype="uint8")
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@ -276,11 +278,11 @@ class MqttSource(Source):
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def get_stream_name(self) -> str:
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return self._img_out.getStreamName()
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def link(self, input_node: dai.Node.Input):
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def link(self, input_node: dai.Node.Input) -> None:
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self._img_in.out.link(input_node)
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def _to_planar(arr: npt.NDArray[int], shape: tuple[int, int]) -> list[int]:
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def _to_planar(arr: npt.NDArray[np.uint8], shape: tuple[int, int]) -> list[int]:
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return [val for channel in cv2.resize(arr, shape).transpose(2, 0, 1) for y_col in channel for val in y_col]
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@ -316,17 +318,19 @@ class PipelineController:
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:return:
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"""
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# Connect to device and start pipeline
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with dai.Device(pipeline=self._pipeline) as device:
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logger.info('MxId: %s', device.getDeviceInfo().getMxId())
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logger.info('USB speed: %s', device.getUsbSpeed())
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logger.info('Connected cameras: %s', str(device.getConnectedCameras()))
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logger.info("output queues found: %s", str(device.getOutputQueueNames()))
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with Device(pipeline=self._pipeline) as dev:
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logger.info('MxId: %s', dev.getDeviceInfo().getMxId())
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logger.info('USB speed: %s', dev.getUsbSpeed())
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logger.info('Connected cameras: %s', str(dev.getConnectedCameras()))
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logger.info("output queues found: %s", str(''.join(dev.getOutputQueueNames()))) # type: ignore
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device.startPipeline()
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dev.startPipeline()
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# Queues
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queue_size = 4
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q_rgb = device.getOutputQueue(name=self._camera.get_stream_name(), maxSize=queue_size, blocking=False)
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q_nn = device.getOutputQueue(name=self._object_node.get_stream_name(), maxSize=queue_size, blocking=False)
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q_rgb = dev.getOutputQueue(name=self._camera.get_stream_name(), maxSize=queue_size, # type: ignore
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blocking=False)
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q_nn = dev.getOutputQueue(name=self._object_node.get_stream_name(), maxSize=queue_size, # type: ignore
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blocking=False)
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self._stop = False
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while True:
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@ -343,14 +347,14 @@ class PipelineController:
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logger.debug("wait for new frame")
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# Wait for frame
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in_rgb: dai.ImgFrame = q_rgb.get() # blocking call, will wait until a new data has arrived
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in_rgb: dai.ImgFrame = q_rgb.get() # type: ignore # blocking call, will wait until a new data has arrived
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try:
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frame_ref = self._frame_processor.process(in_rgb)
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except FrameProcessError as ex:
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logger.error("unable to process frame: %s", str(ex))
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return
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# Read NN result
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in_nn: dai.NNData = q_nn.get()
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in_nn: dai.NNData = q_nn.get() # type: ignore
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self._object_processor.process(in_nn, frame_ref)
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def stop(self) -> None:
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@ -361,9 +365,9 @@ class PipelineController:
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self._stop = True
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def _bbox_to_object(bbox: npt.NDArray[np.float64], score: float) -> events.events_pb2.Object:
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obj = events.events_pb2.Object()
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obj.type = events.events_pb2.TypeObject.ANY
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def _bbox_to_object(bbox: npt.NDArray[np.float64], score: float) -> evt.Object:
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obj = evt.Object()
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obj.type = evt.TypeObject.ANY
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obj.top = bbox[0].astype(float)
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obj.right = bbox[3].astype(float)
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obj.bottom = bbox[2].astype(float)
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@ -1,26 +1,28 @@
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import datetime
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import typing
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import unittest.mock
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import depthai as dai
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import events.events_pb2
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import numpy as np
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import numpy.typing as npt
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import paho.mqtt.client as mqtt
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import pytest
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import pytest_mock
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import camera.depthai
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import events.events_pb2
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Object = dict[str, float]
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@pytest.fixture
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def mqtt_client(mocker: pytest_mock.MockerFixture) -> mqtt.Client:
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return mocker.MagicMock()
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return mocker.MagicMock() # type: ignore
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class TestObjectProcessor:
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@pytest.fixture
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def frame_ref(self):
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def frame_ref(self) -> events.events_pb2.FrameRef:
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now = datetime.datetime.now()
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frame_msg = events.events_pb2.FrameMessage()
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frame_msg.id.name = "robocar-oak-camera-oak"
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@ -42,7 +44,7 @@ class TestObjectProcessor:
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def raw_objects_empty(self, mocker: pytest_mock.MockerFixture) -> dai.NNData:
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raw_objects = mocker.MagicMock()
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def mock_return(name):
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def mock_return(name: str) -> typing.List[typing.Union[int, typing.List[int]]]:
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if name == "ExpandDims":
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return [[0] * 4] * 100
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elif name == "ExpandDims_2":
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@ -56,7 +58,7 @@ class TestObjectProcessor:
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@pytest.fixture
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def raw_objects_one(self, mocker: pytest_mock.MockerFixture, object1: Object) -> dai.NNData:
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def mock_return(name):
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def mock_return(name: str) -> typing.Union[npt.NDArray[np.int64], typing.List[float]]:
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if name == "ExpandDims": # Detection boxes
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boxes: list[list[float]] = [[0.] * 4] * 100
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boxes[0] = [object1["top"], object1["left"], object1["bottom"], object1["right"]]
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@ -77,20 +79,24 @@ class TestObjectProcessor:
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def object_processor(self, mqtt_client: mqtt.Client) -> camera.depthai.ObjectProcessor:
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return camera.depthai.ObjectProcessor(mqtt_client, "topic/object", 0.2)
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def test_process_without_object(self, object_processor: camera.depthai.ObjectProcessor, mqtt_client,
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raw_objects_empty, frame_ref):
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def test_process_without_object(self, object_processor: camera.depthai.ObjectProcessor, mqtt_client: mqtt.Client,
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raw_objects_empty: dai.NNData, frame_ref: events.events_pb2.FrameRef) -> None:
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object_processor.process(raw_objects_empty, frame_ref)
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mqtt_client.publish.assert_not_called()
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publish_mock: unittest.mock.MagicMock = mqtt_client.publish # type: ignore
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publish_mock.assert_not_called()
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def test_process_with_object_with_low_score(self, object_processor: camera.depthai.ObjectProcessor, mqtt_client,
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raw_objects_one, frame_ref):
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def test_process_with_object_with_low_score(self, object_processor: camera.depthai.ObjectProcessor,
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mqtt_client: mqtt.Client, raw_objects_one: dai.NNData,
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frame_ref: events.events_pb2.FrameRef) -> None:
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object_processor._objects_threshold = 0.9
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object_processor.process(raw_objects_one, frame_ref)
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mqtt_client.publish.assert_not_called()
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publish_mock: unittest.mock.MagicMock = mqtt_client.publish # type: ignore
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publish_mock.assert_not_called()
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def test_process_with_one_object(self,
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object_processor: camera.depthai.ObjectProcessor, mqtt_client,
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raw_objects_one, frame_ref, object1: Object):
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object_processor: camera.depthai.ObjectProcessor, mqtt_client: mqtt.Client,
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raw_objects_one: dai.NNData, frame_ref: events.events_pb2.FrameRef,
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object1: Object) -> None:
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object_processor.process(raw_objects_one, frame_ref)
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left = object1["left"]
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right = object1["right"]
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@ -98,7 +104,7 @@ class TestObjectProcessor:
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bottom = object1["bottom"]
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score = object1["score"]
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pub_mock: unittest.mock.MagicMock = mqtt_client.publish
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pub_mock: unittest.mock.MagicMock = mqtt_client.publish # type: ignore
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pub_mock.assert_called_once_with(payload=unittest.mock.ANY, qos=0, retain=False, topic="topic/object")
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payload = pub_mock.call_args.kwargs['payload']
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objects_msg = events.events_pb2.ObjectsMessage()
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@ -118,13 +124,13 @@ class TestFrameProcessor:
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return camera.depthai.FrameProcessor(mqtt_client, "topic/frame")
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def test_process(self, frame_processor: camera.depthai.FrameProcessor, mocker: pytest_mock.MockerFixture,
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mqtt_client: mqtt.Client):
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mqtt_client: mqtt.Client) -> None:
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img: dai.ImgFrame = mocker.MagicMock()
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mocker.patch(target="cv2.imencode").return_value = (True, np.array(b"img content"))
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frame_ref = frame_processor.process(img)
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pub_mock: unittest.mock.MagicMock = mqtt_client.publish
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pub_mock: unittest.mock.MagicMock = mqtt_client.publish # type: ignore
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pub_mock.assert_called_once_with(payload=unittest.mock.ANY, qos=0, retain=False, topic="topic/frame")
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payload = pub_mock.call_args.kwargs['payload']
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frame_msg = events.events_pb2.FrameMessage()
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@ -140,7 +146,7 @@ class TestFrameProcessor:
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milliseconds=10) < frame_msg.id.created_at.ToDatetime() < now + datetime.timedelta(milliseconds=10)
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def test_process_error(self, frame_processor: camera.depthai.FrameProcessor, mocker: pytest_mock.MockerFixture,
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mqtt_client: mqtt.Client):
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mqtt_client: mqtt.Client) -> None:
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img: dai.ImgFrame = mocker.MagicMock()
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mocker.patch(target="cv2.imencode").return_value = (False, None)
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@ -1,6 +1,6 @@
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# Python: 3.8.0 (tags/v3.8.0:fa919fd, Oct 14 2019, 19:37:50) [MSC v.1916 64 bit (AMD64)]
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# Library: cv2, version: 4.4.0
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# Module: cv2.cv2, version: 4.4.0
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# Library: cv2-stubs, version: 4.4.0
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# Module: cv2-stubs.cv2-stubs, version: 4.4.0
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import typing
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import __init__ as _mod_cv2
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6
poetry.lock
generated
6
poetry.lock
generated
@ -771,7 +771,7 @@ requests = ">=2.0.1,<3.0.0"
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[[package]]
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name = "robocar-protobuf"
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version = "1.1.1"
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version = "1.1.2"
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description = "Protobuf message definitions for robocar"
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category = "main"
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optional = false
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@ -1526,8 +1526,8 @@ requests-toolbelt = [
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{file = "requests_toolbelt-0.9.1-py2.py3-none-any.whl", hash = "sha256:380606e1d10dc85c3bd47bf5a6095f815ec007be7a8b69c878507068df059e6f"},
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]
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robocar-protobuf = [
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{file = "robocar_protobuf-1.1.1-py3-none-any.whl", hash = "sha256:d04b8e4cdacb7286d3425d74fb4402210422469e1240951921029c3dcf8c3e83"},
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{file = "robocar_protobuf-1.1.1.tar.gz", hash = "sha256:c41dfa9bcc143ea88ac38dee7c52f9672bb06f13ad1bccad3b244c32d3f12073"},
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{file = "robocar_protobuf-1.1.2-py3-none-any.whl", hash = "sha256:3f47608464576cf10377b1635aa1f2a494445c71dbca1bd7ae1e97c4d09301e6"},
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{file = "robocar_protobuf-1.1.2.tar.gz", hash = "sha256:7ae5fe6c2b53edd7314d685a5492d945ad315a5a498c1342e95a3b46bf684bbc"},
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]
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s3transfer = [
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{file = "s3transfer-0.6.0-py3-none-any.whl", hash = "sha256:06176b74f3a15f61f1b4f25a1fc29a4429040b7647133a463da8fa5bd28d5ecd"},
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