robocars/robocar-oak-camera
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build: fix all pylint/mypy errors

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This commit is contained in:
Cyrille Nofficial
2022-10-27 10:34:04 +02:00
parent 4daf4d3c23
commit 55d8ce06c6
5 changed files with 68 additions and 49 deletions
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17
camera/cli.py
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@@ -5,10 +5,12 @@ import argparse
import logging
import os
import signal
import typing, types
import depthai as dai
import paho.mqtt.client as mqtt
from . import depthai as cam
from . import depthai as cam # pylint: disable=reimported
logger = logging.getLogger(__name__)
logging.basicConfig(level=logging.INFO)
@@ -54,7 +56,7 @@ def _parse_args_cli() -> argparse.Namespace:
return args
def _init_mqtt_client(broker_host: str, broker_port, user: str, password: str, client_id: str) -> mqtt.Client:
def _init_mqtt_client(broker_host: str, broker_port: int, user: str, password: str, client_id: str) -> mqtt.Client:
logger.info("Start part.py-robocar-oak-camera")
client = mqtt.Client(client_id=client_id, clean_session=True, userdata=None, protocol=mqtt.MQTTv311)
@@ -85,10 +87,17 @@ def execute_from_command_line() -> None:
objects_topic=args.mqtt_topic_robocar_objects,
objects_threshold=args.objects_threshold)
pipeline = dai.Pipeline()
pipeline_controller = cam.PipelineController(frame_processor=frame_processor,
object_processor=object_processor)
object_processor=object_processor,
object_node=cam.ObjectDetectionNN(pipeline=pipeline),
camera=cam.CameraSource(pipeline=pipeline,
img_width=args.image_width,
img_height=args.image_width,
))
def sigterm_handler():
def sigterm_handler(signum: int, frame: typing.Optional[
types.FrameType]) -> None: # pylint: disable=unused-argument # need to implement handler signature
logger.info("exit on SIGTERM")
pipeline_controller.stop()

50
camera/depthai.py
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@@ -4,15 +4,17 @@ Camera event loop
import abc
import datetime
import logging
import pathlib
import typing
from dataclasses import dataclass
import cv2
import depthai as dai
import events.events_pb2
import events.events_pb2 as evt
import numpy as np
import numpy.typing as npt
import paho.mqtt.client as mqtt
from depthai import Device
logger = logging.getLogger(__name__)
@@ -31,7 +33,7 @@ class ObjectProcessor:
self._objects_topic = objects_topic
self._objects_threshold = objects_threshold
def process(self, in_nn: dai.NNData, frame_ref) -> None:
def process(self, in_nn: dai.NNData, frame_ref: evt.FrameRef) -> None:
"""
Parse and publish result of NeuralNetwork result
:param in_nn: NeuralNetwork result read from device
@@ -48,8 +50,8 @@ class ObjectProcessor:
if boxes.shape[0] > 0:
self._publish_objects(boxes, frame_ref, scores)
def _publish_objects(self, boxes: npt.NDArray[np.float64], frame_ref, scores: npt.NDArray[np.float64]) -> None:
objects_msg = events.events_pb2.ObjectsMessage()
def _publish_objects(self, boxes: npt.NDArray[np.float64], frame_ref: evt.FrameRef, scores: npt.NDArray[np.float64]) -> None:
objects_msg = evt.ObjectsMessage()
objs = []
for i in range(boxes.shape[0]):
logger.debug("new object detected: %s", str(boxes[i]))
@@ -105,7 +107,7 @@ class FrameProcessor:
byte_im = im_buf_arr.tobytes()
now = datetime.datetime.now()
frame_msg = events.events_pb2.FrameMessage()
frame_msg = evt.FrameMessage()
frame_msg.id.name = "robocar-oak-camera-oak"
frame_msg.id.id = str(int(now.timestamp() * 1000))
frame_msg.id.created_at.FromDatetime(now)
@@ -149,7 +151,7 @@ class ObjectDetectionNN:
def __init__(self, pipeline: dai.Pipeline):
# Define a neural network that will make predictions based on the source frames
detection_nn = pipeline.createNeuralNetwork()
detection_nn.setBlobPath(_NN_PATH)
detection_nn.setBlobPath(pathlib.Path(_NN_PATH))
detection_nn.setNumPoolFrames(4)
detection_nn.input.setBlocking(False)
detection_nn.setNumInferenceThreads(2)
@@ -230,7 +232,7 @@ class MqttConfig:
class MqttSource(Source):
"""Image source based onto mqtt stream"""
def __init__(self, device: dai.Device, pipeline: dai.Pipeline, mqtt_config: MqttConfig):
def __init__(self, device: Device, pipeline: dai.Pipeline, mqtt_config: MqttConfig):
self._mqtt_config = mqtt_config
self._client = mqtt.Client()
self._client.user_data_set(mqtt_config)
@@ -264,7 +266,7 @@ class MqttSource(Source):
# pylint: disable=unused-argument
def _on_message(self, _: mqtt.Client, user_data: MqttConfig, msg: mqtt.MQTTMessage) -> None:
frame_msg = events.events_pb2.FrameMessage()
frame_msg = evt.FrameMessage()
frame_msg.ParseFromString(msg.payload)
frame = np.asarray(frame_msg.frame, dtype="uint8")
@@ -276,11 +278,11 @@ class MqttSource(Source):
def get_stream_name(self) -> str:
return self._img_out.getStreamName()
def link(self, input_node: dai.Node.Input):
def link(self, input_node: dai.Node.Input) -> None:
self._img_in.out.link(input_node)
def _to_planar(arr: npt.NDArray[int], shape: tuple[int, int]) -> list[int]:
def _to_planar(arr: npt.NDArray[np.uint8], shape: tuple[int, int]) -> list[int]:
return [val for channel in cv2.resize(arr, shape).transpose(2, 0, 1) for y_col in channel for val in y_col]
@@ -316,17 +318,19 @@ class PipelineController:
:return:
"""
# Connect to device and start pipeline
with dai.Device(pipeline=self._pipeline) as device:
logger.info('MxId: %s', device.getDeviceInfo().getMxId())
logger.info('USB speed: %s', device.getUsbSpeed())
logger.info('Connected cameras: %s', str(device.getConnectedCameras()))
logger.info("output queues found: %s", str(device.getOutputQueueNames()))
with Device(pipeline=self._pipeline) as dev:
logger.info('MxId: %s', dev.getDeviceInfo().getMxId())
logger.info('USB speed: %s', dev.getUsbSpeed())
logger.info('Connected cameras: %s', str(dev.getConnectedCameras()))
logger.info("output queues found: %s", str(''.join(dev.getOutputQueueNames()))) # type: ignore
device.startPipeline()
dev.startPipeline()
# Queues
queue_size = 4
q_rgb = device.getOutputQueue(name=self._camera.get_stream_name(), maxSize=queue_size, blocking=False)
q_nn = device.getOutputQueue(name=self._object_node.get_stream_name(), maxSize=queue_size, blocking=False)
q_rgb = dev.getOutputQueue(name=self._camera.get_stream_name(), maxSize=queue_size, # type: ignore
blocking=False)
q_nn = dev.getOutputQueue(name=self._object_node.get_stream_name(), maxSize=queue_size, # type: ignore
blocking=False)
self._stop = False
while True:
@@ -343,14 +347,14 @@ class PipelineController:
logger.debug("wait for new frame")
# Wait for frame
in_rgb: dai.ImgFrame = q_rgb.get() # blocking call, will wait until a new data has arrived
in_rgb: dai.ImgFrame = q_rgb.get() # type: ignore # blocking call, will wait until a new data has arrived
try:
frame_ref = self._frame_processor.process(in_rgb)
except FrameProcessError as ex:
logger.error("unable to process frame: %s", str(ex))
return
# Read NN result
in_nn: dai.NNData = q_nn.get()
in_nn: dai.NNData = q_nn.get() # type: ignore
self._object_processor.process(in_nn, frame_ref)
def stop(self) -> None:
@@ -361,9 +365,9 @@ class PipelineController:
self._stop = True
def _bbox_to_object(bbox: npt.NDArray[np.float64], score: float) -> events.events_pb2.Object:
obj = events.events_pb2.Object()
obj.type = events.events_pb2.TypeObject.ANY
def _bbox_to_object(bbox: npt.NDArray[np.float64], score: float) -> evt.Object:
obj = evt.Object()
obj.type = evt.TypeObject.ANY
obj.top = bbox[0].astype(float)
obj.right = bbox[3].astype(float)
obj.bottom = bbox[2].astype(float)

40
camera/tests/test_depthai.py
View File

@@ -1,26 +1,28 @@
import datetime
import typing
import unittest.mock
import depthai as dai
import events.events_pb2
import numpy as np
import numpy.typing as npt
import paho.mqtt.client as mqtt
import pytest
import pytest_mock
import camera.depthai
import events.events_pb2
Object = dict[str, float]
@pytest.fixture
def mqtt_client(mocker: pytest_mock.MockerFixture) -> mqtt.Client:
return mocker.MagicMock()
return mocker.MagicMock() # type: ignore
class TestObjectProcessor:
@pytest.fixture
def frame_ref(self):
def frame_ref(self) -> events.events_pb2.FrameRef:
now = datetime.datetime.now()
frame_msg = events.events_pb2.FrameMessage()
frame_msg.id.name = "robocar-oak-camera-oak"
@@ -42,7 +44,7 @@ class TestObjectProcessor:
def raw_objects_empty(self, mocker: pytest_mock.MockerFixture) -> dai.NNData:
raw_objects = mocker.MagicMock()
def mock_return(name):
def mock_return(name: str) -> typing.List[typing.Union[int, typing.List[int]]]:
if name == "ExpandDims":
return [[0] * 4] * 100
elif name == "ExpandDims_2":
@@ -56,7 +58,7 @@ class TestObjectProcessor:
@pytest.fixture
def raw_objects_one(self, mocker: pytest_mock.MockerFixture, object1: Object) -> dai.NNData:
def mock_return(name):
def mock_return(name: str) -> typing.Union[npt.NDArray[np.int64], typing.List[float]]:
if name == "ExpandDims": # Detection boxes
boxes: list[list[float]] = [[0.] * 4] * 100
boxes[0] = [object1["top"], object1["left"], object1["bottom"], object1["right"]]
@@ -77,20 +79,24 @@ class TestObjectProcessor:
def object_processor(self, mqtt_client: mqtt.Client) -> camera.depthai.ObjectProcessor:
return camera.depthai.ObjectProcessor(mqtt_client, "topic/object", 0.2)
def test_process_without_object(self, object_processor: camera.depthai.ObjectProcessor, mqtt_client,
raw_objects_empty, frame_ref):
def test_process_without_object(self, object_processor: camera.depthai.ObjectProcessor, mqtt_client: mqtt.Client,
raw_objects_empty: dai.NNData, frame_ref: events.events_pb2.FrameRef) -> None:
object_processor.process(raw_objects_empty, frame_ref)
mqtt_client.publish.assert_not_called()
publish_mock: unittest.mock.MagicMock = mqtt_client.publish # type: ignore
publish_mock.assert_not_called()
def test_process_with_object_with_low_score(self, object_processor: camera.depthai.ObjectProcessor, mqtt_client,
raw_objects_one, frame_ref):
def test_process_with_object_with_low_score(self, object_processor: camera.depthai.ObjectProcessor,
mqtt_client: mqtt.Client, raw_objects_one: dai.NNData,
frame_ref: events.events_pb2.FrameRef) -> None:
object_processor._objects_threshold = 0.9
object_processor.process(raw_objects_one, frame_ref)
mqtt_client.publish.assert_not_called()
publish_mock: unittest.mock.MagicMock = mqtt_client.publish # type: ignore
publish_mock.assert_not_called()
def test_process_with_one_object(self,
object_processor: camera.depthai.ObjectProcessor, mqtt_client,
raw_objects_one, frame_ref, object1: Object):
object_processor: camera.depthai.ObjectProcessor, mqtt_client: mqtt.Client,
raw_objects_one: dai.NNData, frame_ref: events.events_pb2.FrameRef,
object1: Object) -> None:
object_processor.process(raw_objects_one, frame_ref)
left = object1["left"]
right = object1["right"]
@@ -98,7 +104,7 @@ class TestObjectProcessor:
bottom = object1["bottom"]
score = object1["score"]
pub_mock: unittest.mock.MagicMock = mqtt_client.publish
pub_mock: unittest.mock.MagicMock = mqtt_client.publish # type: ignore
pub_mock.assert_called_once_with(payload=unittest.mock.ANY, qos=0, retain=False, topic="topic/object")
payload = pub_mock.call_args.kwargs['payload']
objects_msg = events.events_pb2.ObjectsMessage()
@@ -118,13 +124,13 @@ class TestFrameProcessor:
return camera.depthai.FrameProcessor(mqtt_client, "topic/frame")
def test_process(self, frame_processor: camera.depthai.FrameProcessor, mocker: pytest_mock.MockerFixture,
mqtt_client: mqtt.Client):
mqtt_client: mqtt.Client) -> None:
img: dai.ImgFrame = mocker.MagicMock()
mocker.patch(target="cv2.imencode").return_value = (True, np.array(b"img content"))
frame_ref = frame_processor.process(img)
pub_mock: unittest.mock.MagicMock = mqtt_client.publish
pub_mock: unittest.mock.MagicMock = mqtt_client.publish # type: ignore
pub_mock.assert_called_once_with(payload=unittest.mock.ANY, qos=0, retain=False, topic="topic/frame")
payload = pub_mock.call_args.kwargs['payload']
frame_msg = events.events_pb2.FrameMessage()
@@ -140,7 +146,7 @@ class TestFrameProcessor:
milliseconds=10) < frame_msg.id.created_at.ToDatetime() < now + datetime.timedelta(milliseconds=10)
def test_process_error(self, frame_processor: camera.depthai.FrameProcessor, mocker: pytest_mock.MockerFixture,
mqtt_client: mqtt.Client):
mqtt_client: mqtt.Client) -> None:
img: dai.ImgFrame = mocker.MagicMock()
mocker.patch(target="cv2.imencode").return_value = (False, None)