debug = not args.no_debug
camera = not args.video
if args.camera and args.video:
raise ValueError(
'Incorrect command line parameters! "-cam" cannot be used with "-vid"!'
)
elif args.camera is False and args.video is None:
raise ValueError(
'Missing inference source! Either use "-cam" to run on DepthAI camera or "-vid <path>" to run on video file'
)
parentDir = Path(__file__).parent
shaves = 6 if args.camera else 8
blobconverter.set_defaults(output_dir=parentDir / Path("models"))
def timer(function):
"""
Decorator function timer
:param function:The function you want to time
:return:
"""
def wrapper(*args, **kwargs):
time_start = time.time()
res = function(*args, **kwargs)
cost_time = time.time() - time_start
print("【 %s 】operation hours：【 %s 】second" %
(function.__name__, cost_time))
return res
# coding=utf-8
import time
from pathlib import Path
import blobconverter
import click
import cv2
import depthai as dai
import numpy as np
from depthai_sdk import getDeviceInfo, FPSHandler, toTensorResult
from loguru import logger
from utils import run_nn, get_mini_box_frame, drawText
blobconverter.set_defaults(output_dir=Path(__file__).parent / Path("models"),
optimizer_params=None)
preview_size = (1080, 1080)
def create_pipeline(video):
pipeline = dai.Pipeline()
# pipeline.setOpenVINOVersion(dai.OpenVINO.VERSION_2021_4)
mesh = pipeline.create(dai.node.NeuralNetwork)
mesh.setBlobPath("models/face_landmark_openvino_2021.4_6shave.blob")
mesh.setNumInferenceThreads(2)
mesh.input.setBlocking(False)
mesh.input.setQueueSize(2)
if video:
'Artifactory password, can be also set using env variable ARTIFACTORY_PASSWORD',
default=os.getenv('ARTIFACTORY_PASSWORD'))
parser.add_argument(
'-url',
'--blobconverter-url',
type=str,
help="URL to custom BlobConverter URL to be used for conversion",
required=False)
args = parser.parse_args()
if None in (args.username, args.password):
parser.print_help()
sys.exit(1)
if args.blobconverter_url is not None:
blobconverter.set_defaults(url=args.blobconverter_url)
path = ArtifactoryPath(
"https://artifacts.luxonis.com/artifactory/blobconverter-backup/blobs",
auth=(args.username, args.password))
if not path.exists():
path.mkdir()
priority_models = [
"mobilenet-ssd", "efficientnet-b0",
"vehicle-license-plate-detection-barrier-0106",
"vehicle-detection-adas-0002", "license-plate-recognition-barrier-0007"
"vehicle-attributes-recognition-barrier-0039",
"face-detection-retail-0004", "landmarks-regression-retail-0009"
]
backup_shaves = range(1, 17)
