def __init__(self,
routePoints,
sensorsAlgorithms={'Vision': [VisionDetectSVM]},
avoidClass=FixAvoid,
comunication=AirSimCommunication,
fusionAlgorithm=FusionData_Mean,
configPath='config.yml',
startPoint=None):
Thread.__init__(self)
self.start_point = startPoint
self.status = 'start'
# vehicleComunication = comunication.getVehicle()
# Conectando ao simulador AirSim
self.vehicleComunication = AirSimCommunication()
self.control = Control(self.vehicleComunication, routePoints)
self.unrealControl = UnrealCommunication()
self.stop = False
with open(configPath, 'r') as file_config:
self.config = yaml.full_load(file_config)
if avoidClass is not None:
self.avoidThread = avoidClass(self, self.control)
if sensorsAlgorithms is not None:
self.detect = Detect(self,
self.vehicleComunication,
sensorsAlgorithms,
self.avoidThread,
fusionAlgorithm=fusionAlgorithm)
def detect(self):
# 呼叫Detect.py檔，做rule-base偵測
Det = Detect(self.filename_pro)
Det.process()
Det.trend()
self.data_rule_df = Det.signal()
Det.result()
self.save(self.data_rule_df, self.filename_rule, 'csv')
def __init__(self, parent=None):
super().__init__(parent)
self.timer_camera = QtCore.QTimer()
self.set_ui()
self.slot_init()
self.TIME = 0
self.detector = Detect()
self.sgbm = SGBM()
self.sgbm.Init_SGBM()
self.Camera = cv.VideoCapture()
self.CAM_NUM = 1
def __init__(self, song):
self.audio = Audio()
self.audio.preOpen()
self.detect = Detect()
pygame.init()
self.audio.open()
self.song = LoadSong(song).song
pygame.display.set_mode((WIDTH, HEIGHT))
pygame.display.set_caption('DanceDanceCV')
screen = pygame.display.get_surface()
self.view = View(screen, self.detect, self.song)
def detect_key(wav_location):
D = Detect()
bpm = D.detect(wav_location)
sys.exit(1)
score = music21.converter.parse(os.getcwd() + '/' + file_name)
key1 = score.analyze('Krumhansl')
key2 = score.analyze('AardenEssen')
if key1 != key2:
print(key1, key2)
else:
print(key1)
def __init__(self):
QtWidgets.QMainWindow.__init__(self)
Ui_MainWindow.__init__(self)
self.setupUi(self)
self.detect = Detect()
self.original_image = None
self.after_image = None
self.pix_map = None
self.start = False
self.start_point = None
self.end_point = None
def btn_click(self):
object_target = self.lbl_image_after
object_origin_name = self.sender().objectName()
no_line = self.get_boolean(self.ck_noline.checkState())
cut = self.get_boolean(self.ck_cut.checkState())
join = self.get_boolean(self.ck_join.checkState())
p_font = self.get_boolean(self.ck_print.checkState())
threshold_binary = int(self.sb_binary_value.text())
threshold_ratio = float(self.sb_ratio_value.text())
rect_char = RectChar(no_line, cut, join, p_font, threshold_binary,
threshold_ratio)
gray_image = rect_char.get_gray_image(self.original_image)
binary_image = rect_char.get_binary_image(gray_image)
result_list = rect_char.get_char_list(binary_image)
result_image = None
if object_origin_name == "btn_split":
print("123")
elif object_origin_name == "btn_gray":
result_image = self.get_pix_from_mat(gray_image,
object_target.width(),
object_target.height())
elif object_origin_name == "btn_brinary":
result_image = self.get_pix_from_mat(binary_image,
object_target.width(),
object_target.height())
elif object_origin_name == "btn_location":
result_image = self.original_image.copy()
for char in result_list:
cv2.rectangle(result_image, (char[0], char[1]),
(char[2], char[3]), (0, 0, 255))
result_image = self.get_pix_from_mat(result_image,
object_target.width(),
object_target.height())
elif object_origin_name == "btn_recognize":
image_list = []
rect_temp = None
for rect in result_list:
if rect_temp is not None and (rect_temp[2] > rect[0]
and rect_temp[1] < rect[3]):
image_list.append(None)
image_list.append(
gray_image[rect[1]:rect[3], rect[0]:rect[2], :] / 255)
rect_temp = rect
detect = Detect()
result_str = detect.find_class(image_list)
self.text_result.setText(result_str)
print(result_str)
if result_image is not None:
object_target.setPixmap(result_image)
cap = cv2.VideoCapture(cv2.CAP_DSHOW)
while True:
ret, image = cap.read()
if ret:
no_mask_faces = []
# Cal Frame
curTime = time.time()
sec = curTime - prevTime
prevTime = curTime
fps = 1 / (sec)
print(fps)
Mask_Detect = Detect(image)
# Detect Face
Mask_Detect.detectFace()
if len(Mask_Detect.face_lst) != 0:
# Detect Mask & NOSE & MASK IN FACE
Mask_Detect.detectMaskNose()
# 조건에 맞게 결과 도출
for face_info in Mask_Detect.face_lst:
x1, y1, x2, y2 = face_info["roi_face"]
mask_status = face_info["with_mask"]
nose_status = face_info["with_nose"]
color = (0, 0, 0)
for nX in range(length):
if each_col[nX] ^ start:
if start is False:
start = True
start_index = nX
else:
start = False
col_list.append([start_index, nX])
return col_list
if __name__ == '__main__':
image = cv2.imread("汉字_手写.jpg")
from Detect import Detect
rect_char = RectChar()
gray_image = rect_char.get_gray_image(image)
binary_image = rect_char.get_binary_image(gray_image)
result_list = rect_char.get_char_list(binary_image)
image_list = []
rect_temp = None
for rect in result_list:
if rect_temp is not None and (rect_temp[2] > rect[0]
and rect_temp[1] < rect[3]):
image_list.append(None)
image_list.append(image[rect[1]:rect[3], rect[0]:rect[2], :] / 255)
rect_temp = rect
detect = Detect()
result = detect.find_class(image_list)
print(result)
import os
import sys
import cv2 as cv
from Detect import Detect
from SGBM import SGBM
from time import time
import numpy as np
detector = Detect()
detector.Init_Net()
sgbm = SGBM()
sgbm.Init_SGBM()
Camera = cv.VideoCapture(1)
if not Camera.isOpened():
print("Could not open the Camera")
sys.exit()
ret, Fream = Camera.read()
cv.imwrite("Two.jpg", Fream)
os.system("./camera.sh")
def SegmentFrame(Fream):
double = cv.resize(Fream, (640, 240), cv.INTER_AREA)
left = double[0:240, 0:320]
right = double[0:240, 320:640]
return left, right
while (True):
