def slabDim(dimCameraLiink):
global lookForOcr
#print(lookForOcr)
global timeOver
global valCsv
global ui
global Ui_MainWindow
lookForOcr = False
timeOver = 0
#alarRef = [410,1165,2165,1165]
alarRef = [365, 1165, 2200, 1165] # 1_june_2020(10.51_am)
#alar = [alarRef[0],alarRef[1]-40,alarRef[2],alarRef[3]-40]
alar = [alarRef[0], alarRef[1] - 80, alarRef[2], alarRef[3] - 80]
#alarRef = [330,820,1585,820] # trail_ggjh
#alar = [alarRef[0],alarRef[1]-40,alarRef[2],alarRef[3]-40] # # trail_ggjh
dB = dist.euclidean(alarRef[:2], alarRef[-2:])
#dB = alar[2]-alar[0]
#print(str(dB)+'====sub')
pixelsPerMetric = dB / 1690 #(pixel/mm)
#print(str(pixelsPerMetric)+'***pixelPerMetric')
print(str(1 / pixelsPerMetric) + '--------mmPerPixel')
valCsv = []
dim = cv2.VideoCapture(dimCameraLiink)
#dim = cv2.VideoCapture("C:/Users/CCTV/Desktop/Videos/1280.mov")
dim.set(cv2.CAP_PROP_BUFFERSIZE, 10)
#dim = cv2.VideoCapture('rtsp://*****:*****@10.152.235.180')
#dim.set(cv2.CAP_PROP_POS_FRAMES,1)
while (True):
#st1 = time.time()
ret, img_dim = dim.read()
val = Ui_MainWindow.retunValue()
alarRef = [365, 1165 + val, 2200, 1165 + val] # 05_june_2020(12.20_pm)
alar = [alarRef[0], alarRef[1] - 80, alarRef[2], alarRef[3] - 80]
#img_dim[:,2485:] = 0
#img_dim[:,0:100] = 0
if ret == False:
#print((time.time()-st1)*1000,"ms---")
print(
"Slab camera Video could not be fetched --- Kindly re-run the application"
)
print(time.strftime("%Y-%m-%d(%H_%M_%S)"))
dim = cv2.VideoCapture(dimCameraLiink)
#dim.set(cv2.CAP_PROP_BUFFERSIZE, 10)
continue
#img_dim = imutils.rotate_bound(img_dim,.5)
thresh = threshOP(
img_dim
) #----------------------------------------------------------------------
#if np.count_nonzero(thresh[alar[1],]) >= 550: # traila_igjyg
if np.count_nonzero(thresh[alar[1], ]) >= 950 and lookForOcr == False:
mmPPix, img_dim = mmPerPix(
img_dim, thresh, alar, pixelsPerMetric
) #-----------------------------------------------------
valCsv.append(mmPPix)
'''if len(valCsv) > 5 and len(valCsv) < 150:
t3 = threading.Thread(target=ui.updateGraph,args=(valCsv,))
t3.start()
t3.join()
if (len(valCsv) % 6) == 0:
ui.updateGraph(valCsv)
dim = cv2.VideoCapture(dimCameraLiink)'''
# considaring we have a longest slab
if len(valCsv) > 150:
if lookForOcr == False:
lookForOcr = True
timeOver = time.time()
print(
'----------------------------------------------max value reached >150'
)
print(lookForOcr, "<-look for ocr")
ui.updateGraph(valCsv)
#dim = cv2.VideoCapture(dimCameraLiink)
#dim.set(cv2.CAP_PROP_BUFFERSIZE, 10)
# slab passes the ROI
#if np.count_nonzero(thresh[alar[1]+30,]) <= 550 and np.count_nonzero(thresh[alar[1]-30,]) <= 550: # trail_jkghjvjhg
if np.count_nonzero(
thresh[alar[1] + 30, ]) <= 950 and np.count_nonzero(
thresh[alar[1] - 30, ]) <= 950:
if len(valCsv) > 60:
if lookForOcr == False:
lookForOcr = True
timeOver = time.time()
#writeCSV(valCsv)
#valCsv = []
print("+++++++++++++++++++++++++ slab over")
print(lookForOcr, "<-look for ocr")
ui.updateGraph(valCsv)
#dim = cv2.VideoCapture(dimCameraLiink)
#dim.set(cv2.CAP_PROP_BUFFERSIZE, 10)
else:
None
#valCsv = []
# Ref line
#img_dim = cv2.line(img_dim ,(alar[0] ,alar[1]+60),(alar[2] ,alar[3]+60),(250,0,0),4) # ref line
img_dim = cv2.line(img_dim, (alarRef[0], alarRef[1]),
(alarRef[2], alarRef[3]), (255, 0, 0),
4) # ref line
img_dim = cv2.resize(img_dim, (int(1200), int(700)))
img_dim = cv2.cvtColor(img_dim, cv2.COLOR_BGR2RGB)
img_dim = np.require(img_dim, np.uint8, 'C')
ui.showImg1(img_dim)
#dim = cv2.VideoCapture(dimCameraLiink)
#dim.set(cv2.CAP_PROP_BUFFERSIZE, 10)
#continue
# Resize
#img_dim1 = cv2.resize(img_dim ,(int(1200),int(700)))
#thresh1 = cv2.resize(thresh,(int(1920/2),int(1080/2)))
#cv2.imshow('img_dim ',img_dim1)
#cv2.imshow(' thrsh ',thresh1)
#key = cv2.waitKey(1) & 0xFF
#print((time.time()-st1)*1000,"ms---")
'''if key == ord('q'):
