new

asd

D_copy.py

@@ -5,7 +5,6 @@
 import time
 import threading
 import math
-
 tempoGB = 0
 statusSemaforo = 'null'
 extent = False
@@ -40,17 +39,17 @@ def Calculating_time_extent(classes):
  global extent
  global semaforoAberto
 
- if tempoGB == 0 and tempoGB < 10:
- tempoGB = 10
+ if tempoGB == 0 and tempoGB < 20:
+ tempoGB = 20
  extent = False
  t1 = threading.Thread(target=thread_delay, args=(0,))
  t1.start()
  print("TEMPO: PESSOA ", tempoGB)
  # Text = 'TEMPO PARA PESSOA: '
  # cv2.putText(frame, Text+str(tempoGB)+'s', (0, 25),
  # cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 150, 0), 3)
- if classes == "chair" and extent == False and tempoGB < 15:
- tempoGB += 5
+ if classes == "chair" and extent == False and tempoGB < 30:
+ tempoGB += 10
  print("TEMPO: CADEIRANTE ", tempoGB)
  extent = True
  # cv2.putText(frame, Text+str(tempoGB)+'s', (0, 25),
@@ -133,13 +132,13 @@ def createBoxes(_img, i, _confidences, _boxes, _COLORS, _LABELS, _AllClassesID):
 # CAPTURA FRAME A FRAME
 def DetectionX():
  # ARQUIVOS
- input_file = 'arquivos/carros1.mp4'
+ input_file = 'arquivos/lv1.mp4'
  weights_path = 'arquivos/yolov4-tiny.weights'
  cfg_path = 'arquivos/yolov4-tiny.cfg'
  names_path = 'arquivos/coco.names'
  # CONFIG PRECISÃO
- threshold = 0.6 # Nivel de confiança?
- threshold_NMS = 0.6
+ threshold = 0.3 # Nivel de confiança?
+ threshold_NMS = 0.4
  font_smal, font_big = 0.4, 0.6
  font_tipe = cv2.FONT_HERSHEY_SIMPLEX
  fontLine = 2 # inteiro
@@ -194,6 +193,7 @@ def DetectionX():
 
  if len(objects) > 0:
  for i in objects.flatten():
+
  Calculating_time_extent(LABELS[AllClassesID[i]])
 
  if semaforoAberto:
@@ -205,12 +205,21 @@ def DetectionX():
 
  cv2.putText(_frame, "TEMPO: "+str(count)+'s', (0, 25),
  cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 150, 0), 3)
- cv2.putText(_frame, "SEMAFORO: "+str(semaforoAberto), (0, 50),
- cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 150), 2)
+ cv2.putText(_frame, "SEMAFORO: "+str(semaforoAberto), (0, 60),
+ cv2.FONT_HERSHEY_SIMPLEX, 1, (255, 255, 255), 2)
 
  # t1 = threading.Thread(target=thread_delay, args=(5,))
  # t1.start()
  # print(tempoGB)
+ if semaforoAberto:
+ semaforoImage = cv2.imread("arquivos/sTrue.png")
+ cv2.putText(_frame, "N DETECCOES: "+str(len(AllBoxes)), (0, 100),
+ cv2.FONT_HERSHEY_SIMPLEX, 1, (255, 255, 255), 2)
+
+ else:
+ semaforoImage = cv2.imread("arquivos/sFalse.png")
+ cv2.imshow('SEMAFORO', semaforoImage)
+
  imageShow(_frame)
 
 

D_video.py

@@ -3,13 +3,13 @@
 import time
 
 # ARQUIVOS
-input_file = 'arquivos/carros1.mp4'
+input_file = 'arquivos/s1.mp4'
 weights_path = 'arquivos/yolov4-tiny.weights'
 cfg_path = 'arquivos/yolov4-tiny.cfg'
 names_path = 'arquivos/coco.names'
 # CONFIG PRECISÃO
-threshold = 0.8 # Nivel de confiança?
-threshold_NMS = 0.3
+threshold = 0.3 # Nivel de confiança?
+threshold_NMS = 0.2
 font_smal, font_big = 0.4, 0.6
 font_tipe = cv2.FONT_HERSHEY_SIMPLEX
 fontLine = 2 # inteiro
@@ -72,7 +72,7 @@ def blobImage(net, img):
  net.setInput(blob)
  layer_Outputs = net.forward(ln)
  end = time.time()
- print("[TEMPO DE DETECÇÃO] {:.2f} seconds".format(end - start))
+ #print("[TEMPO DE DETECÇÃO] {:.2f} seconds".format(end - start))
  return net, img, layer_Outputs
 
 
@@ -151,8 +151,8 @@ def createBoxes(_img, i, _confidences, _boxes, _COLORS, _LABELS, _AllClassesID):
  _frame, i, AllConfidences, AllBoxes, COLORS, LABELS, AllClassesID)
  objects = imageCopy[y:y+h, x:x+w]
 
- cv2.putText(_frame, "PROCSSAMENTO {:.2f}s".format(time.time()-t),
- (20, video_height-20), font_tipe, font_big, (255, 255, 255), fontLine, lineType=cv2.LINE_AA)
+ # cv2.putText(_frame, "PROCSSAMENTO {:.2f}s".format(time.time()-t),
+ # (20, video_height-20), font_tipe, font_big, (255, 255, 255), fontLine, lineType=cv2.LINE_AA)
 
  cv2.imshow("frame", _frame)