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# -*- coding: cp936 -*-
import sys
import threading #線程模塊
import cv2
import numpy as np
import time
import os
import sys
from PyQt5 import Qt
from PyQt5 import QtCore
from PyQt5.QtGui import QImage, QPixmap,QFont,QIcon
from PyQt5.QtWidgets import (QApplication,QDialog, QFileDialog, QGridLayout,
QLabel, QPushButton,QHBoxLayout,QFrame,QWidget,QLineEdit)
font = cv2.FONT_HERSHEY_SIMPLEX #設置字體
class Work(threading.Thread):
def __init__(self, caller):
threading.Thread.__init__(self)
self.caller = caller #父類調用者
self.isHaveFire = False #全局變量是否檢測到火焰
def run(self): #線程啟動后自動調用此函數
cap = cv2.VideoCapture()#初始化VideoCapture類對象
if(self.caller.video_flag == 1):#標志位為1，對應打開攝像頭
cap = cv2.VideoCapture(0) #打開攝像頭
print("打開攝像頭")
else: #標志位為1，對應打開視頻文件
cap = cv2.VideoCapture(self.caller.video_path)#打開對應路徑的視頻文件
print("打開視頻文件%s"%self.caller.video_path)
while(1):
if(self.caller.flag): #如果視頻結束標志位為1，則退出并清空圖像
bgImg = np.ones((640,480,3),np.uint8)*240
self.showViewImg(self.caller.label, bgImg)
break
ret, frame = cap.read() #讀取視頻或攝像頭幀
if(ret==False):#取幀失敗，提示退出循環
print("攝像頭打開失敗！" )
break
time.sleep(0.001)
frame = self.fire_detect(frame)#調用火焰檢測函數
frameTest = frame.copy()#原圖備份
self.showViewImg(self.caller.label, frame)
cap.release()#釋放VideoCapture類對象
def showViewImg(self,label,img):
# 提取圖像的尺寸和通道, 用于將opencv下的image轉換成Qimage
#self.label.clear()
channel = 1
height = width = 1
try:
height, width, channel = img.shape
except:
channel = 1
showImg = None
if channel != 3:
showImg = cv2.cvtColor(img,cv2.COLOR_GRAY2BGR)
else:
showImg = img.copy()
bytesPerLine = 3 * width
qImg = QImage(showImg.data, width, height, bytesPerLine,
QImage.Format_RGB888).rgbSwapped()
# 將Qimage顯示出來
label.setPixmap(QPixmap.fromImage(qImg))
def img_detect(self,img):#加載圖片檢測火焰
print("Image Test")
frame = self.fire_detect(img)#調用檢測火焰函數
self.showViewImg(self.caller.label, frame)
def fire_detect(self,frame): #火焰檢測函數，核心算法
self.isHaveFire = False #初始化火焰檢測結果標志位False
redThres = 49 #紅色閾值
sat = 7 #比例系數
blackImg = np.zeros((frame.shape[0],frame.shape[1],1),np.uint8)#創建原圖同大小的黑色圖像
b,g,r = cv2.split(frame)#通道分離
for i in range(0,frame.shape[0]): #訪問所有行
for j in range(0,frame.shape[1]): #訪問所有列
B = int(b[i,j])#訪問第i行，第j列藍色像素值
G = int(g[i,j])#訪問第i行，第j列綠色像素值
R = int(r[i,j])#訪問第i行，第j列紅色像素值
maxValue = max(max(B,G),R)#求RBG像素最大值
minValue = min(min(B,G),R)#求RBG像素最小值
if (R+G+B) == 0:
break
S = (1-3.0*minValue/(R+G+B))#計算S值
if(R>redThres and R>=G and G>=B and S>((255-R)*sat/redThres)):#火焰像素刪選
blackImg[i,j] = 255 #滿足火焰像素，黑色圖像對應位置變為白色
else:
blackImg[i,j] = 0 #不滿足火焰像素，黑色圖像對應位置仍為黑色
blackImg = cv2.medianBlur(blackImg,5)#中值濾波濾除小雜訊
k1=np.ones((5,5), np.uint8)#指定膨脹核大小5*5
blackImg = cv2.dilate(blackImg, k1, iterations=1)#膨脹
#查找火焰部分輪廓
contours,hierarchy = cv2.findContours(blackImg, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)
index = -1
maxArea = 0
for i in range (0,len(contours)):#遍歷輪廓
(x0, y0, w0, h0) = cv2.boundingRect(contours[i])#獲取輪廓外界矩形
if(w0>10 and h0>10):#刪選外界矩形寬高均大于10
#cv2.rectangle(frame,(x0,y0),(x0+w0,y0+h0),(0,255,0),2)
if(w0*h0>maxArea):#比對輪廓面積
maxArea = w0*h0 #獲取最大面積
index = i #獲取最大面積對應的輪廓序號
if index != -1: #輪廓序號變化了說明沒檢測到火焰
area = cv2.contourArea(contours[index])#獲取火焰輪廓對應的面積
cv2.putText(frame,("FireArea=%0.2f"%(area)), (5,20), font, 0.7, (0,255,0), 2)#圖片上輸出面積
(x0, y0, w0, h0) = cv2.boundingRect(contours[index])#獲取外界矩形
cv2.rectangle(frame,(x0,y0),(x0+w0,y0+h0),(0,255,0),2)#繪制外界矩形框出火焰區域
self.isHaveFire = True #檢測到火焰標志位為True,對應會播放聲音
else: #輪廓序號沒變說明沒檢測到火焰
cv2.putText(frame,("FireArea=0"), (5,20), font, 0.7, (0,255,0), 2)#火焰面積為0
return frame #返回最終處理后的圖像
if __name__=="__main__":
pass

復制代碼

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