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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(shè)置字體
class Work(threading.Thread):
def __init__(self, caller):
threading.Thread.__init__(self)
self.caller = caller #父類調(diào)用者
self.isHaveFire = False #全局變量是否檢測(cè)到火焰
def run(self): #線程啟動(dòng)后自動(dòng)調(diào)用此函數(shù)
cap = cv2.VideoCapture()#初始化VideoCapture類對(duì)象
if(self.caller.video_flag == 1):#標(biāo)志位為1，對(duì)應(yīng)打開(kāi)攝像頭
cap = cv2.VideoCapture(0) #打開(kāi)攝像頭
print("打開(kāi)攝像頭")
else: #標(biāo)志位為1，對(duì)應(yīng)打開(kāi)視頻文件
cap = cv2.VideoCapture(self.caller.video_path)#打開(kāi)對(duì)應(yīng)路徑的視頻文件
print("打開(kāi)視頻文件%s"%self.caller.video_path)
while(1):
if(self.caller.flag): #如果視頻結(jié)束標(biāo)志位為1，則退出并清空?qǐng)D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(huán)
print("攝像頭打開(kāi)失��！" )
break
time.sleep(0.001)
frame = self.fire_detect(frame)#調(diào)用火焰檢測(cè)函數(shù)
frameTest = frame.copy()#原圖備份
self.showViewImg(self.caller.label, frame)
cap.release()#釋放VideoCapture類對(duì)象
def showViewImg(self,label,img):
# 提取圖像的尺寸和通道, 用于將opencv下的image轉(zhuǎn)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(lái)
label.setPixmap(QPixmap.fromImage(qImg))
def img_detect(self,img):#加載圖片檢測(cè)火焰
print("Image Test")
frame = self.fire_detect(img)#調(diào)用檢測(cè)火焰函數(shù)
self.showViewImg(self.caller.label, frame)
def fire_detect(self,frame): #火焰檢測(cè)函數(shù)，核心算法
self.isHaveFire = False #初始化火焰檢測(cè)結(jié)果標(biāo)志位False
redThres = 49 #紅色閾值
sat = 7 #比例系數(shù)
blackImg = np.zeros((frame.shape[0],frame.shape[1],1),np.uint8)#創(chuàng)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(wèn)所有行
for j in range(0,frame.shape[1]): #訪問(wèn)所有列
B = int(b[i,j])#訪問(wèn)第i行，第j列藍(lán)色像素值
G = int(g[i,j])#訪問(wèn)第i行，第j列綠色像素值
R = int(r[i,j])#訪問(wèn)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(jì)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(duì)應(yīng)位置變?yōu)榘咨?br />
else:
blackImg[i,j] = 0 #不滿足火焰像素，黑色圖像對(duì)應(yīng)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(duì)輪廓面積
maxArea = w0*h0 #獲取最大面積
index = i #獲取最大面積對(duì)應(yīng)的輪廓序號(hào)
if index != -1: #輪廓序號(hào)變化了說(shuō)明沒(méi)檢測(cè)到火焰
area = cv2.contourArea(contours[index])#獲取火焰輪廓對(duì)應(yīng)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(qū)域
self.isHaveFire = True #檢測(cè)到火焰標(biāo)志位為True,對(duì)應(yīng)會(huì)播放聲音
else: #輪廓序號(hào)沒(méi)變說(shuō)明沒(méi)檢測(cè)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

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