├── CustomBlinkCascade.xml
├── Driver Cam.py
├── README.md
├── beep-07.wav
├── demo.png
├── haarcascade_eye.xml
├── haarcascade_eye_tree_eyeglasses.xml
└── lbpcascade_frontalface.xml


/Driver Cam.py:
--------------------------------------------------------------------------------
  1 | import numpy
  2 | from pygame import mixer
  3 | import time
  4 | import cv2
  5 | from tkinter import *
  6 | import tkinter.messagebox
  7 | root=Tk()
  8 | root.geometry('500x570')
  9 | frame = Frame(root, relief=RIDGE, borderwidth=2)
 10 | frame.pack(fill=BOTH,expand=1)
 11 | root.title('Driver Cam')
 12 | frame.config(background='light blue')
 13 | label = Label(frame, text="Driver Cam",bg='light blue',font=('Times 35 bold'))
 14 | label.pack(side=TOP)
 15 | filename = PhotoImage(file="E:\python\Driver Cam\demo.png")
 16 | background_label = Label(frame,image=filename)
 17 | background_label.pack(side=TOP)
 18 | 
 19 | 
 20 | 
 21 | def hel():
 22 |    help(cv2)
 23 | 
 24 | def Contri():
 25 |    tkinter.messagebox.showinfo("Contributors","\n1.Mayur Kadam\n2. Abhishek Ezhava \n3. Rajendra Patil \n")
 26 | 
 27 | 
 28 | def anotherWin():
 29 |    tkinter.messagebox.showinfo("About",'Driver Cam version v1.0\n Made Using\n-OpenCV\n-Numpy\n-Tkinter\n In Python 3')
 30 |                                     
 31 |    
 32 | 
 33 | menu = Menu(root)
 34 | root.config(menu=menu)
 35 | 
 36 | subm1 = Menu(menu)
 37 | menu.add_cascade(label="Tools",menu=subm1)
 38 | subm1.add_command(label="Open CV Docs",command=hel)
 39 | 
 40 | subm2 = Menu(menu)
 41 | menu.add_cascade(label="About",menu=subm2)
 42 | subm2.add_command(label="Driver Cam",command=anotherWin)
 43 | subm2.add_command(label="Contributors",command=Contri)
 44 | 
 45 | 
 46 | 
 47 | def exitt():
 48 |    exit()
 49 | 
 50 |   
 51 | def web():
 52 |    capture =cv2.VideoCapture(0)
 53 |    while True:
 54 |       ret,frame=capture.read()
 55 |       gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
 56 |       cv2.imshow('frame',frame)
 57 |       if cv2.waitKey(1) & 0xFF ==ord('q'):
 58 |          break
 59 |    capture.release()
 60 |    cv2.destroyAllWindows()
 61 | 
 62 | def webrec():
 63 |    capture =cv2.VideoCapture(0)
 64 |    fourcc=cv2.VideoWriter_fourcc(*'XVID') 
 65 |    op=cv2.VideoWriter('Sample1.avi',fourcc,11.0,(640,480))
 66 |    while True:
 67 |       ret,frame=capture.read()
 68 |       gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
 69 |       cv2.imshow('frame',frame)
 70 |       op.write(frame)
 71 |       if cv2.waitKey(1) & 0xFF ==ord('q'):
 72 |          break
 73 |    op.release()
 74 |    capture.release()
 75 |    cv2.destroyAllWindows()   
 76 | 
 77 | def webdet():
 78 |    capture =cv2.VideoCapture(0)
 79 |    face_cascade = cv2.CascadeClassifier('lbpcascade_frontalface.xml')
 80 |    eye_glass = cv2.CascadeClassifier('haarcascade_eye_tree_eyeglasses.xml')
 81 |    
 82 | 
 83 |    while True:
 84 |        ret, frame = capture.read()
 85 |        gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
 86 |        faces = face_cascade.detectMultiScale(gray)
 87 |     
 88 | 
 89 |        for (x,y,w,h) in faces:
 90 |            font = cv2.FONT_HERSHEY_COMPLEX
 91 |            cv2.putText(frame,'Face',(x+w,y+h),font,1,(250,250,250),2,cv2.LINE_AA)
 92 |            cv2.rectangle(frame,(x,y),(x+w,y+h),(255,0,0),2)
 93 |            roi_gray = gray[y:y+h, x:x+w]
 94 |            roi_color = frame[y:y+h, x:x+w]
 95 |         
 96 |           
 97 |            eye_g = eye_glass.detectMultiScale(roi_gray)
 98 |            for (ex,ey,ew,eh) in eye_g:
 99 |               cv2.rectangle(roi_color,(ex,ey),(ex+ew,ey+eh),(0,255,0),2)
100 | 
101 |        
102 |        cv2.imshow('frame',frame)
103 |        if cv2.waitKey(1) & 0xff == ord('q'):
104 |           break
105 |    capture.release()
106 |    cv2.destroyAllWindows()
107 | def webdetRec():
108 |    capture =cv2.VideoCapture(0)
109 |    face_cascade = cv2.CascadeClassifier('lbpcascade_frontalface.xml')
110 |    eye_glass = cv2.CascadeClassifier('haarcascade_eye_tree_eyeglasses.xml')
111 |    fourcc=cv2.VideoWriter_fourcc(*'XVID') 
112 |    op=cv2.VideoWriter('Sample2.avi',fourcc,9.0,(640,480))
113 | 
114 |    while True:
115 |        ret, frame = capture.read()
116 |        gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
117 |        faces = face_cascade.detectMultiScale(gray)
118 |     
119 | 
120 |        for (x,y,w,h) in faces:
121 |            font = cv2.FONT_HERSHEY_COMPLEX
122 |            cv2.putText(frame,'Face',(x+w,y+h),font,1,(250,250,250),2,cv2.LINE_AA)
123 |            cv2.rectangle(frame,(x,y),(x+w,y+h),(255,0,0),2)
124 |            roi_gray = gray[y:y+h, x:x+w]
125 |            roi_color = frame[y:y+h, x:x+w]
126 |         
127 |           
128 | 
129 |            eye_g = eye_glass.detectMultiScale(roi_gray)
130 |            for (ex,ey,ew,eh) in eye_g:
131 |               cv2.rectangle(roi_color,(ex,ey),(ex+ew,ey+eh),(0,255,0),2)
132 |        op.write(frame)
133 |        cv2.imshow('frame',frame)
134 |        if cv2.waitKey(1) & 0xff == ord('q'):
135 |           break
136 |    op.release()      
137 |    capture.release()
138 |    cv2.destroyAllWindows()
139 | 
140 |    
141 | def alert():
142 |    mixer.init()
143 |    alert=mixer.Sound('beep-07.wav')
144 |    alert.play()
145 |    time.sleep(0.1)
146 |    alert.play()   
147 |    
148 | def blink():
149 |    capture =cv2.VideoCapture(0)
150 |    face_cascade = cv2.CascadeClassifier('lbpcascade_frontalface.xml')
151 |    eye_cascade = cv2.CascadeClassifier('haarcascade_eye.xml')
152 |    blink_cascade = cv2.CascadeClassifier('CustomBlinkCascade.xml')
153 | 
154 |    while True:
155 |       ret, frame = capture.read()
156 |       gray = cv2.cvtColor(frame,cv2.COLOR_BGR2GRAY)
157 |       faces = face_cascade.detectMultiScale(gray)
158 | 
159 |       for (x,y,w,h) in faces:
160 |          font = cv2.FONT_HERSHEY_COMPLEX
161 |          cv2.putText(frame,'Face',(x+w,y+h),font,1,(250,250,250),2,cv2.LINE_AA)
162 |          cv2.rectangle(frame,(x,y),(x+w,y+h),(255,0,0),2)
163 |          roi_gray = gray[y:y+h, x:x+w]
164 |          roi_color = frame[y:y+h, x:x+w]
165 | 
166 |          eyes = eye_cascade.detectMultiScale(roi_gray)
167 |          for(ex,ey,ew,eh) in eyes:
168 |             cv2.rectangle(roi_color,(ex,ey),(ex+ew,ey+eh),(0,255,0),2)
169 | 
170 |          blink = blink_cascade.detectMultiScale(roi_gray)
171 |          for(eyx,eyy,eyw,eyh) in blink:
172 |             cv2.rectangle(roi_color,(eyx,eyy),(eyx+eyw,eyy+eyh),(255,255,0),2)
173 |             alert()
174 |       cv2.imshow('frame',frame)
175 |       if cv2.waitKey(1) & 0xFF ==ord('q'):
176 |           break
177 |          
178 |   
179 |    capture.release()
180 |    cv2.destroyAllWindows()
181 | 
182 |    
183 | but1=Button(frame,padx=5,pady=5,width=39,bg='white',fg='black',relief=GROOVE,command=web,text='Open Cam',font=('helvetica 15 bold'))
184 | but1.place(x=5,y=104)
185 | 
186 | but2=Button(frame,padx=5,pady=5,width=39,bg='white',fg='black',relief=GROOVE,command=webrec,text='Open Cam & Record',font=('helvetica 15 bold'))
187 | but2.place(x=5,y=176)
188 | 
189 | but3=Button(frame,padx=5,pady=5,width=39,bg='white',fg='black',relief=GROOVE,command=webdet,text='Open Cam & Detect',font=('helvetica 15 bold'))
190 | but3.place(x=5,y=250)
191 | 
192 | but4=Button(frame,padx=5,pady=5,width=39,bg='white',fg='black',relief=GROOVE,command=webdetRec,text='Detect & Record',font=('helvetica 15 bold'))
193 | but4.place(x=5,y=322)
194 | 
195 | but5=Button(frame,padx=5,pady=5,width=39,bg='white',fg='black',relief=GROOVE,command=blink,text='Detect Eye Blink & Record With Sound',font=('helvetica 15 bold'))
196 | but5.place(x=5,y=400)
197 | 
198 | but5=Button(frame,padx=5,pady=5,width=5,bg='white',fg='black',relief=GROOVE,text='EXIT',command=exitt,font=('helvetica 15 bold'))
199 | but5.place(x=210,y=478)
200 | 
201 | 
202 | root.mainloop()
203 | 
204 | 


--------------------------------------------------------------------------------
/README.md:
--------------------------------------------------------------------------------
1 | # Driver-Cam-Using-OpenCV-Python


--------------------------------------------------------------------------------
/beep-07.wav:
--------------------------------------------------------------------------------
https://raw.githubusercontent.com/abhishek305/Drowsiness-monitoring-Using-OpenCV-Python/a32efc7956aeaf68748ea0095f69476547a8e03b/beep-07.wav


--------------------------------------------------------------------------------
/demo.png:
--------------------------------------------------------------------------------
https://raw.githubusercontent.com/abhishek305/Drowsiness-monitoring-Using-OpenCV-Python/a32efc7956aeaf68748ea0095f69476547a8e03b/demo.png


--------------------------------------------------------------------------------
/lbpcascade_frontalface.xml:
--------------------------------------------------------------------------------
   1 | <?xml version="1.0"?>
   2 | <!--
   3 | number of positive samples 3000
   4 | number of negative samples 1500
   5 | -->
   6 | <opencv_storage>
   7 | <cascade type_id="opencv-cascade-classifier">
   8 |   <stageType>BOOST</stageType>
   9 |   <featureType>LBP</featureType>
  10 |   <height>24</height>
  11 |   <width>24</width>
  12 |   <stageParams>
  13 |     <boostType>GAB</boostType>
  14 |     <minHitRate>0.9950000047683716</minHitRate>
  15 |     <maxFalseAlarm>0.5000000000000000</maxFalseAlarm>
  16 |     <weightTrimRate>0.9500000000000000</weightTrimRate>
  17 |     <maxDepth>1</maxDepth>
  18 |     <maxWeakCount>100</maxWeakCount></stageParams>
  19 |   <featureParams>
  20 |     <maxCatCount>256</maxCatCount></featureParams>
  21 |   <stageNum>20</stageNum>
  22 |   <stages>
  23 |     <!-- stage 0 -->
  24 |     <_>
  25 |       <maxWeakCount>3</maxWeakCount>
  26 |       <stageThreshold>-0.7520892024040222</stageThreshold>
  27 |       <weakClassifiers>
  28 |         <!-- tree 0 -->
  29 |         <_>
  30 |           <internalNodes>
  31 |             0 -1 46 -67130709 -21569 -1426120013 -1275125205 -21585
  32 |             -16385 587145899 -24005</internalNodes>
  33 |           <leafValues>
  34 |             -0.6543210148811340 0.8888888955116272</leafValues></_>
  35 |         <!-- tree 1 -->
  36 |         <_>
  37 |           <internalNodes>
  38 |             0 -1 13 -163512766 -769593758 -10027009 -262145 -514457854
  39 |             -193593353 -524289 -1</internalNodes>
  40 |           <leafValues>
  41 |             -0.7739216089248657 0.7278633713722229</leafValues></_>
  42 |         <!-- tree 2 -->
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  44 |           <internalNodes>
  45 |             0 -1 2 -363936790 -893203669 -1337948010 -136907894
  46 |             1088782736 -134217726 -741544961 -1590337</internalNodes>
  47 |           <leafValues>
  48 |             -0.7068563103675842 0.6761534214019775</leafValues></_></weakClassifiers></_>
  49 |     <!-- stage 1 -->
  50 |     <_>
  51 |       <maxWeakCount>4</maxWeakCount>
  52 |       <stageThreshold>-0.4872078299522400</stageThreshold>
  53 |       <weakClassifiers>
  54 |         <!-- tree 0 -->
  55 |         <_>
  56 |           <internalNodes>
  57 |             0 -1 84 2147483647 1946124287 -536870913 2147450879
  58 |             738132490 1061101567 243204619 2147446655</internalNodes>
  59 |           <leafValues>
  60 |             -0.8083735704421997 0.7685696482658386</leafValues></_>
  61 |         <!-- tree 1 -->
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  63 |           <internalNodes>
  64 |             0 -1 21 2147483647 263176079 1879048191 254749487 1879048191
  65 |             -134252545 -268435457 801111999</internalNodes>
  66 |           <leafValues>
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  68 |         <!-- tree 2 -->
  69 |         <_>
  70 |           <internalNodes>
  71 |             0 -1 106 -98110272 1610939566 -285484400 -850010381
  72 |             -189334372 -1671954433 -571026695 -262145</internalNodes>
  73 |           <leafValues>
  74 |             -0.7506558895111084 0.5444605946540833</leafValues></_>
  75 |         <!-- tree 3 -->
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  77 |           <internalNodes>
  78 |             0 -1 48 -798690576 -131075 1095771153 -237144073 -65569 -1
  79 |             -216727745 -69206049</internalNodes>
  80 |           <leafValues>
  81 |             -0.7775990366935730 0.5465461611747742</leafValues></_></weakClassifiers></_>
  82 |     <!-- stage 2 -->
  83 |     <_>
  84 |       <maxWeakCount>4</maxWeakCount>
  85 |       <stageThreshold>-1.1592328548431396</stageThreshold>
  86 |       <weakClassifiers>
  87 |         <!-- tree 0 -->
  88 |         <_>
  89 |           <internalNodes>
  90 |             0 -1 47 -21585 -20549 -100818262 -738254174 -20561 -36865
  91 |             -151016790 -134238549</internalNodes>
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  94 |         <!-- tree 1 -->
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 101 |         <!-- tree 2 -->
 102 |         <_>
 103 |           <internalNodes>
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 105 |             -50364513 -33619992 -172490753</internalNodes>
 106 |           <leafValues>
 107 |             -0.6114496588706970 0.6537628173828125</leafValues></_>
 108 |         <!-- tree 3 -->
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 112 |             2146926575 -18910642 1095231247</internalNodes>
 113 |           <leafValues>
 114 |             -0.6854077577590942 0.5403239130973816</leafValues></_></weakClassifiers></_>
 115 |     <!-- stage 3 -->
 116 |     <_>
 117 |       <maxWeakCount>5</maxWeakCount>
 118 |       <stageThreshold>-0.7562355995178223</stageThreshold>
 119 |       <weakClassifiers>
 120 |         <!-- tree 0 -->
 121 |         <_>
 122 |           <internalNodes>
 123 |             0 -1 96 -1273 1870659519 -20971602 -67633153 -134250731
 124 |             2004875127 -250 -150995969</internalNodes>
 125 |           <leafValues>
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 127 |         <!-- tree 1 -->
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 131 |             -268959873 -2656269 -524289</internalNodes>
 132 |           <leafValues>
 133 |             -0.7388162612915039 0.5340843200683594</leafValues></_>
 134 |         <!-- tree 2 -->
 135 |         <_>
 136 |           <internalNodes>
 137 |             0 -1 57 -12817 -49 -541103378 -152950 -38993 -20481 -1153876
 138 |             -72478976</internalNodes>
 139 |           <leafValues>
 140 |             -0.6582943797111511 0.5339496731758118</leafValues></_>
 141 |         <!-- tree 3 -->
 142 |         <_>
 143 |           <internalNodes>
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 145 |             -990117891 -488975296 -520947741</internalNodes>
 146 |           <leafValues>
 147 |             -0.5981323719024658 0.5323504805564880</leafValues></_>
 148 |         <!-- tree 4 -->
 149 |         <_>
 150 |           <internalNodes>
 151 |             0 -1 53 557787431 670265215 -1342193665 -1075892225
 152 |             1998528318 1056964607 -33570977 -1</internalNodes>
 153 |           <leafValues>
 154 |             -0.6498787999153137 0.4913350641727448</leafValues></_></weakClassifiers></_>
 155 |     <!-- stage 4 -->
 156 |     <_>
 157 |       <maxWeakCount>5</maxWeakCount>
 158 |       <stageThreshold>-0.8085358142852783</stageThreshold>
 159 |       <weakClassifiers>
 160 |         <!-- tree 0 -->
 161 |         <_>
 162 |           <internalNodes>
 163 |             0 -1 60 -536873708 880195381 -16842788 -20971521 -176687276
 164 |             -168427659 -16777260 -33554626</internalNodes>
 165 |           <leafValues>
 166 |             -0.5278195738792419 0.6946372389793396</leafValues></_>
 167 |         <!-- tree 1 -->
 168 |         <_>
 169 |           <internalNodes>
 170 |             0 -1 7 -1 -62981529 -1090591130 805330978 -8388827 -41945787
 171 |             -39577 -531118985</internalNodes>
 172 |           <leafValues>
 173 |             -0.5206505060195923 0.6329920291900635</leafValues></_>
 174 |         <!-- tree 2 -->
 175 |         <_>
 176 |           <internalNodes>
 177 |             0 -1 98 -725287348 1347747543 -852489 -16809993 1489881036
 178 |             -167903241 -1 -1</internalNodes>
 179 |           <leafValues>
 180 |             -0.7516061067581177 0.4232024252414703</leafValues></_>
 181 |         <!-- tree 3 -->
 182 |         <_>
 183 |           <internalNodes>
 184 |             0 -1 44 -32777 1006582562 -65 935312171 -8388609 -1078198273
 185 |             -1 733886267</internalNodes>
 186 |           <leafValues>
 187 |             -0.7639313936233521 0.4123568832874298</leafValues></_>
 188 |         <!-- tree 4 -->
 189 |         <_>
 190 |           <internalNodes>
 191 |             0 -1 24 -85474705 2138828511 -1036436754 817625855
 192 |             1123369029 -58796809 -1013468481 -194513409</internalNodes>
 193 |           <leafValues>
 194 |             -0.5123769044876099 0.5791834592819214</leafValues></_></weakClassifiers></_>
 195 |     <!-- stage 5 -->
 196 |     <_>
 197 |       <maxWeakCount>5</maxWeakCount>
 198 |       <stageThreshold>-0.5549971461296082</stageThreshold>
 199 |       <weakClassifiers>
 200 |         <!-- tree 0 -->
 201 |         <_>
 202 |           <internalNodes>
 203 |             0 -1 42 -17409 -20481 -268457797 -134239493 -17473 -1 -21829
 204 |             -21846</internalNodes>
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 206 |             -0.3763174116611481 0.7298233509063721</leafValues></_>
 207 |         <!-- tree 1 -->
 208 |         <_>
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 210 |             0 -1 6 -805310737 -2098262358 -269504725 682502698
 211 |             2147483519 1740574719 -1090519233 -268472385</internalNodes>
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 214 |         <!-- tree 2 -->
 215 |         <_>
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 218 |             -50856216 -16849696</internalNodes>
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 221 |         <!-- tree 3 -->
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 232 |             -36190633 33498198 -151796633</internalNodes>
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 235 |     <!-- stage 6 -->
 236 |     <_>
 237 |       <maxWeakCount>5</maxWeakCount>
 238 |       <stageThreshold>-0.8776460289955139</stageThreshold>
 239 |       <weakClassifiers>
 240 |         <!-- tree 0 -->
 241 |         <_>
 242 |           <internalNodes>
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 247 |         <!-- tree 1 -->
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 254 |         <!-- tree 2 -->
 255 |         <_>
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 258 |             -50855988 -129 -1 -1</internalNodes>
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 261 |         <!-- tree 3 -->
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 268 |         <!-- tree 4 -->
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 272 |             -1140949004 -3 -2361356 -739516</internalNodes>
 273 |           <leafValues>
 274 |             -0.6445107460021973 0.4227822124958038</leafValues></_></weakClassifiers></_>
 275 |     <!-- stage 7 -->
 276 |     <_>
 277 |       <maxWeakCount>6</maxWeakCount>
 278 |       <stageThreshold>-1.1139287948608398</stageThreshold>
 279 |       <weakClassifiers>
 280 |         <!-- tree 0 -->
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 287 |         <!-- tree 1 -->
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 294 |         <!-- tree 2 -->
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 301 |         <!-- tree 3 -->
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 308 |         <!-- tree 4 -->
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 315 |         <!-- tree 5 -->
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 322 |     <!-- stage 8 -->
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 326 |       <weakClassifiers>
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 334 |         <!-- tree 1 -->
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 341 |         <!-- tree 2 -->
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 348 |         <!-- tree 3 -->
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 355 |         <!-- tree 4 -->
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 362 |         <!-- tree 5 -->
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 369 |         <!-- tree 6 -->
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 376 |     <!-- stage 9 -->
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 402 |         <!-- tree 3 -->
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 409 |         <!-- tree 4 -->
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 416 |         <!-- tree 5 -->
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 423 |         <!-- tree 6 -->
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 430 |     <!-- stage 10 -->
 431 |     <_>
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 442 |         <!-- tree 1 -->
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 449 |         <!-- tree 2 -->
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 456 |         <!-- tree 3 -->
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 463 |         <!-- tree 4 -->
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 470 |         <!-- tree 5 -->
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 477 |         <!-- tree 6 -->
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 484 |     <!-- stage 11 -->
 485 |     <_>
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 496 |         <!-- tree 1 -->
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 503 |         <!-- tree 2 -->
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 510 |         <!-- tree 3 -->
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 517 |         <!-- tree 4 -->
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 524 |         <!-- tree 5 -->
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 531 |         <!-- tree 6 -->
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 538 |     <!-- stage 12 -->
 539 |     <_>
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 550 |         <!-- tree 1 -->
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 564 |         <!-- tree 3 -->
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 571 |         <!-- tree 4 -->
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 578 |         <!-- tree 5 -->
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 585 |         <!-- tree 6 -->
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 592 |         <!-- tree 7 -->
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 599 |     <!-- stage 13 -->
 600 |     <_>
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 611 |         <!-- tree 1 -->
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 632 |         <!-- tree 4 -->
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 639 |         <!-- tree 5 -->
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 646 |         <!-- tree 6 -->
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 653 |         <!-- tree 7 -->
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 660 |         <!-- tree 8 -->
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 667 |     <!-- stage 14 -->
 668 |     <_>
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 679 |         <!-- tree 1 -->
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 686 |         <!-- tree 2 -->
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 693 |         <!-- tree 3 -->
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 700 |         <!-- tree 4 -->
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 707 |         <!-- tree 5 -->
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 714 |         <!-- tree 6 -->
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 721 |         <!-- tree 7 -->
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 728 |         <!-- tree 8 -->
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 735 |         <!-- tree 9 -->
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 742 |     <!-- stage 15 -->
 743 |     <_>
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 754 |         <!-- tree 1 -->
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 761 |         <!-- tree 2 -->
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 768 |         <!-- tree 3 -->
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 775 |         <!-- tree 4 -->
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 782 |         <!-- tree 5 -->
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 810 |     <!-- stage 16 -->
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1021 |     <!-- stage 19 -->
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1349 |     <_>
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1352 |     <_>
1353 |       <rect>
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1355 |     <_>
1356 |       <rect>
1357 |         11 6 1 1</rect></_>
1358 |     <_>
1359 |       <rect>
1360 |         11 7 2 2</rect></_>
1361 |     <_>
1362 |       <rect>
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1364 |     <_>
1365 |       <rect>
1366 |         11 10 1 1</rect></_>
1367 |     <_>
1368 |       <rect>
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1370 |     <_>
1371 |       <rect>
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1373 |     <_>
1374 |       <rect>
1375 |         11 17 1 1</rect></_>
1376 |     <_>
1377 |       <rect>
1378 |         11 18 1 1</rect></_>
1379 |     <_>
1380 |       <rect>
1381 |         12 0 2 2</rect></_>
1382 |     <_>
1383 |       <rect>
1384 |         12 1 2 5</rect></_>
1385 |     <_>
1386 |       <rect>
1387 |         12 2 4 1</rect></_>
1388 |     <_>
1389 |       <rect>
1390 |         12 3 1 3</rect></_>
1391 |     <_>
1392 |       <rect>
1393 |         12 7 3 4</rect></_>
1394 |     <_>
1395 |       <rect>
1396 |         12 10 3 2</rect></_>
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1398 |       <rect>
1399 |         12 11 1 1</rect></_>
1400 |     <_>
1401 |       <rect>
1402 |         12 12 3 2</rect></_>
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1404 |       <rect>
1405 |         12 14 4 3</rect></_>
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1407 |       <rect>
1408 |         12 17 1 1</rect></_>
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1410 |       <rect>
1411 |         12 21 2 1</rect></_>
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1413 |       <rect>
1414 |         13 6 2 5</rect></_>
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1416 |       <rect>
1417 |         13 7 3 5</rect></_>
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1419 |       <rect>
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1422 |       <rect>
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1424 |     <_>
1425 |       <rect>
1426 |         13 17 3 2</rect></_>
1427 |     <_>
1428 |       <rect>
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1430 |     <_>
1431 |       <rect>
1432 |         13 18 2 2</rect></_>
1433 |     <_>
1434 |       <rect>
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1436 |     <_>
1437 |       <rect>
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1440 |       <rect>
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1442 |     <_>
1443 |       <rect>
1444 |         14 7 2 1</rect></_>
1445 |     <_>
1446 |       <rect>
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1448 |     <_>
1449 |       <rect>
1450 |         14 13 3 3</rect></_>
1451 |     <_>
1452 |       <rect>
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1456 |         15 0 2 2</rect></_>
1457 |     <_>
1458 |       <rect>
1459 |         15 0 2 3</rect></_>
1460 |     <_>
1461 |       <rect>
1462 |         15 4 3 2</rect></_>
1463 |     <_>
1464 |       <rect>
1465 |         15 4 3 6</rect></_>
1466 |     <_>
1467 |       <rect>
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1469 |     <_>
1470 |       <rect>
1471 |         15 11 3 4</rect></_>
1472 |     <_>
1473 |       <rect>
1474 |         15 13 3 2</rect></_>
1475 |     <_>
1476 |       <rect>
1477 |         15 17 2 2</rect></_>
1478 |     <_>
1479 |       <rect>
1480 |         15 17 3 2</rect></_>
1481 |     <_>
1482 |       <rect>
1483 |         16 1 2 3</rect></_>
1484 |     <_>
1485 |       <rect>
1486 |         16 3 2 4</rect></_>
1487 |     <_>
1488 |       <rect>
1489 |         16 6 1 1</rect></_>
1490 |     <_>
1491 |       <rect>
1492 |         16 16 2 2</rect></_>
1493 |     <_>
1494 |       <rect>
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1497 |       <rect>
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1500 |       <rect>
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1505 | </opencv_storage>
1506 | 


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