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SaharshPandeySaharshPandey
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Added graph plotting in Bokeh
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‎Project6-FaceDetection/Graph1.html

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<!DOCTYPE html>
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<html lang="en">
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<head>
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<meta charset="utf-8">
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<title>Bokeh Plot</title>
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<link rel="stylesheet" href="https://cdn.pydata.org/bokeh/release/bokeh-0.13.0.min.css" type="text/css" />
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<script type="text/javascript" src="https://cdn.pydata.org/bokeh/release/bokeh-0.13.0.min.js"></script>
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<script type="text/javascript">
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Bokeh.set_log_level("info");
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</script>
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</head>
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<body>
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<div class="bk-root" id="ba0d7700-6f18-4609-86b8-ebe145999aa6"></div>
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<script type="application/json" id="e833eda6-990a-4f39-b512-58ddd675ce52">
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</script>
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<script type="text/javascript">
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(function() {
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var fn = function() {
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Bokeh.safely(function() {
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(function(root) {
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function embed_document(root) {
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var docs_json = document.getElementById('e833eda6-990a-4f39-b512-58ddd675ce52').textContent;
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var render_items = [{"docid":"04a2799a-eece-4aa6-9993-0e71ed533ca5","roots":{"f2bb602b-ca57-42ab-9505-2e5b9a8b122b":"ba0d7700-6f18-4609-86b8-ebe145999aa6"}}];
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root.Bokeh.embed.embed_items(docs_json, render_items);
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}
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if (root.Bokeh !== undefined) {
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embed_document(root);
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} else {
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var attempts = 0;
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var timer = setInterval(function(root) {
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if (root.Bokeh !== undefined) {
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embed_document(root);
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clearInterval(timer);
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}
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attempts++;
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if (attempts > 100) {
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console.log("Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing")
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clearInterval(timer);
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}
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}, 10, root)
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}
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})(window);
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});
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};
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if (document.readyState != "loading") fn();
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else document.addEventListener("DOMContentLoaded", fn);
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})();
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</script>
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</body>
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</html>

‎Project6-FaceDetection/Times.csv

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,Start,End,END
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0,2018-07-11 16:15:50.329286,,2018-07-11 16:15:50.343558
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1,2018-07-11 16:15:50.371213,,2018-07-11 16:15:55.901013
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0,2018-07-14 11:52:48.363216,,2018-07-14 11:52:57.117491
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1,2018-07-14 11:52:57.381828,,2018-07-14 11:53:02.357403
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2,2018-07-14 11:53:02.485783,,2018-07-14 11:53:08.541854
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3,2018-07-14 11:53:09.330664,,2018-07-14 11:53:11.551983
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4,2018-07-14 11:53:11.683509,,2018-07-14 11:53:11.814517
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5,2018-07-14 11:53:12.863569,,2018-07-14 11:53:15.868537
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6,2018-07-14 11:53:17.047192,,2018-07-14 11:53:33.538832
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7,2018-07-14 11:53:34.059060,,2018-07-14 11:53:34.197151

‎Project6-FaceDetection/__pycache__/motion_detector.cpython-36.pyc

1.58 KB
Binary file not shown.

‎Project6-FaceDetection/motion_detector.py

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import cv2 as cv
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from datetime import datetime
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import pandas
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import pandas,imutils
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first_frame=None #stores the first frame...
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status_list=[None,None] #stroing the status if objects
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times=[] #storing the datetime for objects
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while True:
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#two attributes check->:boolean that tells video is recording..while frame :-> ndarray
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check,frame=video.read()
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frame = imutils.resize(frame, width=500)
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#this status=0 means there is no motion right now..
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status=0
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#print(check)
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continue #now if we continue then there will be no first frame,because it is pre generated.
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delta_frame=cv.absdiff(first_frame,gray) #this finding the diff between the first frame(background) and other frames of video.
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thresh_frame=cv.threshold(delta_frame,30,255,cv.THRESH_BINARY)[1] #create threshold frame
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thresh_frame=cv.dilate(thresh_frame,None,iterations=2) #dilate means making tthe edges smoother
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#thresh_frame=cv.threshold(delta_frame,50,255,cv.THRESH_BINARY)[1] #create threshold frame
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#thresh_frame=cv.adaptiveThreshold(delta_frame,255,cv.ADAPTIVE_THRESH_MEAN_C ,cv.THRESH_BINARY,11,2)
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thresh_frame=cv.threshold(delta_frame,160,255,cv.THRESH_BINARY)[1]
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thresh_frame=cv.dilate(thresh_frame,None,iterations=2 ) #dilate means making tthe edges smoother
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#finding the contours which helps to find out objects in a frame.
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(_,cnts,_)=cv.findContours(thresh_frame.copy(),cv.RETR_EXTERNAL,cv.CHAIN_APPROX_SIMPLE)
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for contour in cnts:
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#if area of object is less then 1000 then we will continue otherwise there is an object.
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if cv.contourArea(contour)<1000:
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if cv.contourArea(contour)<15000:
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continue
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status=1 #this implies there is an object in a frame
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(x,y,w,h)=cv.boundingRect(contour) # finding the corners of object in a frame.
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cv.rectangle(frame,(x,y),(x+w,y+h),(0,255,0),3) # making out rectangle for every objects
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cv.rectangle(frame,(x,y),(x+w,y+h),(0,255,0),2) # making out rectangle for every objects
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#appending all the incoming and outgoing of the object in an frame
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status_list.append(status)
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status_list=status_list[-2:]
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#checking the datetime of apearing object
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if status_list[-1]==1 and status_list[-2]==0:

‎Project6-FaceDetection/plotting.py

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from motion_detector import df
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from bokeh.plotting import figure, show, output_file
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from bokeh.models import HoverTool, ColumnDataSource
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df["Start_string"]=df["Start"].dt.strftime("%Y-%m-%d %H:%M:%S")
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df["End_string"]=df["End"].dt.strftime("%Y-%m-%d %H:%M:%S")
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cds=ColumnDataSource(df)
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p=figure(x_axis_type='datetime',height=100, width=500, sizing_mode="scale_width",title="Motion Graph")
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p.yaxis.minor_tick_line_color=None
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p.ygrid[0].ticker.desired_num_ticks=1
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hover=HoverTool(tooltips=[("Start","@Start_string"),("End","@End_string")])
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p.add_tools(hover)
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q=p.quad(left="Start",right="End",bottom=0,top=1,color="green",source=cds)
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output_file("Graph1.html")
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show(p)

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