Hardware components | ||||||
 |
| × | 1 | |||
| × | 1 | ||||
Software apps and online services | ||||||
| ||||||
| ||||||
There are some Historical places and other places like museums where the entry of the people is restricted after the visiting hours. After visiting hours the people should not stay in those areas as it would be not safe for those people and in some cases it would become problem for the authorities. As some people will stay back there and cause damage to the property and may steal the valuable things present there.
In the present system the security guards need to check every place whether there is any person present in that area or not and he should send them back from that place. In order to overcome this scenario a smart device can be integrated at the entrance of that particular place and count the number of persons entering and exiting that location. We can capture the faces of the persons while entry and exit. Storing these images we can match the exit faces with the entry faces by using face matching algorithms and can identify the faces of those who has entered but didn’t exit.
There will be a web application through which the security guards can check the faces of those who didn’t exit and they can get the count of the people who remained there. This data will be helpful to them and makes their task easier.
import cv2
import sys
import logging as log
import datetime as dt
from time import sleep
import os
import boto3
global a
s3_bucket = 'dayaalibucket1'
s3_bucket1 = 'historical123'
s3_bucket_region = 'us-east-1'
s3 = boto3.resource('s3')
my_bucket = s3.Bucket(s3_bucket)
entry_folder_name = "entry/"
exit_folder_name = "exit/"
q = []
############################# function for listing faces in folders of a bucket
entry_folder = "entry/"
exit_folder = "exit/"
a = []
b = []
images = []
c=0
###############################################################
faceCascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
log.basicConfig(filename='webcam.log',level=log.INFO)
video_capture = cv2.VideoCapture(0)
anterior = 0
i=0
offset=10
name=dt.datetime.now()
name = str(name.strftime('%Y:%m:%d'))
folder = 'entry'
s3 = boto3.client('s3')
key_name = folder + '/'
s3_connect = boto3.client('s3', s3_bucket_region)
try:
bucket = s3_connect.put_object(Bucket=s3_bucket, Key=key_name)
#print ("Bucket:", bucket)
except Exception as e:
print ("Bucket Error " , e)
# i eddited not to get ret=false ................................................final haarcascade_frontalface_default.xml'
while(not video_capture.isOpened()): # i eddited not to get ret=false
video_capture = cv2.VideoCapture(0)
ret = video_capture.isOpened()
print (ret)
def list_faces():
c=0
del images[:]
for file in my_bucket.objects.all():
g = file.key
print (".......after:" + str(g))
images.append(g)
for x in images:
if( x == entry_folder ):
continue
elif(x != exit_folder):
a.append(x)
if(x == exit_folder):
break
for y in images:
if(y != exit_folder):
if(c==1):
b.append(y)
else:
continue
elif(y == exit_folder):
c=1
else:
break
################################delete object
def delete_faces(bucket, key, region="us-east-1"):
rekognition = boto3.client("rekognition", region)
objs = list(my_bucket.objects.filter(Prefix=key))
response = my_bucket.delete_objects(
Delete={
'Objects': [
{
'Key': key,
},
],
'Quiet': True|False
},
)
return response
##############################
##############################
while True:
name1 = dt.datetime.now()
name = str(name1.strftime('%d:%m:%Y:%H:%M:%S'))
if not video_capture.isOpened():
print('Unable to load camera.')
sleep(2)
pass
# Capture frame-by-frame
ret, frame = video_capture.read()
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
faces = faceCascade.detectMultiScale(
gray,
scaleFactor=1.2,
minNeighbors=5,
minSize=(30, 30)
)
# Draw a rectangle around the faces
for (x, y, w, h) in faces:
cv2.rectangle(frame, (x, y), (x+w, y+h), (0, 255, 0), 2)
if i%25 == 0:
cv2.imwrite("entry/"+ name +'.'+ str(i) + ".jpg", frame)
filename= name +'.'+ str(i) + ".jpg"
# upload File to S3
file_key_name = folder + '/' + filename
local_path = os.getcwd()
local_name = local_path + '/' + key_name + filename
upload = s3_connect.upload_file(local_name, s3_bucket, file_key_name)
#upload = s3_connect.upload_file(local_name, s3_bucket1, "visitors" + '/' + filename)
upload = s3_connect.upload_file(local_name, s3_bucket1, "visitors" + '/' + str(name1.strftime('%d:%m:%Y')) + '/' + filename)
i=i+1
if anterior != len(faces):
anterior = len(faces)
log.info("faces: "+str(len(faces))+" at "+str(dt.datetime.now()))
# Display the resulting frame
cv2.imshow('Video', frame)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
# Display the resulting frame
cv2.imshow('Video', frame)
# When everything is done, release the capture
video_capture.release()
cv2.destroyAllWindows()
import cv2
import sys
import logging as log
import datetime as dt
from time import sleep
import os
import boto3
global a
import requests
import json
s3_bucket = 'dayaalibucket1'
s3_bucket_region = 'us-east-1'
s3 = boto3.resource('s3')
my_bucket = s3.Bucket(s3_bucket)
entry_folder_name = "entry/"
exit_folder_name = "exit/"
q = []
############################# function for listing faces in folders of a bucket
entry_folder = "entry/"
exit_folder = "exit/"
visitor_folder = "visitors/"
a = []
b = []
images = []
c=0
###############################################################
faceCascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
log.basicConfig(filename='webcam.log',level=log.INFO)
video_capture = cv2.VideoCapture(0)
anterior = 0
i=0
offset=10
name = dt.datetime.now()
name = name.strftime('%H:%M:%S')
folder = 'exit'
s3 = boto3.client('s3')
key_name = folder + '/'
s3_connect = boto3.client('s3', s3_bucket_region)
try:
bucket = s3_connect.put_object(Bucket=s3_bucket, Key=key_name)
#print ("Bucket:", bucket)
except Exception as e:
print ("Bucket Error " , e)
# i eddited not to get ret=false ................................................final haarcascade_frontalface_default.xml'
while(not video_capture.isOpened()): # i eddited not to get ret=false
video_capture = cv2.VideoCapture(0)
ret = video_capture.isOpened()
print (ret)
################################
def list_faces():
c=0
del images[:]
for file in my_bucket.objects.all():
g = file.key
print (".......after:" + str(g))
images.append(g)
for x in images:
if( x == entry_folder ):
continue
elif(x != exit_folder):
a.append(x)
if(x == exit_folder):
break
for y in images:
if(y != exit_folder):
if(c==1):
b.append(y)
else:
continue
elif(y == exit_folder):
c=1
else:
break
################################
def list_faces1():
c=0
del images[:]
for file in my_bucket.objects.all():
g = file.key
print (".......after:" + str(g))
images.append(g)
print("images:",images)
for x in images:
if( x == entry_folder ):
continue
elif(x != exit_folder):
a.append(x)
if(x == exit_folder):
break
for y in images:
if(y != exit_folder):
if(c==1 and y != visitor_folder):
b.append(y)
elif(c ==1 and y == visitor_folder):
break
else:
continue
elif(y == exit_folder):
c=1
else:
break
################################delete object
def delete_faces(bucket, key, region="us-east-1"):
rekognition = boto3.client("rekognition", region)
objs = list(my_bucket.objects.filter(Prefix=key))
response = my_bucket.delete_objects(
Delete={
'Objects': [
{
'Key': key,
},
],
'Quiet': True|False
},
)
return response
############################## face comparision
def compare_faces(bucket, key, bucket_target, key_target, threshold=0, region="us-east-1"):
rekognition = boto3.client("rekognition", region)
response = rekognition.compare_faces(
SourceImage={
"S3Object": {
"Bucket": bucket,
"Name": key,
}
},
TargetImage={
"S3Object": {
"Bucket": bucket_target,
"Name": key_target,
}
},
SimilarityThreshold=threshold,
)
return response['SourceImageFace'], response['FaceMatches']
############################## face comparision
def compare():
list_faces()
print(a,b,q)
for i in a:
for j in b:
KEY_SOURCE = i
KEY_TARGET = j
print ("............face comparision started.....................")
print (i,j)
source_face, matches = compare_faces(s3_bucket, KEY_SOURCE, s3_bucket, KEY_TARGET)
print ("Source Face ({Confidence}%)".format(**source_face))
for match in matches:
print ("Target Face ({Confidence}%)".format(**match['Face']))
percent = match['Similarity']
print (" Similarity : {}%".format(match['Similarity']))
print("......................face comparision ended ............................................")
print(percent)
if(percent>80):
if i not in q:
q.append(i)
print (q)
for key in q:
delete_faces(s3_bucket, key, region="us-east-1")
print("...................wait until comparision ended.................................................")
#q.clear()
##############################
def verification():
print('Authorized')
##espeak.synth(str (i))
##############################
r = requests.get(url="https://api.thingspeak.com/channels/445400/feeds/last.json?api_key=KY768RJVKAME0SBA")
x1 = r.json()
dh = (x1["field1"])
dm1 = (x1["field2"])
dm2 = (x1["field3"])
print ("webpage: hour: start min :stop min", dh,dm1,dm2)
while True:
name = dt.datetime.now()
name = name.strftime('%H:%M:%S')
if not video_capture.isOpened():
print('Unable to load camera.')
sleep(2)
pass
# Capture frame-by-frame
ret, frame = video_capture.read()
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
faces = faceCascade.detectMultiScale(
gray,
scaleFactor=1.2,
minNeighbors=5,
minSize=(30, 30)
)
# Draw a rectangle around the faces
for (x, y, w, h) in faces:
cv2.rectangle(frame, (x, y), (x+w, y+h), (0, 255, 0), 2)
if i%25 == 0:
cv2.imwrite("exit/"+ str(name) +'.'+ str(i) + ".jpg", frame)
filename= name +'.'+ str(i) + ".jpg"
# upload File to S3
file_key_name = folder + '/' + filename
local_path = os.getcwd()
local_name = local_path + '/' + key_name + filename
upload = s3_connect.upload_file(local_name, s3_bucket, file_key_name)
name = dt.datetime.now()
print("present time:",name)
h = name.strftime('%H')
s = name.minute;
print("h,s",h,s)
if((str(h) =='16') and ( s>3 and s<58)):
print('static Time Match')
compare()
elif ((str(h) == str(dh)) and (s > int(dm1)) and (s < int(dm2))):
print('dynamic Time Match')
compare()
else:
print('Time Not Match')
i=i+1
if anterior != len(faces):
anterior = len(faces)
log.info("faces: "+str(len(faces))+" at "+str(dt.datetime.now()))
# Display the resulting frame
cv2.imshow('Video', frame)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
# Display the resulting frame
cv2.imshow('Video', frame)
# When everything is done, release the capture
video_capture.release()
cv2.destroyAllWindows()
<html lang="en">
<head>
<title>Intelligent Security Guard for Historical places</title>
<meta charset="utf-8">
<meta name="viewport" content="width=device-width, initial-scale=1">
<link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/bootstrap/3.3.7/css/bootstrap.min.css">
<script src="https://ajax.googleapis.com/ajax/libs/jquery/3.1.1/jquery.min.js"></script>
<script src="https://maxcdn.bootstrapcdn.com/bootstrap/3.3.7/js/bootstrap.min.js"></script>
<script src="https://sdk.amazonaws.com/js/aws-sdk-2.7.16.min.js"></script>
<style>
.navbar-custom
{
background-color:#0b5d75ed;
}
.header1
{
text-align : center;
vertical-align:middle;
float: none;
font-size:170%;
}
h2
{
color : #f0ad4e;
}
.cl
{
margin-top: 90px;
}
h3 {
text-align : center;
color: #0b5d75ed;
}
#s3_images{
border: 1px solid #f0ad4e;
border-radius: 5px;
padding: 10px;
}
.cs
{
margin: 6px;
}
</style>
</head>
<body>
<nav class="navbar navbar-default navbar-fixed-top navbar-custom">
<div class="container-fluid">
<div class="header1">
<h2>Intelligent Security Guard for Historical Places</h2>
</div>
</div>
</nav>
<div class="container cl" >
<div class="row new_search" >
<div class="col-sm-2" >
</div>
<div class="col-sm-10" >
<div class="row" id="app_serch">
<div class="col-sm-3">
<input type="number" class="form-control" placeholder="Set Hours " id="hour">
</div>
<div class="col-sm-3">
<input type="number" class="form-control" placeholder="Set Start Minuts " id="sminut">
</div>
<div class="col-sm-3">
<input type="number" class="form-control" placeholder="Set End Minutes" id="eminut">
</div>
<div class="col-sm-3">
<button class="btn btn-info" id="search_btn"><i class="fa fa-search"></i> Set Time</button>
</div>
</div>
</div>
</div>
<div class="row">
<div id="list_folder">
</div>
</div>
<div class="row">
<h3>People who are Present in Historical Place after Closing Hours </h3><hr>
<div class="col-sm-1">
</div>
<div id="s3_images" class="col-sm-10">
<h4>Waiting for Images</h4>
</div>
<div class="col-sm-1">
</div>
</div>
<div class="row">
<h3>People who visited and left the Musium </h3><hr>
<div class="col-sm-1">
</div>
<div id="exit_images" class="col-sm-10">
<h4>Waiting for Images</h4>
</div>
<div class="col-sm-1">
</div>
</div>
<div class="row">
<h3>Visitors Images</h3><hr>
<div class="col-sm-1">
</div>
<div id="visit_images" class="col-sm-10">
<h4>Waiting for Images</h4>
</div>
<div class="col-sm-1">
</div>
</div>
<div class="row">
<br><br>
</div>
</div>
</body>
<html>
<script type="text/javascript">
var html = '';
var html1 = '';
var html2 = '';
var albumBucketName = 'dayaalibucket1';
var BucketName = 'historical123';
var bucketRegion = 'us-east-1';
var IdentityPoolId = 'us-east-1:09badf75-df0f-4567-b3c7-f5459a3869a0';
var folder = 'entry';
var folder1 = 'visitors';
var folder2 = 'exit';
AWS.config.update({
region: bucketRegion,
credentials: new AWS.CognitoIdentityCredentials({
IdentityPoolId: IdentityPoolId
})
});
var s3 = new AWS.S3({
apiVersion: '2006-03-01',
params: {Bucket: albumBucketName}
});
var s3_new = new AWS.S3({
apiVersion: '2006-03-01',
params: {Bucket: BucketName}
});
viewAlbum(folder);
viewAlbum1(folder1);
viewAlbum2(folder2);
function viewAlbum(albumName) {
var albumPhotosKey = encodeURIComponent(albumName) + '/';
s3.listObjects({Prefix: albumPhotosKey}, function(err, data) {
if (err) {
return alert('There was an error viewing your album: ' + err.message);
}
// `this` references the AWS.Response instance that represents the response
var href = this.request.httpRequest.endpoint.href;
var bucketUrl = href + albumBucketName + '/';
var photos = data.Contents.map(function(photo) {
var photoKey = photo.Key;
console.log(photoKey);
var photoUrl = bucketUrl + encodeURIComponent(photoKey);
console.log(photoUrl);
if(photoUrl.indexOf('.jpg') > 0 || photoUrl.indexOf('.png') > 0 || photoUrl.indexOf('.jpeg') > 0)
{
// Found world
html += '<div class="col-sm-2">';
html += '<img src="'+photoUrl+'" class="img-thumbnail cs" alt="Image">';
html += '<span>';
html += photoKey.replace(albumPhotosKey, '');
html += '</span>';
html += '</div>';
}
});
$('#s3_images').html(html);
});
}
function viewAlbum2(albumName) {
console.log(albumName);
var albumPhotosKey = encodeURIComponent(albumName) + '/';
s3.listObjects({Prefix: albumPhotosKey}, function(err, data) {
if (err) {
return alert('There was an error viewing your album: ' + err.message);
}
// `this` references the AWS.Response instance that represents the response
var href = this.request.httpRequest.endpoint.href;
var bucketUrl = href + albumBucketName + '/';
var photos = data.Contents.map(function(photo) {
var photoKey = photo.Key;
var photoUrl = bucketUrl + encodeURIComponent(photoKey);
console.log(photoUrl);
if(photoUrl.indexOf('.jpg') > 0 || photoUrl.indexOf('.png') > 0 || photoUrl.indexOf('.jpeg') > 0)
{
// Found world
html2 += '<div class="col-sm-2">';
html2 += '<img src="'+photoUrl+'" class="img-thumbnail cs" alt="Image">';
html2 += '<span>';
html2 += photoKey.replace(albumPhotosKey, '');
html2 += '</span>';
html2 += '</div>';
}
});
$('#exit_images').html(html2);
});
}
function viewAlbum1(albumName) {
var albumPhotosKey = encodeURIComponent(albumName) + '/';
s3_new.listObjects({Prefix: albumPhotosKey}, function(err, data) {
if (err) {
return alert('There was an error viewing your album: ' + err.message);
}
// `this` references the AWS.Response instance that represents the response
var href = this.request.httpRequest.endpoint.href;
var bucketUrl = href + BucketName + '/';
var photos = data.Contents.map(function(photo) {
var photoKey = photo.Key;
var photoUrl = bucketUrl + encodeURIComponent(photoKey);
console.log(photoUrl);
if(photoUrl.indexOf('.jpg') > 0 || photoUrl.indexOf('.png') > 0 || photoUrl.indexOf('.jpeg') > 0)
{
// Found world
html1 += '<div class="col-sm-2">';
html1 += '<img src="'+photoUrl+'" class="img-thumbnail cs" alt="Image">';
html1 += '<div style="word-wrap: break-word;">';
html1 += photoKey.replace(albumPhotosKey, '');
html1 += '</div>';
html1 += '</div>';
}
});
$('#visit_images').html(html1);
});
}
$('#search_btn').click(function(){
var hr1 = $('#hour').val();
var smt1 = $('#sminut').val();
var smt2 = $('#eminut').val();
if((hr1!= "")&&(smt1 != "")&&(smt2 != ""))
{
$.post("https://api.thingspeak.com/update?api_key=71L2TOEK1LBXUBVA&field1="+hr1+"&field2="+smt1+"&field3="+smt2,
{
},
function(data,status){
alert("Time Updated Successfully ");
});
}
else
{
alert("Please Enter Hours ,Starting Minuts , Ending Minuts Properly");
}
$('#hour').val('');
$('#sminut').val('');
$('#eminut').val('');
});
</script>
Comments