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updat_edit2.py
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updat_edit2.py
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# -*- coding: utf-8 -*-
"""
Created on Fri Aug 23 16:41:58 2019
@author: robin
"""
import tensorflow as tf
import numpy as np
import facenet
from align import detect_face
import cv2
import argparse
import pandas as pd
import csv
import smtplib
from email.mime.text import MIMEText
from email.mime.multipart import MIMEMultipart
from email.mime.base import MIMEBase
from email import encoders
emal1=[]
nam1=[]
embd1=[]
title=[['emailid','name','userphoto']]
tf.reset_default_graph()
# some constants kept as default from facenet
minsize = 20
threshold = [0.6, 0.7, 0.7]
factor = 0.709
margin = 44
input_image_size = 160
j=0
sess = tf.Session()
thresholde=.9
k=0
# read pnet, rnet, onet models from align directory and files are det1.npy, det2.npy, det3.npy
pnet, rnet, onet = detect_face.create_mtcnn(sess, 'align')
#names=[' ','anirudh',' ','surya','achutha','yogesh','sanyukta','ishita','robin','abishek','saquib','abha','pankhi','stuti','']
names=[]
vecs=[]
#names=[' ','anirudh',' ','surya','achutha',' ',' ',' ',' ',' ',' ',' ',' ',' ','jasper','anand','anuj','skandhan','Aravindraj','Natraj','Ashwin','Jones','Jeffery','deepak']
facenet.load_model("20170512-110547/20170512-110547.pb")
#names=np.load("G:/FaceDetection/facematch/names.npy")
# Get input and output tensors
images_placeholder = tf.get_default_graph().get_tensor_by_name("input:0")
embeddings = tf.get_default_graph().get_tensor_by_name("embeddings:0")
phase_train_placeholder = tf.get_default_graph().get_tensor_by_name("phase_train:0")
embedding_size = embeddings.get_shape()[1]
def getFace(img):
faces = []
img_size = np.asarray(img.shape)[0:2]
bounding_boxes, _ = detect_face.detect_face(img, minsize, pnet, rnet, onet, threshold, factor)
if not len(bounding_boxes) == 0:
for face in bounding_boxes:
if face[4] > 0.50:
det = np.squeeze(face[0:4])
bb = np.zeros(4, dtype=np.int32)
bb[0] = np.maximum(det[0] - margin / 2, 0)
bb[1] = np.maximum(det[1] - margin / 2, 0)
bb[2] = np.minimum(det[2] + margin / 2, img_size[1])
bb[3] = np.minimum(det[3] + margin / 2, img_size[0])
cropped = img[bb[1]:bb[3], bb[0]:bb[2], :]
resized = cv2.resize(cropped, (input_image_size,input_image_size),interpolation=cv2.INTER_CUBIC)
prewhitened = facenet.prewhiten(resized)
faces.append({'face':resized,'rect':[bb[0],bb[1],bb[2],bb[3]],'embedding':getEmbedding(prewhitened)})
return faces
def getEmbedding(resized):
reshaped = resized.reshape(-1,input_image_size,input_image_size,3)
feed_dict = {images_placeholder: reshaped, phase_train_placeholder: False}
embedding = sess.run(embeddings, feed_dict=feed_dict)
#file=open("em.txt",'w')
#cont=file.write(np.array_str(embedding))
# print(embedding)
#data={'points':[embedding]}
#df=pd.DataFrame(data)
#df.to_csv('neon.csv',index='false')
# print('File Successfully written.')
return embedding
#file.close()
def compare2face(facess):
ind=0
flag='False'
for i in range(len(vecs)):
#print(npys[i].shape,facess.shape)
dist=np.sqrt(np.sum(np.square(np.subtract(vecs[i], facess))))
#dist=int(dist)
if dist<=thresholde:
ind=i+1
return ind
#print(dist)
# calculate Euclidean distance
#dist = np.sqrt(np.sum(np.square(np.subtract(i, facess))))
# ind=i+1
# break
flag='True'
return flag
cap = cv2.VideoCapture(0)#"GH011493.mp4")#0)
z=0
mail_list=[]
ret, image = cap.read()
[h, w] = image.shape[:2]
out = cv2.VideoWriter("test_out.avi", 0, 25.0, (w, h))
name_index_counter=0
while(cap.isOpened()):
ret, frame = cap.read()
print('z',z)
if z%4==0 and ret==True:
#img = imutils.resize(frame,width=1000)
faces = getFace(frame)
for face in faces:
#file=open("em.txt",'w')
#cont=file.write()
cv2.rectangle(frame,(face['rect'][0], face['rect'][1]), (face['rect'][2], face['rect'][3]), (0, 255, 0), 2)
name=compare2face(face['embedding'])
if name=='True':
email=input("Enter your email-id:")
nam=input("Enter your name")
emal1.append(email)
nam1.append(nam)
embd1.append(face['embedding'])
print(emal1)
print(nam1)
j=j+1
vecs.append(face['embedding'])
names.append(str(name_index_counter))
mail_list.append(str(email))
name_index_counter += 1
else:
nm=mail_list[name-1]
email_user = 'shopfinite6@gmail.com'
email_password = 'wewillwin'
email_send = nm
subject = 'Welcome To FiniteShop'
msg = MIMEMultipart()
msg['From'] = email_user
msg['To'] = email_send
msg['Subject'] = subject
body = 'Check out our newest arrival of apparels, Exciting discounts on Pants, Shirts, Casuals.Latest arrival of electronic goods.'
msg.attach(MIMEText(body,'plain'))
filename='finite.jpg'
attachment =open(filename,'rb')
print("The total customers till now:")
print (j)
part = MIMEBase('application','octet-stream')
part.set_payload((attachment).read())
encoders.encode_base64(part)
part.add_header('Content-Disposition',"attachment; filename= "+filename)
msg.attach(part)
text = msg.as_string()
try:
server = smtplib.SMTP('smtp.gmail.com',587)
server.starttls()
server.login(email_user,email_password)
server.sendmail(email_user,email_send,text)
server.quit()
print('Done')
except:
print("Failed to send the Email!\nPlease check whether you have entered the name of the file properly")
# =============================================================================
# if(name==0):
# for k in range(0,400):
# with open('neon.csv','a') as csvfile :
# # g=embedding[0][0]
# colnames=['id', 'embd']
# writer=csv.writer(csvfile)
# writer.writerow([k,face['embedding']])
#
# data=pd.read_csv("neon.csv")
# data_top=data.head(2)
# =============================================================================
# print(names[name])
#file.close()
#cv2.putText(frame, names[name], (face['rect'][0],face['rect'][1]-15), cv2.FONT_HERSHEY_SIMPLEX, 1.0, (0, 255, 255), lineType=cv2.LINE_AA)
#cv2.imshow('img',faces[0]['face'])
cv2.imshow("faces", frame)
out.write(frame)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
z += 1
dict={"name":nam1,"email-id":emal1,"embedding":embd1}
df=pd.DataFrame(dict)
df.to_csv('dota.csv')
#print([names])
#print([vecs])
cv2.destroyAllWindows()
cap.release()
print("The total customers in this day:")
print(j)
out.release()
# =============================================================================
# img = cv2.imread("G://FaceDetection//facematch//images//Esha-gupta.jpg",1)
# #img = imutils.resize(img,width=1000)
# faces = getFace(img)
# for face in faces:
# cv2.rectangle(img, (face['rect'][0], face['rect'][1]), (face['rect'][2], face['rect'][3]), (0, 255, 0), 2)
# cv2.imshow("faces", img)
# cv2.waitKey(0)
# cv2.destroyAllWindows()
# =============================================================================