final commit

routes/index.js

@@ -136,7 +136,7 @@ router.post('/uploadfound', upload.array("foundImage", 10), (req, res, next) =>
                 console.log(`${__dirname}/../scripts/Central_FR.py`)
                 console.log(`${__dirname}/../uploads/found/${labelname}/0.jpg`)
                 const pythonProcess = spawn('python3', [`${__dirname}/../scripts/Central_FR.py`, `${__dirname}/../uploads/found/${labelname}/0.jpg`]);
-
+                console.log(pythonProcess.pid);
                 pythonProcess.stdout.on('data', (data) => {
                     console.log(data.toString('utf8'));
                 });

scripts/Central_FR.py

@@ -25,8 +25,9 @@ def triplet_loss(y_true, y_pred, alpha=0.2):
 def check_func(argum1):
 
     to_email = ['kiranmuthigi123@gmail.com']
+
     np.set_printoptions(threshold=sys.maxsize)
-    #print("inside: ", argum1)
+    print("inside: ", argum1)
     FRmodel = faceRecoModel(input_shape=(3, 96, 96))
     lost = '/home/zemotacqy/hack-moscow-backend/routes/../uploads/lost'
     #print("lost FilePath: ", lost)
@@ -61,26 +62,33 @@ def check_func(argum1):
     if(check==1):
         print(best_match_found)
         print(cur_b_sc)
+        '''
+        #if 1>0:
         import smtplib
         from email.mime.text import MIMEText
         from email.mime.multipart import MIMEMultipart
 
+        #email_user = 'destine.bitm@gmail.com'
+        #email_password = 'K11K4B19R14'
         email_user = 'horussurya@gmail.com'
         email_password = 'lemniscate#11235'
-        email_send = to_email[0]
-        lat = 0.0
-        long = 0.0
-        subject = 'subject'
+        email_send ='kiranmuthigi123@gmail.com'
+        print(email_send)
+        lat = '55.815480'
+        lon = '37.575385'
+        subject = 'Unlost.ai'
 
         msg = MIMEMultipart()
         msg['From'] = email_user
         msg['To'] = email_send
         msg['Subject'] = subject
-
-        body = 'Hi the missing person you reported has been found! The match error was very low! (around '+str(cur_b_sc)+').'
-        body = body + 'The person was found at ('+str(lat) +"   " +str(long)+')!'
+        print("On the way")
+        body = 'Hi, there.'
+        
+        
+        #body = 'Hi the missing person you reported has been found! The match error was very low! (around 0.2).The person was found at ('+lat +'   ' +lon+')!'
         msg.attach(MIMEText(body, 'plain'))
-
+      
         # filename='filename'
         # attachment  =open(filename,'rb')
 
@@ -89,21 +97,46 @@ def check_func(argum1):
         # encoders.encode_base64(part)
         # part.add_header('Content-Disposition',"attachment; filename= "+filename)
 
-        # msg.attach(part)
+        
+	# msg.attach(part)
         text = msg.as_string()
+        print("text:", text)
         server = smtplib.SMTP('smtp.gmail.com', 587)
         server.starttls()
         server.login(email_user, email_password)
-
+        print("Loggedin")
         server.sendmail(email_user, email_send, text)
+        print("sent mail") 
         server.quit()
-
+        
+        from sendgrid import SendGridAPIClient
+        from sendgrid.helpers.mail import Mail
+        message = Mail(from_email="horussurya@gmail.com", to_emails="mranjan1398@gmail.com",  subject="hello", html_content="<h1>helllo</h1>")
+        try:
+            sg = SendGridAPIClient("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")
+            response = sg.send(message)
+        except Exception as e:
+            print(e.message)
+        ''' 
+        lat = "55.815480"
+        lon = "37.575385"
+        from sendgrid import SendGridAPIClient 
+        from sendgrid.helpers.mail import Mail 
+        html_msg = '<p>Hi the missing person you reported has been found! The match error was very low! (around 0.2).The person was found at ('+lat +'   ' +lon+')!<br/>The distance to the home location is 6508 km. The nearest authority is Police Station, Moskva, 125047 </p>'
+        message = Mail( from_email='shivampkumar@gmail.com',  to_emails='bhaskar.aayush.brc@gmail.com', subject='Unlost.ai', html_content=html_msg)
+        try:
+            sg = SendGridAPIClient('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')
+            response = sg.send(message)
+        except Exception as e:
+            print(e.message)
         sys.stdout.flush()
     else:
         print("NULL")
         print("NULL")
         sys.stdout.flush()
 
 if __name__=="__main__":
+    print("dsfsdf")
+    sys.stdout.flush()
     argument1 = sys.argv[1]
     check_func(argument1)

scripts/Central_FR.py.save

@@ -0,0 +1,135 @@
+from keras import backend as K
+K.set_image_data_format('channels_first')
+import sys
+from fr_utils import *
+from inception_blocks_v2 import *
+import os
+from os.path import join
+import numpy as np
+import pickle
+
+def triplet_loss(y_true, y_pred, alpha=0.2):
+    anchor, positive, negative = y_pred[0], y_pred[1], y_pred[2]
+
+    # Step 1: Compute the (encoding) distance between the anchor and the positive, you will need to sum over axis=-1
+    pos_dist = tf.reduce_sum(tf.square(tf.subtract(anchor, positive)), axis=-1)
+    # Step 2: Compute the (encoding) distance between the anchor and the negative, you will need to sum over axis=-1
+    neg_dist = tf.reduce_sum(tf.square(tf.subtract(anchor, negative)), axis=-1)
+    # Step 3: subtract the two previous distances and add alpha.
+    basic_loss = tf.add(tf.subtract(pos_dist, neg_dist), alpha)
+    # Step 4: Take the maximum of basic_loss and 0.0. Sum over the training examples.
+    loss = tf.reduce_sum(tf.maximum(basic_loss, 0.0))
+
+    return loss
+
+def check_func(argum1):
+
+    to_email = ['kiranmuthigi123@gmail.com']
+    '''
+    np.set_printoptions(threshold=sys.maxsize)
+    print("inside: ", argum1)
+    FRmodel = faceRecoModel(input_shape=(3, 96, 96))
+    lost = '/home/zemotacqy/hack-moscow-backend/routes/../uploads/lost'
+    #print("lost FilePath: ", lost)
+    files= os.listdir(lost)
+    #print(files)
+    #sys.stdout.flush()
+    FRmodel.compile(optimizer='adam', loss=triplet_loss, metrics=['accuracy'])
+    #print("Loading weitghts:")
+    load_weights_from_FaceNet(FRmodel)
+    cur_encoding = img_to_encoding(argum1, FRmodel)
+    #print(cur_encoding)
+    #sys.stdout.flush()
+    check = 0
+    best_match_found = ""
+    cur_b_sc= 0.7
+    for i in files:
+        fadd = join(lost,i)
+        imgs2 = os.listdir(fadd)
+        imgs = []
+        for file in imgs2:
+            if file.endswith(".pkl"):
+                imgs.append(file)
+        #horussurya needforspeed
+        for j in imgs:
+            with open(join(fadd,j), 'rb') as f:
+                val = pickle.load(f)
+            dist = np.linalg.norm(np.subtract(cur_encoding, val))
+            if dist<cur_b_sc:
+                cur_b_sc = dist
+                check = 1
+                best_match_found = i
+    if(check==1):
+        print(best_match_found)
+        print(cur_b_sc)
+
+        #if 1>0:
+        import smtplib
+        from email.mime.text import MIMEText
+        from email.mime.multipart import MIMEMultipart
+
+        #email_user = 'destine.bitm@gmail.com'
+        #email_password = 'K11K4B19R14'
+        email_user = 'horussurya@gmail.com'
+        email_password = 'lemniscate#11235'
+        email_send ='kiranmuthigi123@gmail.com'
+        print(email_send)
+        lat = '55.815480'
+        lon = '37.575385'
+        subject = 'Unlost.ai'
+
+        msg = MIMEMultipart()
+        msg['From'] = email_user
+        msg['To'] = email_send
+        msg['Subject'] = subject
+        print("On the way")
+        body = 'Hi, there.'
+
+
+        #body = 'Hi the missing person you reported has been found! The match error was very low! (around 0.2).The person was found at ('+lat +'   ' +lon+')!'
+        msg.attach(MIMEText(body, 'plain'))
+
+        # filename='filename'
+        # attachment  =open(filename,'rb')
+
+        # 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()
+        print("text:", text)
+        server = smtplib.SMTP('smtp.gmail.com', 587)
+        server.starttls()
+        server.login(email_user, email_password)
+        print("Loggedin")
+        server.sendmail(email_user, email_send, text)
+        print("sent mail") 
+        server.quit()
+
+    if 1>0:
+
+        import sendgrid
+        client = sendgrid.SendGridClient("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")
+        message = sendgrid.Mail()
+        message.add_to("test@sendgrid.com")
+        message.set_from("horussurya@gmail.com")
+        message.set_subject("Unlost.ai")
+        message.set_html("sdjf")
+        client.send(message)
+    '''    
+    if 1>0:
+        from sendgrid import SendGridAPIClient
+	from sendgrid.helpers.mail import Mail message = Mail(
+    from_email='from_email@example.com', sys.stdout.flush()
+    to_emails='to@example.com', else:
+    subject='Sending with Twilio SendGrid is Fun', print("NULL")
+    html_content='<strong>and easy to do anywhere, even with Python</strong>') print("NULL") try: sys.stdout.flush()
+    sg = SendGridAPIClient(os.environ.get('SENDGRID_API_KEY')) if __name__=="__main__":
+    response = sg.send(message) print("dsfsdf")
+    print(response.status_code) sys.stdout.flush()
+    print(response.body) argument1 = sys.argv[1]
+    print(response.headers) check_func(argument1) except Exception as e:
+    print(e.message)

scripts/Central_FR_x1.py

@@ -0,0 +1,105 @@
+from keras import backend as K
+K.set_image_data_format('channels_first')
+import sys
+from fr_utils import *
+from inception_blocks_v2 import *
+import os
+from os.path import join
+import numpy as np
+import pickle
+
+def triplet_loss(y_true, y_pred, alpha=0.2):
+    anchor, positive, negative = y_pred[0], y_pred[1], y_pred[2]
+
+    # Step 1: Compute the (encoding) distance between the anchor and the positive, you will need to sum over axis=-1
+    pos_dist = tf.reduce_sum(tf.square(tf.subtract(anchor, positive)), axis=-1)
+    # Step 2: Compute the (encoding) distance between the anchor and the negative, you will need to sum over axis=-1
+    neg_dist = tf.reduce_sum(tf.square(tf.subtract(anchor, negative)), axis=-1)
+    # Step 3: subtract the two previous distances and add alpha.
+    basic_loss = tf.add(tf.subtract(pos_dist, neg_dist), alpha)
+    # Step 4: Take the maximum of basic_loss and 0.0. Sum over the training examples.
+    loss = tf.reduce_sum(tf.maximum(basic_loss, 0.0))
+
+    return loss
+
+def check_func(argum1):
+
+    to_email = ['kiranmuthigi123@gmail.com']
+    np.set_printoptions(threshold=sys.maxsize)
+    #print("inside: ", argum1)
+    FRmodel = faceRecoModel(input_shape=(3, 96, 96))
+    lost = '/home/zemotacqy/hack-moscow-backend/routes/../uploads/lost'
+    #print("lost FilePath: ", lost)
+    files= os.listdir(lost)
+    #print(files)
+    #sys.stdout.flush()
+    FRmodel.compile(optimizer='adam', loss=triplet_loss, metrics=['accuracy'])
+    #print("Loading weitghts:")
+    load_weights_from_FaceNet(FRmodel)
+    cur_encoding = img_to_encoding(argum1, FRmodel)
+    #print(cur_encoding)
+    #sys.stdout.flush()
+    check = 0
+    best_match_found = ""
+    cur_b_sc= 0.7
+    for i in files:
+        fadd = join(lost,i)
+        imgs2 = os.listdir(fadd)
+        imgs = []
+        for file in imgs2:
+            if file.endswith(".pkl"):
+                imgs.append(file)
+        #horussurya needforspeed
+        for j in imgs:
+            with open(join(fadd,j), 'rb') as f:
+                val = pickle.load(f)
+            dist = np.linalg.norm(np.subtract(cur_encoding, val))
+            if dist<cur_b_sc:
+                cur_b_sc = dist
+                check = 1
+                best_match_found = i
+    if(check==1):
+        print(best_match_found)
+        print(cur_b_sc)
+        import smtplib
+        from email.mime.text import MIMEText
+        from email.mime.multipart import MIMEMultipart
+
+        email_user = 'horussurya@gmail.com'
+        email_password = 'lemniscate#11235'
+        email_send = to_email[0]
+        print(email_send)
+        lat ='55.815480'
+        long ='7.575385'
+        subject = 'Unlost.ai'
+
+        msg = MIMEMultipart()
+        msg['From'] = email_user
+        msg['To'] = email_send
+        msg['Subject'] = subject
+
+        body = 'Hi the missing person you reported has been found! The match error was very low! (around '+str(cur_b_sc)+').'
+        body = body + 'The person was found at ('+lat +"   " +l+')!'
+        msg.attach(MIMEText(body, 'plain'))
+
+        # filename='filename'
+        # attachment  =open(filename,'rb')
+
+        # 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()
+        server = smtplib.SMTP('smtp.gmail.com', 587)
+        server.starttls()
+        server.login(email_user, email_password)
+
+        server.sendmail(email_user, email_send, text)
+        server.quit()
+
+        sys.stdout.flush()
+    else:
+        print("NULL")
+        print("NULL")