From 6cbd67bb7232e2ed499a1b94b51d255cbaea0183 Mon Sep 17 00:00:00 2001
From: Navan Chauhan <navanchauhan@gmail.com>
Date: Sat, 11 May 2019 21:38:22 +0530
Subject: Initial Commit

---
 Safety Toolkit-2.pdf                               |   Bin 0 -> 199947 bytes
 files/.DS_Store                                    |   Bin 0 -> 6148 bytes
 files/bac.txt                                      |     1 +
 files/carSpeed.txt                                 |     1 +
 files/haarcascade_eye.xml                          | 12213 +++++++
 files/haarcascade_frontalface_default.xml          | 33314 +++++++++++++++++++
 files/haarcascade_lefteye_2splits.xml              |  7390 ++++
 files/haarcascade_righteye_2splits.xml             |  7407 +++++
 files/shape_predictor_68_face_landmarks.dat        |   Bin 0 -> 99693937 bytes
 function-specific-programs/.DS_Store               |   Bin 0 -> 6148 bytes
 function-specific-programs/1.json                  |     1 +
 .../__pycache__/tweepy.cpython-37.pyc              |   Bin 0 -> 1450 bytes
 function-specific-programs/drunk.py                |    25 +
 function-specific-programs/ear.py                  |   117 +
 function-specific-programs/speedlimit.py           |    35 +
 function-specific-programs/tweet.py                |    43 +
 function-specific-programs/zomato-api.txt          |     1 +
 function-specific-programs/zomato.py               |    41 +
 main.py                                            |   345 +
 19 files changed, 60934 insertions(+)
 create mode 100644 Safety Toolkit-2.pdf
 create mode 100644 files/.DS_Store
 create mode 100644 files/bac.txt
 create mode 100644 files/carSpeed.txt
 create mode 100644 files/haarcascade_eye.xml
 create mode 100644 files/haarcascade_frontalface_default.xml
 create mode 100644 files/haarcascade_lefteye_2splits.xml
 create mode 100644 files/haarcascade_righteye_2splits.xml
 create mode 100644 files/shape_predictor_68_face_landmarks.dat
 create mode 100644 function-specific-programs/.DS_Store
 create mode 100644 function-specific-programs/1.json
 create mode 100644 function-specific-programs/__pycache__/tweepy.cpython-37.pyc
 create mode 100644 function-specific-programs/drunk.py
 create mode 100644 function-specific-programs/ear.py
 create mode 100644 function-specific-programs/speedlimit.py
 create mode 100644 function-specific-programs/tweet.py
 create mode 100644 function-specific-programs/zomato-api.txt
 create mode 100644 function-specific-programs/zomato.py
 create mode 100755 main.py

diff --git a/Safety Toolkit-2.pdf b/Safety Toolkit-2.pdf
new file mode 100644
index 0000000..e8a689c
Binary files /dev/null and b/Safety Toolkit-2.pdf differ
diff --git a/files/.DS_Store b/files/.DS_Store
new file mode 100644
index 0000000..5c0c762
Binary files /dev/null and b/files/.DS_Store differ
diff --git a/files/bac.txt b/files/bac.txt
new file mode 100644
index 0000000..d8263ee
--- /dev/null
+++ b/files/bac.txt
@@ -0,0 +1 @@
+2
\ No newline at end of file
diff --git a/files/carSpeed.txt b/files/carSpeed.txt
new file mode 100644
index 0000000..209e3ef
--- /dev/null
+++ b/files/carSpeed.txt
@@ -0,0 +1 @@
+20
diff --git a/files/haarcascade_eye.xml b/files/haarcascade_eye.xml
new file mode 100644
index 0000000..b21e3b9
--- /dev/null
+++ b/files/haarcascade_eye.xml
@@ -0,0 +1,12213 @@
+<?xml version="1.0"?>
+<!--
+    Stump-based 20x20 frontal eye detector.
+    Created by Shameem Hameed (http://umich.edu/~shameem)
+
+////////////////////////////////////////////////////////////////////////////////////////
+
+  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+
+  By downloading, copying, installing or using the software you agree to this license.
+  If you do not agree to this license, do not download, install,
+  copy or use the software.
+
+
+                        Intel License Agreement
+                For Open Source Computer Vision Library
+
+ Copyright (C) 2000, Intel Corporation, all rights reserved.
+ Third party copyrights are property of their respective owners.
+
+ Redistribution and use in source and binary forms, with or without modification,
+ are permitted provided that the following conditions are met:
+
+   * Redistribution's of source code must retain the above copyright notice,
+     this list of conditions and the following disclaimer.
+
+   * Redistribution's in binary form must reproduce the above copyright notice,
+     this list of conditions and the following disclaimer in the documentation
+     and/or other materials provided with the distribution.
+
+   * The name of Intel Corporation may not be used to endorse or promote products
+     derived from this software without specific prior written permission.
+
+ This software is provided by the copyright holders and contributors "as is" and
+ any express or implied warranties, including, but not limited to, the implied
+ warranties of merchantability and fitness for a particular purpose are disclaimed.
+ In no event shall the Intel Corporation or contributors be liable for any direct,
+ indirect, incidental, special, exemplary, or consequential damages
+ (including, but not limited to, procurement of substitute goods or services;
+ loss of use, data, or profits; or business interruption) however caused
+ and on any theory of liability, whether in contract, strict liability,
+ or tort (including negligence or otherwise) arising in any way out of
+ the use of this software, even if advised of the possibility of such damage.
+-->
+<opencv_storage>
+<cascade type_id="opencv-cascade-classifier"><stageType>BOOST</stageType>
+  <featureType>HAAR</featureType>
+  <height>20</height>
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diff --git a/files/haarcascade_frontalface_default.xml b/files/haarcascade_frontalface_default.xml
new file mode 100644
index 0000000..cbd1aa8
--- /dev/null
+++ b/files/haarcascade_frontalface_default.xml
@@ -0,0 +1,33314 @@
+<?xml version="1.0"?>
+<!--
+    Stump-based 24x24 discrete(?) adaboost frontal face detector.
+    Created by Rainer Lienhart.
+
+////////////////////////////////////////////////////////////////////////////////////////
+
+  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+
+  By downloading, copying, installing or using the software you agree to this license.
+  If you do not agree to this license, do not download, install,
+  copy or use the software.
+
+
+                        Intel License Agreement
+                For Open Source Computer Vision Library
+
+ Copyright (C) 2000, Intel Corporation, all rights reserved.
+ Third party copyrights are property of their respective owners.
+
+ Redistribution and use in source and binary forms, with or without modification,
+ are permitted provided that the following conditions are met:
+
+   * Redistribution's of source code must retain the above copyright notice,
+     this list of conditions and the following disclaimer.
+
+   * Redistribution's in binary form must reproduce the above copyright notice,
+     this list of conditions and the following disclaimer in the documentation
+     and/or other materials provided with the distribution.
+
+   * The name of Intel Corporation may not be used to endorse or promote products
+     derived from this software without specific prior written permission.
+
+ This software is provided by the copyright holders and contributors "as is" and
+ any express or implied warranties, including, but not limited to, the implied
+ warranties of merchantability and fitness for a particular purpose are disclaimed.
+ In no event shall the Intel Corporation or contributors be liable for any direct,
+ indirect, incidental, special, exemplary, or consequential damages
+ (including, but not limited to, procurement of substitute goods or services;
+ loss of use, data, or profits; or business interruption) however caused
+ and on any theory of liability, whether in contract, strict liability,
+ or tort (including negligence or otherwise) arising in any way out of
+ the use of this software, even if advised of the possibility of such damage.
+-->
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diff --git a/files/haarcascade_lefteye_2splits.xml b/files/haarcascade_lefteye_2splits.xml
new file mode 100644
index 0000000..9a9ef58
--- /dev/null
+++ b/files/haarcascade_lefteye_2splits.xml
@@ -0,0 +1,7390 @@
+<?xml version="1.0"?>
+<!--
+    Tree-based 20x20 left eye detector.
+    The detector is trained by 6665 positive samples from FERET, VALID and BioID face databases. 
+    Created by Shiqi Yu (http://yushiqi.cn/research/eyedetection).
+
+////////////////////////////////////////////////////////////////////////////////////////
+
+  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+
+  By downloading, copying, installing or using the software you agree to this license.
+  If you do not agree to this license, do not download, install,
+  copy or use the software.
+
+
+                        Intel License Agreement
+                For Open Source Computer Vision Library
+
+ Copyright (C) 2000, Intel Corporation, all rights reserved.
+ Third party copyrights are property of their respective owners.
+
+ Redistribution and use in source and binary forms, with or without modification,
+ are permitted provided that the following conditions are met:
+
+   * Redistribution's of source code must retain the above copyright notice,
+     this list of conditions and the following disclaimer.
+
+   * Redistribution's in binary form must reproduce the above copyright notice,
+     this list of conditions and the following disclaimer in the documentation
+     and/or other materials provided with the distribution.
+
+   * The name of Intel Corporation may not be used to endorse or promote products
+     derived from this software without specific prior written permission.
+
+ This software is provided by the copyright holders and contributors "as is" and
+ any express or implied warranties, including, but not limited to, the implied
+ warranties of merchantability and fitness for a particular purpose are disclaimed.
+ In no event shall the Intel Corporation or contributors be liable for any direct,
+ indirect, incidental, special, exemplary, or consequential damages
+ (including, but not limited to, procurement of substitute goods or services;
+ loss of use, data, or profits; or business interruption) however caused
+ and on any theory of liability, whether in contract, strict liability,
+ or tort (including negligence or otherwise) arising in any way out of
+ the use of this software, even if advised of the possibility of such damage.
+-->
+<opencv_storage>
+<cascade type_id="opencv-cascade-classifier"><stageType>BOOST</stageType>
+  <featureType>HAAR</featureType>
+  <height>20</height>
+  <width>20</width>
+  <stageParams>
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diff --git a/files/haarcascade_righteye_2splits.xml b/files/haarcascade_righteye_2splits.xml
new file mode 100644
index 0000000..db4571c
--- /dev/null
+++ b/files/haarcascade_righteye_2splits.xml
@@ -0,0 +1,7407 @@
+<?xml version="1.0"?>
+<!--
+    Tree-based 20x20 right eye detector.
+    The detector is trained by 6665 positive samples from FERET, VALID and BioID face databases. 
+    Created by Shiqi Yu (http://yushiqi.cn/research/eyedetection).
+
+////////////////////////////////////////////////////////////////////////////////////////
+
+  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+
+  By downloading, copying, installing or using the software you agree to this license.
+  If you do not agree to this license, do not download, install,
+  copy or use the software.
+
+
+                        Intel License Agreement
+                For Open Source Computer Vision Library
+
+ Copyright (C) 2000, Intel Corporation, all rights reserved.
+ Third party copyrights are property of their respective owners.
+
+ Redistribution and use in source and binary forms, with or without modification,
+ are permitted provided that the following conditions are met:
+
+   * Redistribution's of source code must retain the above copyright notice,
+     this list of conditions and the following disclaimer.
+
+   * Redistribution's in binary form must reproduce the above copyright notice,
+     this list of conditions and the following disclaimer in the documentation
+     and/or other materials provided with the distribution.
+
+   * The name of Intel Corporation may not be used to endorse or promote products
+     derived from this software without specific prior written permission.
+
+ This software is provided by the copyright holders and contributors "as is" and
+ any express or implied warranties, including, but not limited to, the implied
+ warranties of merchantability and fitness for a particular purpose are disclaimed.
+ In no event shall the Intel Corporation or contributors be liable for any direct,
+ indirect, incidental, special, exemplary, or consequential damages
+ (including, but not limited to, procurement of substitute goods or services;
+ loss of use, data, or profits; or business interruption) however caused
+ and on any theory of liability, whether in contract, strict liability,
+ or tort (including negligence or otherwise) arising in any way out of
+ the use of this software, even if advised of the possibility of such damage.
+-->
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+  <featureType>HAAR</featureType>
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China","url":"https:\/\/www.zomato.com\/ncr\/yo-china-vasant-vihar-new-delhi?utm_source=api_basic_user&utm_medium=api&utm_campaign=v2.1","location":{"address":"46, 1st Floor, Priya Cinema Complex, Basant Lok Market, Vasant Vihar, New Delhi","locality":"Basant Lok Market, Vasant Vihar","city":"New Delhi","city_id":1,"latitude":"28.5573965773","longitude":"77.1636349708","zipcode":"","country_id":1,"locality_verbose":"Basant Lok Market, Vasant Vihar, New Delhi"},"switch_to_order_menu":0,"cuisines":"Thai, Asian, Chinese, Beverages, Seafood, Momos","average_cost_for_two":1150,"price_range":3,"currency":"Rs.","offers":[],"zomato_events":[{"event":{"event_id":194525,"friendly_start_date":"01 December","friendly_end_date":"31 December","friendly_timing_str":"Saturday, 1st December - Monday, 31st December","start_date":"2018-12-01","end_date":"2018-12-31","end_time":"23:00:00","start_time":"11:00:00","is_active":1,"date_added":"2018-02-15 07:41:53","photos":[],"restaurants":[],"is_valid":1,"share_url":"http:\/\/www.zoma.to\/r\/0","show_share_url":0,"title":"BIRTHDAY PARTY KITTY PARTY","description":"Celebrate Memorable Birthday and Kitty parties with us @ 299 onwards with unlimited appetisers, rice\/noodle, main course, soft drinks, icecream and free decoration, games, prizes etc. Call us at 011 26151919\/1929","display_time":"11:00 am - 11:00 pm","display_date":"01 December - 31 December","is_end_time_set":1,"disclaimer":"Restaurants are solely responsible for the service; availability and quality of the events including all or any cancellations\/ modifications\/ complaints.","event_category":1,"event_category_name":"","book_link":"","types":[],"share_data":{"should_show":0}}}],"opentable_support":0,"is_zomato_book_res":0,"mezzo_provider":"OTHER","is_book_form_web_view":0,"book_form_web_view_url":"","book_again_url":"","thumb":"https:\/\/b.zmtcdn.com\/data\/reviews_photos\/06b\/8d69c91c75e296a1d66986a20f30306b_1462782211.jpg?fit=around%7C200%3A200&crop=200%3A200%3B%2A%2C%2A","user_rating":{"aggregate_rating":"3.7","rating_text":"Good","rating_color":"9ACD32","votes":"531"},"photos_url":"https:\/\/www.zomato.com\/ncr\/yo-china-vasant-vihar-new-delhi\/photos?utm_source=api_basic_user&utm_medium=api&utm_campaign=v2.1#tabtop","menu_url":"https:\/\/www.zomato.com\/ncr\/yo-china-vasant-vihar-new-delhi\/menu?utm_source=api_basic_user&utm_medium=api&utm_campaign=v2.1&openSwipeBox=menu&showMinimal=1#tabtop","featured_image":"https:\/\/b.zmtcdn.com\/data\/reviews_photos\/06b\/8d69c91c75e296a1d66986a20f30306b_1462782211.jpg","medio_provider":1,"has_online_delivery":1,"is_delivering_now":0,"include_bogo_offers":true,"deeplink":"zomato:\/\/restaurant\/304675","is_table_reservation_supported":1,"has_table_booking":0,"events_url":"https:\/\/www.zomato.com\/ncr\/yo-china-vasant-vihar-new-delhi\/events#tabtop?utm_source=api_basic_user&utm_medium=api&utm_campaign=v2.1"}},{"restaurant":{"R":{"res_id":18588949},"apikey":"a530c1424d9abe5442fa22f77ce03d25","id":"18588949","name":"Gabbars","url":"https:\/\/www.zomato.com\/ncr\/gabbars-vasant-vihar-new-delhi?utm_source=api_basic_user&utm_medium=api&utm_campaign=v2.1","location":{"address":"Shop No.15, DDA Shopping Centre, Munirka Vihar, Vasant Vihar, New Delhi","locality":"Vasant Vihar","city":"New Delhi","city_id":1,"latitude":"28.5543398000","longitude":"77.1668179000","zipcode":"110068","country_id":1,"locality_verbose":"Vasant Vihar, New Delhi"},"switch_to_order_menu":0,"cuisines":"Mughlai, North Indian","average_cost_for_two":700,"price_range":2,"currency":"Rs.","offers":[],"opentable_support":0,"is_zomato_book_res":0,"mezzo_provider":"OTHER","is_book_form_web_view":0,"book_form_web_view_url":"","book_again_url":"","thumb":"https:\/\/b.zmtcdn.com\/data\/pictures\/chains\/9\/18588949\/e349fb34fa2010d93000df99d823f3a7.jpg?fit=around%7C200%3A200&crop=200%3A200%3B%2A%2C%2A","user_rating":{"aggregate_rating":"4.5","rating_text":"Excellent","rating_color":"3F7E00","votes":"368"},"photos_url":"https:\/\/www.zomato.com\/ncr\/gabbars-vasant-vihar-new-delhi\/photos?utm_source=api_basic_user&utm_medium=api&utm_campaign=v2.1#tabtop","menu_url":"https:\/\/www.zomato.com\/ncr\/gabbars-vasant-vihar-new-delhi\/menu?utm_source=api_basic_user&utm_medium=api&utm_campaign=v2.1&openSwipeBox=menu&showMinimal=1#tabtop","featured_image":"https:\/\/b.zmtcdn.com\/data\/pictures\/chains\/9\/18588949\/e349fb34fa2010d93000df99d823f3a7.jpg","has_online_delivery":1,"is_delivering_now":1,"include_bogo_offers":true,"deeplink":"zomato:\/\/restaurant\/18588949","order_url":"https:\/\/www.zomato.com\/ncr\/gabbars-vasant-vihar-new-delhi\/order?utm_source=api_basic_user&utm_medium=api&utm_campaign=v2.1","order_deeplink":"","is_table_reservation_supported":0,"has_table_booking":0,"events_url":"https:\/\/www.zomato.com\/ncr\/gabbars-vasant-vihar-new-delhi\/events#tabtop?utm_source=api_basic_user&utm_medium=api&utm_campaign=v2.1"}}]}
\ No newline at end of file
diff --git a/function-specific-programs/__pycache__/tweepy.cpython-37.pyc b/function-specific-programs/__pycache__/tweepy.cpython-37.pyc
new file mode 100644
index 0000000..a8b2550
Binary files /dev/null and b/function-specific-programs/__pycache__/tweepy.cpython-37.pyc differ
diff --git a/function-specific-programs/drunk.py b/function-specific-programs/drunk.py
new file mode 100644
index 0000000..7e4d94d
--- /dev/null
+++ b/function-specific-programs/drunk.py
@@ -0,0 +1,25 @@
+from uber_rides.session import Session
+from uber_rides.client import UberRidesClient
+
+
+session = Session(server_token=<TOKEN>)
+client = UberRidesClient(session)
+
+
+print("Your Location Appears to be around places which sells \n alcohol, please taka the breathalyser test ")
+
+bac = 0.02
+
+if(bac >= 0.08):
+	print("Please Do Not Drive!\n")
+	print("I can call a cab if you want\n")
+	print("Say No, to disagree, else I'll book the cab")
+	input = yes
+	if(input==no):
+		print("You are not fit to drive")
+		print("Text message to emergency contact sent")
+		break
+	print("Your cab has been booked, thank you for not driving")
+	break
+print("have a safe journey!")
+	
diff --git a/function-specific-programs/ear.py b/function-specific-programs/ear.py
new file mode 100644
index 0000000..a40e065
--- /dev/null
+++ b/function-specific-programs/ear.py
@@ -0,0 +1,117 @@
+# Using Eye aspect ratio
+from scipy.spatial import distance as dist
+from imutils.video import VideoStream
+from imutils import face_utils
+from threading import Thread
+import numpy as np
+import playsound
+import argparse
+import imutils
+import time
+import dlib
+import cv2
+
+def sound_alarm():
+	print('You Sleep You Lose')
+
+def eye_aspect_ratio(eye):
+	# Computes the euclidean distances between the two sets of eyes
+	A = dist.euclidean(eye[1], eye[5])
+	B = dist.euclidean(eye[2], eye[4])
+ 
+	# compute the euclidean distance between the horizontal
+	# eye landmark (x, y)-coordinates
+	C = dist.euclidean(eye[0], eye[3])
+ 
+	# compute the eye aspect ratio
+	ear = (A + B) / (2.0 * C)
+	# return the eye aspect ratio
+	return ear
+
+shape_predictor = "../files/shape_predictor_68_face_landmarks.dat"
+
+
+EYE_AR_THRESH = 0.2 # If the EAR goes < this for 48 frames, it is counted as drowsiness
+EYE_AR_CONSEC_FRAMES = 48
+ 
+COUNTER = 0
+ALERT = False
+
+# initialize dlib's face detector (HOG-based) and then create
+# the facial landmark predictor
+print("Initialising Facial Landmark Predictor...")
+detector = dlib.get_frontal_face_detector()
+predictor = dlib.shape_predictor(shape_predictor)
+
+(lStart, lEnd) = face_utils.FACIAL_LANDMARKS_IDXS["left_eye"]
+(rStart, rEnd) = face_utils.FACIAL_LANDMARKS_IDXS["right_eye"]
+
+print("Starting Video Stream...")
+vs = VideoStream(src=0).start()
+time.sleep(1.0)
+ 
+while True:
+	frame = vs.read()
+	frame = imutils.resize(frame, width=450)
+	gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
+ 
+	rects = detector(gray, 0)
+	for rect in rects:
+		shape = predictor(gray, rect)
+		shape = face_utils.shape_to_np(shape)
+ 
+		# extract the left and right eye coordinates, then use the
+		# coordinates to compute the eye aspect ratio for both eyes
+		leftEye = shape[lStart:lEnd]
+		rightEye = shape[rStart:rEnd]
+		leftEAR = eye_aspect_ratio(leftEye)
+		rightEAR = eye_aspect_ratio(rightEye)
+ 
+		# average the eye aspect ratio together for both eyes
+		ear = (leftEAR + rightEAR) / 2.0
+		# compute the convex hull for the left and right eye, then
+		# visualize each of the eyes
+		leftEyeHull = cv2.convexHull(leftEye)
+		rightEyeHull = cv2.convexHull(rightEye)
+		cv2.drawContours(frame, [leftEyeHull], -1, (0, 255, 0), 1)
+		cv2.drawContours(frame, [rightEyeHull], -1, (0, 255, 0), 1)
+		# check to see if the eye aspect ratio is below the blink
+		# threshold, and if so, increment the blink frame counter
+		if ear < EYE_AR_THRESH:
+			COUNTER += 1
+ 
+			# if the eyes were closed for a sufficient number of
+			# then sound the alarm
+			if COUNTER >= EYE_AR_CONSEC_FRAMES:
+				# if the alarm is not on, turn it on
+				if not ALARM_ON:
+					ALARM_ON = True
+ 
+				# draw an alarm on the frame
+				cv2.putText(frame, "Sleepiness Detected!", (10, 30),
+					cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 0, 255), 2)
+				print("Sleepiness Detected!")
+				print("\a");print("\a");print("\a");print("\a");print("\a")
+				print("\a");print("\a");print("\a");print("\a");print("\a")
+				print("\a");print("\a");print("\a");print("\a");print("\a")
+
+
+ 
+		else:
+			COUNTER = 0
+			ALARM_ON = False
+
+		cv2.putText(frame, "Ratio: {:.2f}".format(ear), (300, 30),
+			cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 0, 255), 2)
+ 
+	# show the frame
+	cv2.imshow("Frame", frame)
+	key = cv2.waitKey(1) & 0xFF
+ 
+	# if the `q` key was pressed, break from the loop
+	if key == ord("q"):
+		break
+ 
+# do a bit of cleanup
+cv2.destroyAllWindows()
+vs.stop()
\ No newline at end of file
diff --git a/function-specific-programs/speedlimit.py b/function-specific-programs/speedlimit.py
new file mode 100644
index 0000000..7a21595
--- /dev/null
+++ b/function-specific-programs/speedlimit.py
@@ -0,0 +1,35 @@
+import overpy
+import sys
+import simplejson as sjson
+import json
+import geocoder 
+
+g = geocoder.ip('me')
+
+def maxspeed(coordinates, radius):
+    lat, lon = coordinates
+    api = overpy.Overpass()
+
+    result = api.query("""
+            way(around:""" + radius + """,""" + lat  + """,""" + lon  + """) ["maxspeed"];
+                (._;>;);
+                    out body;
+                        """)
+    results_list = []
+    for way in result.ways:
+        road = {}
+        road["name"] = way.tags.get("name", "n/a")
+        road["speed_limit"] = way.tags.get("maxspeed", "n/a")
+        nodes = []
+        for node in way.nodes:
+            nodes.append((node.lat, node.lon))
+        road["nodes"] = nodes
+        results_list.append(road)
+    return results_list
+
+
+results = maxspeed((sys.argv[1], sys.argv[2]), sys.argv[3])
+# Alternative
+# results = maxspeed((lat, long, radius))
+speedlimit = sjson.dumps(results[0]['speed_limit']).strip('\"')
+print(speedlimit)
\ No newline at end of file
diff --git a/function-specific-programs/tweet.py b/function-specific-programs/tweet.py
new file mode 100644
index 0000000..e9bfdfb
--- /dev/null
+++ b/function-specific-programs/tweet.py
@@ -0,0 +1,43 @@
+"""
+import tweepy
+
+#twitter application credentials
+consumer_key="knQFpTnjuSvr6OxYwebt3wyrd"
+consumer_secret="Mhex3oRkmaF7lD3hoMvHpAD6ctW0ugKYCopTlhc0JzOLOMIZ0w"
+
+#twitter user credentials
+access_token="2846631344-wEozinvHfEIFxFVy51I6te8SrN5OTFtU00wxsiz"
+access_token_secret="Nfx1U8a2TjAQXFLBrJIyy2p36sjBGAWFIthLc1cIoI56U"
+
+auth = tweepy.OAuthHandler(consumer_key, consumer_secret)
+auth.set_access_token(access_token, access_token_secret)
+
+tweepyapi = tweepy.API(auth)
+
+tweepyapi.update_status('Hello World!')
+print("Hello " + tweepyapi.me().name)
+"""
+
+import tweepy
+
+def get_api(cfg):
+  auth = tweepy.OAuthHandler(cfg['consumer_key'], cfg['consumer_secret'])
+  auth.set_access_token(cfg['access_token'], cfg['access_token_secret'])
+  return tweepy.API(auth)
+
+def main():
+  # Fill in the values noted in previous step here
+  cfg = { 
+    "consumer_key"        : "knQFpTnjuSvr6OxYwebt3wyrd",
+    "consumer_secret"     : "Mhex3oRkmaF7lD3hoMvHpAD6ctW0ugKYCopTlhc0JzOLOMIZ0w",
+    "access_token"        : "2846631344-wEozinvHfEIFxFVy51I6te8SrN5OTFtU00wxsiz",
+    "access_token_secret" : "Nfx1U8a2TjAQXFLBrJIyy2p36sjBGAWFIthLc1cIoI56U" 
+    }
+
+  api = get_api(cfg)
+  tweet = "Hello, world!"
+  status = api.update_status(status=tweet) 
+  # Yes, tweet is called 'status' rather confusing
+
+if __name__ == "__main__":
+  main()
\ No newline at end of file
diff --git a/function-specific-programs/zomato-api.txt b/function-specific-programs/zomato-api.txt
new file mode 100644
index 0000000..802c636
--- /dev/null
+++ b/function-specific-programs/zomato-api.txt
@@ -0,0 +1 @@
+a530c1424d9abe5442fa22f77ce03d25
diff --git a/function-specific-programs/zomato.py b/function-specific-programs/zomato.py
new file mode 100644
index 0000000..26b4c43
--- /dev/null
+++ b/function-specific-programs/zomato.py
@@ -0,0 +1,41 @@
+import requests
+import simplejson as sjson
+import json
+
+res = []
+
+def getRes():
+	headers = {
+	    'Accept': 'application/json',
+	    'user-key': 'a530c1424d9abe5442fa22f77ce03d25',
+	}
+
+	params = (
+	    ('lat', '28.546519'),
+	    ('lon', '77.179248'),
+	)
+
+	response = requests.get('https://developers.zomato.com/api/v2.1/geocode', headers=headers, params=params)
+	res = response.json()['popularity']['nearby_res']
+	return res
+
+def getDetails(res):
+	headers = {
+	    'Accept': 'application/json',
+	    'user-key': 'a530c1424d9abe5442fa22f77ce03d25',
+	}
+	url = "https://developers.zomato.com/api/v2.1/restaurant?res_id=" + str(res[0])
+	newResponse = requests.get(url, headers=headers)
+	newRes = []
+	resName = newResponse.json()['name']
+	resAddress = newResponse.json()['location']['address']
+	print("You are feeling sleepy, why don't you take a break?\n")
+	print("Your nearest eatery is " + resName,"\n")
+	print(resName + " is at " + resAddress,"\n")
+def zomato():
+
+	res = getRes()
+	getDetails(res)
+zomato()
+
+
diff --git a/main.py b/main.py
new file mode 100755
index 0000000..e24980f
--- /dev/null
+++ b/main.py
@@ -0,0 +1,345 @@
+
+import overpy
+import sys
+import simplejson as sjson
+import json
+import time
+from threading import Thread
+from scipy.spatial import distance as dist
+from imutils.video import VideoStream
+from imutils import face_utils
+from threading import Thread
+import numpy as np
+import playsound
+import argparse
+import imutils
+import dlib
+import cv2
+from uber_rides.session import Session
+from uber_rides.client import UberRidesClient
+import signal
+import argparse
+import tweepy
+import requests
+
+#import geocoder
+#import obd
+
+######################
+# Defining Variables #
+######################
+
+radius = str(100) # Radius for maxspeed function. taken as a string because gets concatenated in the function
+
+################
+# Dummy Values #
+################
+
+
+#Latitude
+glat = 28.544565 #28.546519
+#Longitude
+glng = 77.193320 #77.179248
+
+# Commented this as we are not on a road I guess?
+
+#g = geocoder.ip('me')
+#print(g.latlng)
+
+#####################
+#  Real Time Values #
+#####################
+
+#glat = g.lat
+#glng = g.lng
+
+###################
+# Dummy OBD Setup #
+###################
+
+##############################################################
+# What the commands are doing:                               #
+# It setups and asynchronous watch over the speed of the car #
+# this means that the speed's data is constantly updated     #
+# This makes the while loop work                             #
+##############################################################
+
+
+#connection = obd.Async() # auto-connects to USB or RF port
+#connection.watch(obd.commands.SPEED) # select an OBD command (sensor)
+#connections.start()
+#carSpeed = connection.query(obd.commands.SPEED) # send the command, and parse the response
+
+#carSpeed = 30
+
+#####################
+# Tweeting Function #
+#####################
+
+def get_api(cfg):
+    auth = tweepy.OAuthHandler(cfg['consumer_key'], cfg['consumer_secret'])
+    auth.set_access_token(cfg['access_token'], cfg['access_token_secret'])
+    return tweepy.API(auth)
+
+def tweet():
+    cfg = { 
+        "consumer_key"        : "knQFpTnjuSvr6OxYwebt3wyrd",
+        "consumer_secret"     : "Mhex3oRkmaF7lD3hoMvHpAD6ctW0ugKYCopTlhc0JzOLOMIZ0w",
+        "access_token"        : "2846631344-wEozinvHfEIFxFVy51I6te8SrN5OTFtU00wxsiz",
+        "access_token_secret" : "Nfx1U8a2TjAQXFLBrJIyy2p36sjBGAWFIthLc1cIoI56U" 
+        }
+
+    api = get_api(cfg)
+    headers = {
+        'Accept': 'application/json',
+         'user-key': 'a530c1424d9abe5442fa22f77ce03d25',
+                }
+
+    params = (
+        ('lat', '28.546519'),
+        ('lon', '77.179248'),
+    )
+
+    response = requests.get('https://developers.zomato.com/api/v2.1/geocode', headers=headers, params=params)
+    loc = response.json()['location']['title']
+    tweet = ("Stay Alert! Sudden braking at: ", loc  )
+    status = api.update_status(status=tweet) 
+
+################################
+# Fetching Details from Zomato #
+################################
+
+res = []
+
+def getRes():
+    headers = {
+        'Accept': 'application/json',
+        'user-key': 'a530c1424d9abe5442fa22f77ce03d25',
+    }
+
+    params = (
+        ('lat', '28.546519'),
+        ('lon', '77.179248'),
+    )
+
+    response = requests.get('https://developers.zomato.com/api/v2.1/geocode', headers=headers, params=params)
+    res = response.json()['popularity']['nearby_res']
+    return res
+
+def getDetails(res):
+    headers = {
+        'Accept': 'application/json',
+        'user-key': 'a530c1424d9abe5442fa22f77ce03d25',
+    }
+    url = "https://developers.zomato.com/api/v2.1/restaurant?res_id=" + str(res[0])
+    newResponse = requests.get(url, headers=headers)
+    newRes = []
+    resName = newResponse.json()['name']
+    resAddress = newResponse.json()['location']['address']
+    print("You are feeling sleepy, why don't you take a break?\n")
+    print("Your nearest eatery is " + resName,"\n")
+    print(resName + " is at " + resAddress,"\n")
+
+def zomato():
+    res = getRes()
+    getDetails(res)
+
+############################
+# Combatting Drunk Driving #
+############################
+
+def drunk():
+    print("Your Location Appears to be around places which sells \n alcohol, please take the breathalyser test ")
+
+    bac_raw = str(open("./files/bac.txt","r").read())
+    bac = float(float(bac_raw)/100)
+    print(bac)
+    if(bac >= 0.08):
+        print("Please Do Not Drive!\n")
+        print("I can call a cab if you want\n")
+        print("")
+        answer = input("Say No, to disagree, else I'll book the cab: \n")
+        if(answer=="no"):
+            print("You are not fit to drive")
+            print("Text message to emergency contact sent")
+        print("Your cab has been booked, thank you for not driving")
+    print("have a safe journey!")
+    
+
+def sound_alarm():
+    print('You Sleep You Lose')
+
+def eye_aspect_ratio(eye):
+
+    # Computes the euclidean distances between the two sets of eyes
+    A = dist.euclidean(eye[1], eye[5])
+    B = dist.euclidean(eye[2], eye[4])
+    C = dist.euclidean(eye[0], eye[3])
+ 
+    ear = (A + B) / (2.0 * C)
+
+    return ear
+
+shape_predictor = "./files/shape_predictor_68_face_landmarks.dat"
+
+
+EYE_AR_THRESH = 0.2 # If the EAR goes < this for 48 frames, it is counted as drowsiness
+EYE_AR_CONSEC_FRAMES = 24
+ 
+COUNTER = 0
+ALERT = False
+
+
+########################
+# Drowsiness Detection #
+########################
+
+def sleepiness():
+    print("Initialising Facial Landmark Predictor...")
+    detector = dlib.get_frontal_face_detector()
+    predictor = dlib.shape_predictor(shape_predictor)
+
+    (lStart, lEnd) = face_utils.FACIAL_LANDMARKS_IDXS["left_eye"]
+    (rStart, rEnd) = face_utils.FACIAL_LANDMARKS_IDXS["right_eye"]
+
+    print("Starting Video Stream...")
+    vs = VideoStream(src=0).start()
+    time.sleep(1.0)
+    while True:
+        frame = vs.read()
+        frame = imutils.resize(frame, width=450)
+        gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
+     
+        rects = detector(gray, 0)
+        for rect in rects:
+            shape = predictor(gray, rect)
+            shape = face_utils.shape_to_np(shape)
+     
+            leftEye = shape[lStart:lEnd]
+            rightEye = shape[rStart:rEnd]
+            leftEAR = eye_aspect_ratio(leftEye)
+            rightEAR = eye_aspect_ratio(rightEye)
+     
+            ear = (leftEAR + rightEAR) / 2.0
+
+            leftEyeHull = cv2.convexHull(leftEye)
+            rightEyeHull = cv2.convexHull(rightEye)
+            cv2.drawContours(frame, [leftEyeHull], -1, (0, 255, 0), 1)
+            cv2.drawContours(frame, [rightEyeHull], -1, (0, 255, 0), 1)
+
+            if ear < EYE_AR_THRESH:
+                COUNTER += 1
+     
+                # if the eyes were closed for a sufficient number of
+                # then sound the alarm
+                if COUNTER >= EYE_AR_CONSEC_FRAMES:
+                    # if the alarm is not on, turn it on
+                    if not ALARM_ON:
+                        ALARM_ON = True
+     
+                    # draw an alarm on the frame
+                    cv2.putText(frame, "Sleepiness Detected!", (10, 30),
+                        cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 0, 255), 2)
+                    print("Sleepiness Detected!")
+                    print("\a");print("\a");print("\a");print("\a");print("\a")
+                    print("\a");print("\a");print("\a");print("\a");print("\a")
+                    print("\a");print("\a");print("\a");print("\a");print("\a")
+                    zomato()
+                    time.sleep(5)
+                    exit()
+
+
+     
+            else:
+                COUNTER = 0
+                ALARM_ON = False
+
+            cv2.putText(frame, "Ratio: {:.2f}".format(ear), (300, 30),
+                cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 0, 255), 2)
+     
+        cv2.imshow("Frame", frame)
+        key = cv2.waitKey(1) & 0xFF
+     
+        # breaks loop on q
+        if key == ord("q"):
+            break
+     
+    cv2.destroyAllWindows()
+    vs.stop()
+
+##############################
+# Speed Limit Fetch Function #
+##############################
+
+def maxspeed(coordinates, radius):
+
+    lat, lon = coordinates
+    api = overpy.Overpass()
+
+    #######################
+    # Query for Open Maps #
+    ####################### 
+
+    result = api.query("""
+            way(around:""" + radius + """,""" + lat  + """,""" + lon  + """) ["maxspeed"];
+                (._;>;);
+                    out body;
+                        """)
+
+    results_list = []
+    for way in result.ways:
+           road = {}
+           road["name"] = way.tags.get("name", "n/a")
+           road["speed_limit"] = way.tags.get("maxspeed", "n/a")
+           nodes = []
+           for node in way.nodes:
+               nodes.append((node.lat, node.lon))
+           road["nodes"] = nodes
+           results_list.append(road)
+           return results_list
+
+
+
+
+############################################################################################################################
+# Gives data to the function and gets json in return. This json is then parsed. Then the double quotes are stripped off it #
+############################################################################################################################
+def speedlim():
+    speedLimit = sjson.dumps(maxspeed((str(glat), str(glng)), radius)[0]['speed_limit']).strip('\"')
+    while(True):
+        carSpeedDummy = open("./files/carSpeed.txt","r")
+        carSpeed = carSpeedDummy.read()
+        #print(carSpeed)
+        #carSpeed = 29
+        while(int(carSpeed) > int(speedLimit)):
+            carSpeedDummy = open("./files/carSpeed.txt","r")
+            carSpeed = carSpeedDummy.read()
+            print("Over The Speed Limit")
+            time.sleep(5)
+        while(int(carSpeed) <= int(speedLimit)):
+            carSpeedDummy = open("./files/carSpeed.txt","r")
+            carSpeed = carSpeedDummy.read()
+            print("Under the Speed Limit")
+            time.sleep(5)
+
+##################
+# Sudden Braking #
+##################
+
+def brakes():
+    while(True):
+        tweet()
+
+#####################################################
+# Using Argument Parse to run one command at a time #
+#####################################################
+
+parser = argparse.ArgumentParser()
+FUNCTION_MAP = {'overspeed' : speedlim,
+                'sleep-detector' : sleepiness,
+                'sudden-braking' : brakes,
+                'drunk' : drunk }
+parser.add_argument('function', choices=FUNCTION_MAP.keys())
+args = parser.parse_args()
+func = FUNCTION_MAP[args.function]
+func()
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