I hope this fucking works

master_app/nbactions.xml

@@ -10,9 +10,9 @@
                 <goal>org.codehaus.mojo:exec-maven-plugin:1.5.0:exec</goal>
             </goals>
             <properties>
-                <exec.args>-classpath %classpath ${packageClassName} ips.json</exec.args>
+                <exec.args>-classpath %classpath me.yigitcolakoglu.master_app.Main ips.json</exec.args>
                 <exec.executable>java</exec.executable>
-                <exec.workingdir>/home/efeaydin/Masaüstü/MyCity/master_app/src/main/java/me/yigitcolakoglu/master_app</exec.workingdir>
+                <exec.workingdir>/home/tedankara/Downloads/MyCity/master_app/src/main/java/me/yigitcolakoglu/master_app</exec.workingdir>
             </properties>
         </action>
         <action>
@@ -28,7 +28,7 @@
                 <exec.args>-agentlib:jdwp=transport=dt_socket,server=n,address=${jpda.address} -classpath %classpath ${packageClassName} ips.json</exec.args>
                 <exec.executable>java</exec.executable>
                 <jpda.listen>true</jpda.listen>
-                <exec.workingdir>/home/efeaydin/Masaüstü/MyCity/master_app/src/main/java/me/yigitcolakoglu/master_app</exec.workingdir>
+                <exec.workingdir>/home/tedankara/Downloads/MyCity/master_app/src/main/java/me/yigitcolakoglu/master_app</exec.workingdir>
             </properties>
         </action>
         <action>
@@ -43,7 +43,7 @@
             <properties>
                 <exec.args>-classpath %classpath ${packageClassName} ips.json</exec.args>
                 <exec.executable>java</exec.executable>
-                <exec.workingdir>/home/efeaydin/Masaüstü/MyCity/master_app/src/main/java/me/yigitcolakoglu/master_app</exec.workingdir>
+                <exec.workingdir>/home/tedankara/Downloads/MyCity/master_app/src/main/java/me/yigitcolakoglu/master_app</exec.workingdir>
             </properties>
         </action>
     </actions>

master_app/pom.xml

@@ -16,6 +16,11 @@
             <artifactId>sshj</artifactId>
             <version>0.27.0</version>
         </dependency>
+        <dependency>
+            <groupId>commons-io</groupId>
+            <artifactId>commons-io</artifactId>
+            <version>2.6</version>
+        </dependency>
     </dependencies>
     <properties>
         <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>

master_app/target/maven-status/maven-compiler-plugin/compile/default-compile/inputFiles.lst

@@ -1,3 +1,3 @@
-/home/yigit/projects/MyCity/master_app/src/main/java/me/yigitcolakoglu/master_app/Main.java
-/home/yigit/projects/MyCity/master_app/src/main/java/me/yigitcolakoglu/master_app/managementForm.java
-/home/yigit/projects/MyCity/master_app/src/main/java/me/yigitcolakoglu/master_app/cameraForm.java
+/home/efeaydin/Masaüstü/MyCity/master_app/src/main/java/me/yigitcolakoglu/master_app/managementForm.java
+/home/efeaydin/Masaüstü/MyCity/master_app/src/main/java/me/yigitcolakoglu/master_app/cameraForm.java
+/home/efeaydin/Masaüstü/MyCity/master_app/src/main/java/me/yigitcolakoglu/master_app/Main.java

server_side/.idea/codeStyles/codeStyleConfig.xml

@@ -0,0 +1,5 @@
+<component name="ProjectCodeStyleConfiguration">
+  <state>
+    <option name="PREFERRED_PROJECT_CODE_STYLE" value="Default" />
+  </state>
+</component>

server_side/.idea/encodings.xml

@@ -0,0 +1,4 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="Encoding" addBOMForNewFiles="with NO BOM" />
+</project>

server_side/.idea/misc.xml

@@ -0,0 +1,6 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="ProjectRootManager" version="2" languageLevel="JDK_10" project-jdk-name="10" project-jdk-type="JavaSDK">
+    <output url="file://$PROJECT_DIR$/classes" />
+  </component>
+</project>

server_side/.idea/modules.xml

@@ -0,0 +1,9 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="ProjectModuleManager">
+    <modules>
+      <module fileurl="file://$PROJECT_DIR$/server_side.iml" filepath="$PROJECT_DIR$/server_side.iml" />
+      <module fileurl="file://$PROJECT_DIR$/.idea/modules/smartcity/server_side.smartcity.iml" filepath="$PROJECT_DIR$/.idea/modules/smartcity/server_side.smartcity.iml" />
+    </modules>
+  </component>
+</project>

server_side/.idea/vcs.xml

@@ -0,0 +1,6 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="VcsDirectoryMappings">
+    <mapping directory="$PROJECT_DIR$/.." vcs="Git" />
+  </component>
+</project>

server_side/api/ai_services.py

@@ -9,9 +9,10 @@ from PIL import Image
 import base64
 import io
 import json
+import re
 
 import tensorflow as tf
-import sys
+import sys,getpass
 import numpy as np
 from flask import Flask, send_from_directory
 from flask_restful import Api
@@ -30,7 +31,7 @@ PATH_TO_FROZEN_DAMAGE_GRAPH =  'modules/trainedModels/ssd_mobilenet_RoadDamageDe
 linux_def = {"detection_boxes":[(106, 188, 480, 452)],"detection_scores":[0.99],"detection_classes":[1]}
 detection_graph_coco = None
 detection_graph_damage = None
-if sys.platform == "win32":
+if getpass.getuser() == "tedankara":
     detection_graph_coco = tf.Graph()
     detection_graph_damage = tf.Graph()
     with detection_graph_coco.as_default():
@@ -51,11 +52,24 @@ def load_image_into_numpy_array(image):
     return np.array(image.getdata()).reshape(
             (im_height, im_width, 3)).astype(np.uint8)
 
+def decode_base64(data, altchars=b'+/'):
+    """Decode base64, padding being optional.
+
+    :param data: Base64 data as an ASCII byte string
+    :returns: The decoded byte string.
+
+    """
+    data = re.sub(rb'[^a-zA-Z0-9%s]+' % altchars, b'', bytes(data,"utf-8"))  # normalize
+    missing_padding = len(data) % 4
+    if missing_padding:
+        data += b'='* (4 - missing_padding)
+    return base64.b64decode(data, altchars)
+
 def run_inference_for_single_image(image, graph,type):
     global switches
     global sess_coco
     global sess_damage
-    if not sys.platform == "win32":
+    if not getpass.getuser() == "tedankara":
         return linux_def
     with graph.as_default():
         if(switches[type]):
@@ -117,7 +131,7 @@ def run_inference_for_single_image(image, graph,type):
                     [detection_boxes, detection_scores, detection_classes, num_detections],
                     feed_dict={image_tensor: image})
 
-            output_dict = {'detection_classes': np.squeeze(classes).astype(np.int32), 'detection_scores': np.squeeze(scores)}
+            output_dict = {'detection_classes': np.squeeze(classes).astype(np.int32), 'detection_scores': np.squeeze(scores),'detection_boxes': np.squeeze(boxes)}
 
     return output_dict
 
@@ -125,7 +139,8 @@ def run_inference_for_single_image(image, graph,type):
 class Process(Resource):
     def post(self):
         base64_img = request.form['img']
-        image = Image.open(io.BytesIO(base64.b64decode(base64_img)))
+        image = Image.open(io.BytesIO(decode_base64(base64_img)))
+
         type = request.form["type"]
         image_np = load_image_into_numpy_array(image)
         image_np_expanded = np.expand_dims(image_np, axis=0)
@@ -133,9 +148,12 @@ class Process(Resource):
             output_dict = run_inference_for_single_image(image_np_expanded, detection_graph_coco,type)
         elif type == "damage":
             output_dict = run_inference_for_single_image(image_np_expanded, detection_graph_damage,type)
+        if getpass.getuser() == "tedankara":
+        	output_dict["detection_boxes"] = output_dict["detection_boxes"].tolist()
+        	output_dict["detection_scores"] = output_dict["detection_scores"].tolist()
+        	output_dict["detection_classes"] = output_dict["detection_classes"].tolist()
 
-
-        return json.dumps(output_dict,cls=NumpyEncoder)
+        return output_dict
 
 
 class NumpyEncoder(json.JSONEncoder):

server_side/api/app.py

@@ -2,9 +2,8 @@ from flask import Flask, send_from_directory
 from flask_restful import Api
 from flask_cors import CORS, cross_origin
 
-from modules import user_info, voting_system, rating_system, denunciation, navigation, bus_stops, announcements, complaint, car_crash,smart_park
+from modules import user_info, voting_system, rating_system, denunciation,  announcements, complaint, car_crash, smart_park,navigation,bus_stops
 from modules import utility
-from modules import user_set
 
 app = Flask(__name__)
 api = Api(app)

server_side/api/modules/SpotSelector.py

@@ -4,9 +4,9 @@ import json
 
 rects = []
 
-cam = cv2.VideoCapture(2)
+cam = cv2.VideoCapture(5)
 ret,im = cam.read()
-cam.release()
+#im = cv2.imread("lot.jpg")
 if __name__ == '__main__' :
 
 	while(True):

server_side/api/modules/car_crash.py

@@ -8,7 +8,7 @@ import cv2
 
 import base64
 import json
-import sys
+import sys,getpass
 import os
 import io
 import itertools
@@ -28,7 +28,7 @@ import numpy as np
 
 MIN_SCORE_THRESH = 0.6
 
-if sys.platform == "win32":
+if getpass.getuser() == "tedankara":
     sys.path.insert(0, r'C:\Users\Tednokent01\Downloads\MyCity\traffic_analyzer')
 
 PATH_TO_LABELS = os.path.join('object_detection/data', 'mscoco_label_map.pbtxt')
@@ -75,10 +75,10 @@ def find_name(image):
         return None
 
 def rotate_img(img, angle):
-	if angle == 90:
-		return np.rot90(img)
-	elif angle == 270:
-		return np.rot90(np.rot90(np.rot90(img)))
+    if angle == 90:
+        return np.rot90(img)
+    elif angle == 270:
+        return np.rot90(np.rot90(np.rot90(img)))
 
 def process_img(img_base64):
     url = 'https://{}:5001/ai'.format(AI_IP) # Set destination URL here
@@ -150,23 +150,23 @@ def process_img(img_base64):
                         pass
                     (height_person,width_person) = person.shape[:2]
 
-					if name is None:
-						rotated = rotate_img(person, 270)
-						face_locs = face_recognition.face_locations(rotated)[0]
-						name = find_name(rotated)
-						(top_face, right_face, bottom_face, left_face) = face_locs
-						face_locs_processed = (top + height_person - right_face,left+bottom_face,top + height_person - left_face,left+top_face)
-					else:
-						(top_face, right_face, bottom_face, left_face) = face_locs
-						person = cv2.rectangle(person, (width_person - bottom_face, left_face), (width_person - top_face, right_face), (0, 255, 0), 3)
-						face_locs_processed = (top + left_face,left + width_person - top_face,top + right_face,left + width_person - bottom_face)
-					people[index] = [0, face_locs_processed, name]
-				else:
-					face_locs = face_recognition.face_locations(person)[0]
-					(top_face, right_face, bottom_face, left_face) = face_locs
-					face_locs_processed = (top+face_locs[0],left+face_locs[1],top+face_locs[2],left+face_locs[3])
-					name = find_name(person)
-					people[index] = [1, face_locs_processed, name]
+                    if name is None:
+                        rotated = rotate_img(person, 270)
+                        face_locs = face_recognition.face_locations(rotated)[0]
+                        name = find_name(rotated)
+                        (top_face, right_face, bottom_face, left_face) = face_locs
+                        face_locs_processed = (top + height_person - right_face,left+bottom_face,top + height_person - left_face,left+top_face)
+                    else:
+                        (top_face, right_face, bottom_face, left_face) = face_locs
+                        person = cv2.rectangle(person, (width_person - bottom_face, left_face), (width_person - top_face, right_face), (0, 255, 0), 3)
+                        face_locs_processed = (top + left_face,left + width_person - top_face,top + right_face,left + width_person - bottom_face)
+                    people[index] = [0, face_locs_processed, name]
+                else:
+                    face_locs = face_recognition.face_locations(person)[0]
+                    (top_face, right_face, bottom_face, left_face) = face_locs
+                    face_locs_processed = (top+face_locs[0],left+face_locs[1],top+face_locs[2],left+face_locs[3])
+                    name = find_name(person)
+                    people[index] = [1, face_locs_processed, name]
 
 
 
@@ -188,21 +188,21 @@ class Crash(Resource):
         id = request.form['id']
         lat, long = request.form['lat'], request.form['long']
 
-		image, car_count, injured,out,people = process_img(base64_img)
-		(top, right, bottom, left) = people[0][1]	 
-		top = int(top)
-		right = int(right)
-		left = int(left)
-		bottom = int(bottom)
-		img = load_image_into_numpy_array(Image.open(io.BytesIO(base64.b64decode(base64_img))))
-		cv2.rectangle(img,(left,top),(right,bottom),(0,255,0),3)
-		cv2.imshow('test.jpg', img)
-		cv2.waitKey(0)
-		cv2.destroyAllWindows()
-		print(people)
-		priority = car_count + injured
-		if priority > 10:
-			priority = 10
+        image, car_count, injured,out,people = process_img(base64_img)
+        (top, right, bottom, left) = people[0][1]     
+        top = int(top)
+        right = int(right)
+        left = int(left)
+        bottom = int(bottom)
+        img = load_image_into_numpy_array(Image.open(io.BytesIO(base64.b64decode(base64_img))))
+        cv2.rectangle(img,(left,top),(right,bottom),(0,255,0),3)
+        cv2.imshow('test.jpg', img)
+        cv2.waitKey(0)
+        cv2.destroyAllWindows()
+        print(people)
+        priority = car_count + injured
+        if priority > 10:
+            priority = 10
 
         crash = {
             'img': image,

server_side/api/modules/complaint.py

@@ -5,7 +5,7 @@ import json
 import io
 import base64
 from PIL import Image
-import sys
+import sys,getpass
 import datetime
 import cv2
 import ssl
@@ -13,7 +13,7 @@ from urllib.parse import urlencode
 from urllib.request import Request, urlopen
 
 
-if sys.platform == "win32":
+if getpass.getuser() == "tedankara":
 	import tensorflow as tf
 	import numpy as np
 	import pickle
@@ -42,7 +42,7 @@ score_dict = {
 with open("modules/databases/complaints.json","r") as f:
 	complaints = json.load(f)
 
-if sys.platform == "win32":
+if getpass.getuser() == "tedankara":
 	# Path to frozen detection graph. This is the actual model that is used for the object detection.
 
 	# List of the strings that is used to add correct label for each box.
@@ -60,15 +60,15 @@ def load_image_into_numpy_array(image):
 
 def process_img(img_base64):
 
-	if sys.platform == "win32":
+	if getpass.getuser() == "tedankara":
 
-		url = 'https://127.0.0.1:5000/ai' # Set destination URL here
+		url = 'https://127.0.0.1:5001/ai' # Set destination URL here
 		post_fields = {'img': img_base64,"type":"damage"}     # Set POST fields here
 
 		request = Request(url, urlencode(post_fields).encode())
 		img = load_image_into_numpy_array(Image.open(io.BytesIO(base64.b64decode(img_base64))))
 
-		output_dict = json.loads(json.loads(urlopen(request, context=context).read()))
+		output_dict = json.loads(urlopen(request, context=context).read())
 		print(output_dict)
 		vis_util.visualize_boxes_and_labels_on_image_array(
 				img,

server_side/api/modules/databases/locations.json

@@ -1,23 +1,23 @@
 {
   "0": {
-    "x1": 2,
-    "y1": 94,
-    "x2": 198,
-    "y2": 206,
+    "x1": 40,
+    "y1": 64,
+    "x2": 258,
+    "y2": 204,
     "priority": 0
   },
   "1": {
-    "x1": 190,
-    "y1": 88,
-    "x2": 400,
-    "y2": 196,
+    "x1": 262,
+    "y1": 96,
+    "x2": 386,
+    "y2": 206,
     "priority": 1
   },
   "2": {
-    "x1": 390,
-    "y1": 66,
-    "x2": 640,
-    "y2": 200,
+    "x1": 426,
+    "y1": 100,
+    "x2": 564,
+    "y2": 204,
     "priority": 2
   }
 }

server_side/api/modules/smart_park.py

@@ -93,7 +93,7 @@ def generateData(locs, img, avgs,show):
 
 		if spot in show:
 			plt.imshow(vals[spot], interpolation='nearest')
-			plt.show()
+			#plt.show()
 
 	return distances
 
@@ -102,15 +102,13 @@ def im2str(im):
 	imdata = pickle.dumps(im)
 	return base64.b64encode(imdata).decode('ascii')
 
-cam = cv2.VideoCapture(2)
-
 plt.axis("off")
 with open("modules/databases/locations.json","r") as f:
 	locs = json.loads(f.read())
 
 with open("modules/databases/park_data.json","r") as f:
 	data = json.loads(f.read())
-
+cam=cv2.VideoCapture(5)
 if 0:
 	ret,im = cam.read()
 	data = generateAvg(locs,im,data)
@@ -120,9 +118,7 @@ if 0:
 
 class Empty(Resource):
 	def get(self):
-
-		ret,image = cam.read()
-		#image = cv2.imread("module	s/lot.jpg")
+		image = cv2.imread("modules/lot.jpg")
 		backup = image.copy()
 		spot_data = generateData(locs,image,data,["0","1","2"])
 		print(spot_data)
@@ -140,6 +136,7 @@ class Empty(Resource):
 		print(spot_data)
 		if best_spot == -1:
 			print("Sorry, no spot found :(")
+			return
 		else:
 			print("Empty spot found at {}".format(int(best_spot) + 1))
 		foo = locs[best_spot]

server_side/api/modules/smart_park.py.save

@@ -0,0 +1,162 @@
+import cv2
+import numpy as np
+import json
+from pysolar.solar import *
+from datetime import datetime
+from flask import Flask, request
+from flask_restful import Resource, Api, abort
+import base64
+import pickle
+from PIL import Image
+from matplotlib import pyplot as plt
+from io import BytesIO
+
+app = Flask(__name__)
+api = Api(app)
+
+def generateAvg(locs, img, avgs):
+	time = datetime.strptime( "2019-04-27 17:52:00 -0300","%Y-%m-%d %H:%M:%S %z")
+	altitude = int(get_altitude(39.9127938,32.8073577,time))
+
+	loc_images = {}
+
+	for i in locs:
+		temp = locs[i]
+		crop_img = img[temp["y1"]:temp["y2"], temp["x1"]:temp["x2"]]
+		loc_images[i]=[crop_img]
+
+
+
+	vals = {}
+	if str(altitude) in avgs:
+		vals = avgs[str(altitude)]
+	else:
+		for spot in loc_images:
+			vals[spot] = loc_images[spot]
+
+	for spot in loc_images:
+		for col in range(len(vals[spot][0])):
+			for pix in range(len(vals[spot][0][col])):
+
+				vals[spot][0][col][pix] = [
+					np.uint8((int(vals[spot][0][col][pix][0]) + int(loc_images[spot][0][col][pix][0]))/2),
+					np.uint8((int(vals[spot][0][col][pix][1]) + int(loc_images[spot][0][col][pix][1]))/2),
+					np.uint8((int(vals[spot][0][col][pix][2]) + int(loc_images[spot][0][col][pix][2]))/2)]
+
+
+	for i in vals:
+		vals[i] = vals[i][0].tolist()
+
+	avgs[altitude] = vals
+
+	return avgs
+
+def generateData(locs, img, avgs,show):
+
+	time = datetime.strptime( "2019-04-27 17:52:00 -0300","%Y-%m-%d %H:%M:%S %z")
+	altitude = int(get_altitude(39.9127938,32.8073577,time))
+
+	loc_images = {}
+	distances = {}
+
+	for i in locs:
+		temp = locs[i]
+		crop_img = img[temp["y1"]:temp["y2"], temp["x1"]:temp["x2"]]
+		loc_images[i]=[crop_img]
+
+	vals = {}
+
+	if str(altitude) in avgs:
+
+		for spot in avgs[str(altitude)]:
+			vals[spot] = np.array(avgs[str(altitude)][spot])
+	else:
+
+		for spot in loc_images:
+			vals[spot] = loc_images[spot]
+
+	for spot in loc_images:
+		foo = np.zeros((len(vals[spot]),len(vals[spot][0])),dtype=int)
+		distances[spot] = 0
+		for col in range(len(vals[spot])):
+			for pix in range(len(vals[spot][col])):
+				vals[spot][col][pix] = [
+					np.uint8(abs(int(vals[spot][col][pix][0]) - int(loc_images[spot][0][col][pix][0]))),
+					np.uint8(abs(int(vals[spot][col][pix][1]) - int(loc_images[spot][0][col][pix][1]))),
+					np.uint8(abs(int(vals[spot][col][pix][2]) - int(loc_images[spot][0][col][pix][2])))]
+
+				distances[spot] += np.sum(vals[spot][col][pix])
+
+				foo[col][pix] = np.max(vals[spot][col][pix])
+		distances[spot] = int(distances[spot]/vals[spot].size)
+		vals[spot] = foo
+
+		if spot in show:
+			plt.imshow(vals[spot], interpolation='nearest')
+			#plt.show()
+
+	return distances
+
+
+def im2str(im):
+	imdata = pickle.dumps(im)
+	return base64.b64encode(imdata).decode('ascii')
+
+plt.axis("off")
+with open("modules/databases/locations.json","r") as f:
+	locs = json.loads(f.read())
+
+with open("modules/databases/park_data.json","r") as f:
+	data = json.loads(f.read())
+cam = cv2.VideoCapture(5)
+if 1:
+	ret,im = cam.read()
+	data = generateAvg(locs,im,data)
+
+	with open("modules/databases/park_data.json","w") as f:
+		f.write(json.dumps(data,indent=2))
+
+class Empty(Resource):
+	def get(self):
+		image = cv2.imread("modules/lot.jpg")
+		backup = image.copy()
+		spot_data = generateData(locs,image,data,["0","1","2"])
+		print(spot_data)
+		best_spot = -1
+		for loc in spot_data:
+			spot_data[loc] = spot_data[loc] < 30
+			color = (0,255*spot_data[loc],255*(not spot_data[loc]))
+			cv2.rectangle(image,(locs[loc]["x1"],locs[loc]["y1"]),(locs[loc]["x2"],locs[loc]["y2"]),color,5)
+			if spot_data[loc]:
+				if best_spot == -1:
+					best_spot = loc
+					continue
+				if locs[loc]["priority"] < locs[best_spot]["priority"]:
+					best_spot = loc
+		print(spot_data)
+		if best_spot == -1:
+			print("Sorry, no spot found :(")
+			return
+		else:
+			print("Empty spot found at {}".format(int(best_spot) + 1))
+		foo = locs[best_spot]
+		crop_img = backup[foo["y1"]:foo["y2"], foo["x1"]:foo["x2"]].copy(order='C')
+
+		crop_img = Image.fromarray(crop_img,"RGB")
+		buffered = BytesIO()
+		crop_img.save(buffered, format="JPEG")
+		img = base64.b64encode(buffered.getvalue()).decode("ascii")
+
+		return {"lat":foo["lat"], "lng":foo["lng"], "img":img}
+
+
+
+
+
+
+
+
+
+
+
+

server_side/api/modules/user_set.py

@@ -1,26 +1,24 @@
 import os
-import sys
+import sys,getpass
 import json
 import base64
 import face_recognition
 
-from modules import utils
+import utils
 
-with open('modules/databases/users.json') as f:
+with open('databases/users.json') as f:
 	users = json.load(f)
 
-for file in os.listdir("images"):
+for file in os.listdir("../images"):
 	if file.endswith(".png") or file.endswith(".jpg"):
 		uid = file.split('.')[0]
 		if len(uid) == 32 and utils.find_by_id(users.values(), uid):
-			full_path = os.path.join("images", file)
+			full_path = os.path.join("../images", file)
 			image = face_recognition.load_image_file(full_path)
 			with open(full_path, 'rb') as f:
 				base64_image = base64.b64encode(f.read())
 
-			if sys.platform == "win32":
-				face_locations = face_recognition.face_locations(image, model="cnn")[0]
-			else:
+			if getpass.getuser() == "tedankara":
 				face_locations = face_recognition.face_locations(image)[0]
 
 			face_encoding = face_recognition.face_encodings(image)[0]
@@ -30,7 +28,7 @@ for file in os.listdir("images"):
 					users[k]['face_locations'] = face_locations
 					users[k]['face_encoding'] = list(face_encoding)
 
-			with open('modules/databases/users.json', 'w') as f:
+			with open('databases/users.json', 'w') as f:
 				users = json.dump(users, f, indent=2)
 
-			os.remove(full_path)
+			os.remove(full_path)

server_side/api/object_detection/core/preprocessor.py

@@ -65,7 +65,7 @@ back to rank 4.
 
 import functools
 import inspect
-import sys
+import sys,getpass
 import tensorflow as tf
 
 from tensorflow.python.ops import control_flow_ops

server_side/api/object_detection/object_detection_tutorial.ipynb

@@ -39,7 +39,7 @@
         "import numpy as np\n",
         "import os\n",
         "import six.moves.urllib as urllib\n",
-        "import sys\n",
+        "import sys,getpass\n",
         "import tarfile\n",
         "import tensorflow as tf\n",
         "import zipfile\n",

server_side/api/object_detection/protos/anchor_generator_pb2.py

@@ -1,7 +1,7 @@
 # Generated by the protocol buffer compiler.  DO NOT EDIT!
 # source: object_detection/protos/anchor_generator.proto
 
-import sys
+import sys,getpass
 _b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1'))
 from google.protobuf import descriptor as _descriptor
 from google.protobuf import message as _message

server_side/api/object_detection/protos/argmax_matcher_pb2.py

@@ -1,7 +1,7 @@
 # Generated by the protocol buffer compiler.  DO NOT EDIT!
 # source: object_detection/protos/argmax_matcher.proto
 
-import sys
+import sys,getpass
 _b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1'))
 from google.protobuf import descriptor as _descriptor
 from google.protobuf import message as _message

server_side/api/object_detection/protos/bipartite_matcher_pb2.py

@@ -1,7 +1,7 @@
 # Generated by the protocol buffer compiler.  DO NOT EDIT!
 # source: object_detection/protos/bipartite_matcher.proto
 
-import sys
+import sys,getpass
 _b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1'))
 from google.protobuf import descriptor as _descriptor
 from google.protobuf import message as _message

server_side/api/object_detection/protos/box_coder_pb2.py

@@ -1,7 +1,7 @@
 # Generated by the protocol buffer compiler.  DO NOT EDIT!
 # source: object_detection/protos/box_coder.proto
 
-import sys
+import sys,getpass
 _b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1'))
 from google.protobuf import descriptor as _descriptor
 from google.protobuf import message as _message

server_side/api/object_detection/protos/box_predictor_pb2.py

@@ -1,7 +1,7 @@
 # Generated by the protocol buffer compiler.  DO NOT EDIT!
 # source: object_detection/protos/box_predictor.proto
 
-import sys
+import sys,getpass
 _b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1'))
 from google.protobuf import descriptor as _descriptor
 from google.protobuf import message as _message

server_side/api/object_detection/protos/calibration_pb2.py

@@ -1,7 +1,7 @@
 # Generated by the protocol buffer compiler.  DO NOT EDIT!
 # source: object_detection/protos/calibration.proto
 
-import sys
+import sys,getpass
 _b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1'))
 from google.protobuf import descriptor as _descriptor
 from google.protobuf import message as _message

server_side/api/object_detection/protos/eval_pb2.py

@@ -1,7 +1,7 @@
 # Generated by the protocol buffer compiler.  DO NOT EDIT!
 # source: object_detection/protos/eval.proto
 
-import sys
+import sys,getpass
 _b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1'))
 from google.protobuf import descriptor as _descriptor
 from google.protobuf import message as _message

server_side/api/object_detection/protos/faster_rcnn_box_coder_pb2.py

@@ -1,7 +1,7 @@
 # Generated by the protocol buffer compiler.  DO NOT EDIT!
 # source: object_detection/protos/faster_rcnn_box_coder.proto
 
-import sys
+import sys,getpass
 _b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1'))
 from google.protobuf import descriptor as _descriptor
 from google.protobuf import message as _message

server_side/api/object_detection/protos/faster_rcnn_pb2.py

@@ -1,7 +1,7 @@
 # Generated by the protocol buffer compiler.  DO NOT EDIT!
 # source: object_detection/protos/faster_rcnn.proto
 
-import sys
+import sys,getpass
 _b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1'))
 from google.protobuf import descriptor as _descriptor
 from google.protobuf import message as _message

server_side/api/object_detection/protos/flexible_grid_anchor_generator_pb2.py

@@ -1,7 +1,7 @@
 # Generated by the protocol buffer compiler.  DO NOT EDIT!
 # source: object_detection/protos/flexible_grid_anchor_generator.proto
 
-import sys
+import sys,getpass
 _b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1'))
 from google.protobuf import descriptor as _descriptor
 from google.protobuf import message as _message

server_side/api/object_detection/protos/graph_rewriter_pb2.py

@@ -1,7 +1,7 @@
 # Generated by the protocol buffer compiler.  DO NOT EDIT!
 # source: object_detection/protos/graph_rewriter.proto
 
-import sys
+import sys,getpass
 _b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1'))
 from google.protobuf import descriptor as _descriptor
 from google.protobuf import message as _message

server_side/api/object_detection/protos/grid_anchor_generator_pb2.py

@@ -1,7 +1,7 @@
 # Generated by the protocol buffer compiler.  DO NOT EDIT!
 # source: object_detection/protos/grid_anchor_generator.proto
 
-import sys
+import sys,getpass
 _b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1'))
 from google.protobuf import descriptor as _descriptor
 from google.protobuf import message as _message

server_side/api/object_detection/protos/hyperparams_pb2.py

@@ -1,7 +1,7 @@
 # Generated by the protocol buffer compiler.  DO NOT EDIT!
 # source: object_detection/protos/hyperparams.proto
 
-import sys
+import sys,getpass
 _b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1'))
 from google.protobuf import descriptor as _descriptor
 from google.protobuf import message as _message

server_side/api/object_detection/protos/image_resizer_pb2.py

@@ -1,7 +1,7 @@
 # Generated by the protocol buffer compiler.  DO NOT EDIT!
 # source: object_detection/protos/image_resizer.proto
 
-import sys
+import sys,getpass
 _b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1'))
 from google.protobuf.internal import enum_type_wrapper
 from google.protobuf import descriptor as _descriptor

server_side/api/object_detection/protos/input_reader_pb2.py

@@ -1,7 +1,7 @@
 # Generated by the protocol buffer compiler.  DO NOT EDIT!
 # source: object_detection/protos/input_reader.proto
 
-import sys
+import sys,getpass
 _b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1'))
 from google.protobuf.internal import enum_type_wrapper
 from google.protobuf import descriptor as _descriptor

server_side/api/object_detection/protos/keypoint_box_coder_pb2.py

@@ -1,7 +1,7 @@
 # Generated by the protocol buffer compiler.  DO NOT EDIT!
 # source: object_detection/protos/keypoint_box_coder.proto
 
-import sys
+import sys,getpass
 _b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1'))
 from google.protobuf import descriptor as _descriptor
 from google.protobuf import message as _message

server_side/api/object_detection/protos/losses_pb2.py

@@ -1,7 +1,7 @@
 # Generated by the protocol buffer compiler.  DO NOT EDIT!
 # source: object_detection/protos/losses.proto
 
-import sys
+import sys,getpass
 _b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1'))
 from google.protobuf import descriptor as _descriptor
 from google.protobuf import message as _message

server_side/api/object_detection/protos/matcher_pb2.py

@@ -1,7 +1,7 @@
 # Generated by the protocol buffer compiler.  DO NOT EDIT!
 # source: object_detection/protos/matcher.proto
 
-import sys
+import sys,getpass
 _b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1'))
 from google.protobuf import descriptor as _descriptor
 from google.protobuf import message as _message

server_side/api/object_detection/protos/mean_stddev_box_coder_pb2.py

@@ -1,7 +1,7 @@
 # Generated by the protocol buffer compiler.  DO NOT EDIT!
 # source: object_detection/protos/mean_stddev_box_coder.proto
 
-import sys
+import sys,getpass
 _b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1'))
 from google.protobuf import descriptor as _descriptor
 from google.protobuf import message as _message

server_side/api/object_detection/protos/model_pb2.py

@@ -1,7 +1,7 @@
 # Generated by the protocol buffer compiler.  DO NOT EDIT!
 # source: object_detection/protos/model.proto
 
-import sys
+import sys,getpass
 _b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1'))
 from google.protobuf import descriptor as _descriptor
 from google.protobuf import message as _message

server_side/api/object_detection/protos/multiscale_anchor_generator_pb2.py

@@ -1,7 +1,7 @@
 # Generated by the protocol buffer compiler.  DO NOT EDIT!
 # source: object_detection/protos/multiscale_anchor_generator.proto
 
-import sys
+import sys,getpass
 _b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1'))
 from google.protobuf import descriptor as _descriptor
 from google.protobuf import message as _message

server_side/api/object_detection/protos/optimizer_pb2.py

@@ -1,7 +1,7 @@
 # Generated by the protocol buffer compiler.  DO NOT EDIT!
 # source: object_detection/protos/optimizer.proto
 
-import sys
+import sys,getpass
 _b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1'))
 from google.protobuf import descriptor as _descriptor
 from google.protobuf import message as _message

server_side/api/object_detection/protos/pipeline_pb2.py

@@ -1,7 +1,7 @@
 # Generated by the protocol buffer compiler.  DO NOT EDIT!
 # source: object_detection/protos/pipeline.proto
 
-import sys
+import sys,getpass
 _b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1'))
 from google.protobuf import descriptor as _descriptor
 from google.protobuf import message as _message

server_side/api/object_detection/protos/post_processing_pb2.py

@@ -1,7 +1,7 @@
 # Generated by the protocol buffer compiler.  DO NOT EDIT!
 # source: object_detection/protos/post_processing.proto
 
-import sys
+import sys,getpass
 _b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1'))
 from google.protobuf import descriptor as _descriptor
 from google.protobuf import message as _message

server_side/api/object_detection/protos/preprocessor_pb2.py

@@ -1,7 +1,7 @@
 # Generated by the protocol buffer compiler.  DO NOT EDIT!
 # source: object_detection/protos/preprocessor.proto
 
-import sys
+import sys,getpass
 _b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1'))
 from google.protobuf import descriptor as _descriptor
 from google.protobuf import message as _message

server_side/api/object_detection/protos/region_similarity_calculator_pb2.py

@@ -1,7 +1,7 @@
 # Generated by the protocol buffer compiler.  DO NOT EDIT!
 # source: object_detection/protos/region_similarity_calculator.proto
 
-import sys
+import sys,getpass
 _b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1'))
 from google.protobuf import descriptor as _descriptor
 from google.protobuf import message as _message

server_side/api/object_detection/protos/square_box_coder_pb2.py

@@ -1,7 +1,7 @@
 # Generated by the protocol buffer compiler.  DO NOT EDIT!
 # source: object_detection/protos/square_box_coder.proto
 
-import sys
+import sys,getpass
 _b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1'))
 from google.protobuf import descriptor as _descriptor
 from google.protobuf import message as _message

server_side/api/object_detection/protos/ssd_anchor_generator_pb2.py

@@ -1,7 +1,7 @@
 # Generated by the protocol buffer compiler.  DO NOT EDIT!
 # source: object_detection/protos/ssd_anchor_generator.proto
 
-import sys
+import sys,getpass
 _b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1'))
 from google.protobuf import descriptor as _descriptor
 from google.protobuf import message as _message

server_side/api/object_detection/protos/ssd_pb2.py

@@ -1,7 +1,7 @@
 # Generated by the protocol buffer compiler.  DO NOT EDIT!
 # source: object_detection/protos/ssd.proto
 
-import sys
+import sys,getpass
 _b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1'))
 from google.protobuf import descriptor as _descriptor
 from google.protobuf import message as _message

server_side/api/object_detection/protos/string_int_label_map_pb2.py

@@ -1,7 +1,7 @@
 # Generated by the protocol buffer compiler.  DO NOT EDIT!
 # source: object_detection/protos/string_int_label_map.proto
 
-import sys
+import sys,getpass
 _b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1'))
 from google.protobuf import descriptor as _descriptor
 from google.protobuf import message as _message

server_side/api/object_detection/protos/train_pb2.py

@@ -1,7 +1,7 @@
 # Generated by the protocol buffer compiler.  DO NOT EDIT!
 # source: object_detection/protos/train.proto
 
-import sys
+import sys,getpass
 _b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1'))
 from google.protobuf import descriptor as _descriptor
 from google.protobuf import message as _message

traffic_analyzer/ambulance_detect.py

@@ -2,17 +2,19 @@
 
 import pickle
 import threading
-import sys
+import sys,getpass
 import cv2
 import os
 import numpy as np
+import psutil
+import subprocess
 
 from telnetlib import Telnet
 
 from utils import label_map_util
 from utils import visualization_utils as vis_util
 
-if sys.platform == "win32":
+if getpass.getuser() == "tedankara":
 
     import tensorflow as tf
     from distutils.version import StrictVersion
@@ -30,6 +32,7 @@ from PIL import Image
 from io import BytesIO
 from urllib.parse import urlencode
 from urllib.request import Request, urlopen
+from imutils.video import VideoStream
 import ssl
 
 switch = 1
@@ -41,9 +44,9 @@ sys.path.append("..")
 import time
 from object_detection.utils import ops as utils_ops
 
-TELNET = False
+TELNET = True
 
-AI_IP = '10.10.26.161'
+AI_IP = '127.0.0.1'
 LIGHT_IP = '192.168.2.174'
 context = ssl._create_unverified_context()
 if TELNET:
@@ -69,16 +72,18 @@ def load_image_into_numpy_array(image):
 
 data = {"gpu_temp":"10C","gpu_load":"15%","cpu_temp":"47C","cpu_load":"15%","mem_temp":"NaN","mem_load":"17%","fan_speed":"10000RPM"}
 
-"""
+
 def get_temps():
     global data
-    if not sys.platform == "win32":
-        temps = psutil.sensors_temperatures()
-        data["cpu_temp"] = str(int(temps["dell_smm"][0][1]))+"°C"
-        data["cpu_load"] = str(psutil.cpu_percent())+"%"
-        data["mem_load"] = str(dict(psutil.virtual_memory()._asdict())["percent"])+"%"
-        data["fan_speed"] = str(psutil.sensors_fans()["dell_smm"][0][1])+"RPM"
-"""
+    temps = psutil.sensors_temperatures()
+    result = subprocess.run(['nvidia-smi', '--query-gpu=utilization.memory', '--format=csv'] , stdout=subprocess.PIPE)
+    data["gpu_load"] = result.stdout.decode("utf-8").split("\n")[1]
+    result = subprocess.run(['nvidia-smi', '--query-gpu=temperature.gpu', '--format=csv'] , stdout=subprocess.PIPE)
+    data["gpu_temp"] = result.stdout.decode("utf-8").split("\n")[1]+"°C"
+    data["cpu_temp"] = str(int(temps["coretemp"][0][1]))+"°C"
+    data["cpu_load"] = str(psutil.cpu_percent())+"%"
+    data["mem_load"] = str(dict(psutil.virtual_memory()._asdict())["percent"])+"%"
+    data["fan_speed"] = str(psutil.sensors_fans()["dell_smm"][0][1])+"RPM"
 
 
 def run_inference_for_single_image(image):
@@ -88,7 +93,7 @@ def run_inference_for_single_image(image):
     post_fields = {'img': img_base64,"type":"coco"}     # Set POST fields here
     request = Request(url, urlencode(post_fields).encode())
     data = urlopen(request, context=context).read().decode("ascii")
-    output_dict = json.loads(json.loads(data))
+    output_dict = json.loads(data)
     return output_dict
 
 kill = True
@@ -122,20 +127,19 @@ socket_switch = True
 thread = threading.Thread(target=listener)
 thread.start()
 
-cam = cv2.VideoCapture(1)
+cam = VideoStream(src=0).start()
 
 
 switch = 0
-# get_temps()
+get_temps()
 # (left, right, top, bottom)
-ambulance_coordinates = (65, 190, 0, 140)
+ambulance_coordinates = (150, 400, 250, 400)
 
 reps = -1
 reps_vid = 0
 
 while 1:
-    ret,image = cam.read()
-    image = cv2.imread('/home/efeaydin/Masaüstü/union-county-car-accident-attorneys.jpg')
+    image = cam.read()
     reps_vid += 1
 
     reps += 1
@@ -145,6 +149,7 @@ while 1:
         output_dict = run_inference_for_single_image(image_np)
 
         height, width, channels = image_np.shape
+        cv2.imshow('frmmi', image[ambulance_coordinates[2]:ambulance_coordinates[3], ambulance_coordinates[0]:ambulance_coordinates[1]])
 
         out_dict = {'detection_boxes': [], 'detection_classes': [], 'detection_scores': []}
         for index,i in enumerate(output_dict['detection_classes']):
@@ -192,11 +197,10 @@ while 1:
             line_thickness=8,
             min_score_thresh=0.3
         )
-        cv2.imwrite('/home/efeaydin/Masaüstü/foto.jpg', image_np)
-        cv2.imshow('frame', image_np)
-        ex_c = [27, ord("q"), ord("Q")]
-        if cv2.waitKey(1) & 0xFF in ex_c:
-            break
+        #cv2.imshow('frame', image_np)
+        #ex_c = [27, ord("q"), ord("Q")]
+        #if cv2.waitKey(1) & 0xFF in ex_c:
+        #    break
 
         t2 = time.time()
         print("time taken for {}".format(t2-t1))
@@ -224,13 +228,13 @@ while 1:
                 if cut[i] < 0:
                     cut_send[i] = lens[i] + cut[i]
                 cut_send[i+1] = abs(cut[i])-abs(cut[i+1])
-            client_socket.sendall(json.dumps({"image_full":img,"image_sizes":{"x":65,"y":0,"width":125,"height":140},"load":data}).encode('gbk')+b"\n")
+            client_socket.sendall(json.dumps({"image_full":img,"image_sizes":{"x":90,"y":0,"width":140,"height":140},"load":data}).encode('gbk')+b"\n")
             img_counter += 1
         except:
             socket_switch = True
 
         if img_counter % 10 == 0:
-            # get_temps()
+            get_temps()
             pass
 
     except Exception as e:
@@ -248,6 +252,6 @@ if not socket_switch:
 
 
 cv2.destroyAllWindows()
-cam.release()
+cam.stop()
 kill = False
 thread.join()

traffic_analyzer/ml_setup.py

@@ -1,21 +1,18 @@
 import requests
 import os
 import tarfile
-import sys
+import sys,getpass
 
 urls = [
 	"https://s3-ap-northeast-1.amazonaws.com/mycityreport/trainedModels.tar.gz",
-	"http://download.tensorflow.org/models/object_detection/rfcn_resnet101_coco_2018_01_28.tar.gz",
-	"http://download.tensorflow.org/models/object_detection/faster_rcnn_resnet101_kitti_2018_01_28.tar.gz"
-]
+	"http://download.tensorflow.org/models/object_detection/rfcn_resnet101_coco_2018_01_28.tar.gz",]
 
-paths = ["../server_side/api/modules", ".", '../server_side/api/modules']
+paths = ["../server_side/api/modules", "."]
 
 for i in range(len(urls)):
-	if i == 0:
-		continue
+
 	url = urls[i]
-	print("[INFO]: Downloadinng file: {} to temp.tar.gz!".format(url.split("/")[-1]))
+	print("[INFO]: Downloading file: {} to temp.tar.gz!".format(url.split("/")[-1]))
 
 	with open("temp.tar.gz", 'wb') as f:
 		response = requests.get(url, stream=True)

traffic_analyzer/object_detection/.ipynb_checkpoints/object_detection_tutorial-checkpoint.ipynb

@@ -39,7 +39,7 @@
     "import numpy as np\n",
     "import os\n",
     "import six.moves.urllib as urllib\n",
-    "import sys\n",
+    "import sys,getpass\n",
     "import tarfile\n",
     "import tensorflow as tf\n",
     "import zipfile\n",

traffic_analyzer/object_detection/core/preprocessor.py

@@ -65,7 +65,7 @@ back to rank 4.
 
 import functools
 import inspect
-import sys
+import sys,getpass
 import tensorflow as tf
 
 from tensorflow.python.ops import control_flow_ops

traffic_analyzer/object_detection/data/mscoco_label_map.pbtxt

@@ -36,7 +36,7 @@ item {
 item {
   name: "/m/07r04"
   id: 8
-  display_name: "ambulance"
+  display_name: "truck"
 }
 item {
   name: "/m/019jd"

traffic_analyzer/object_detection/object_detection_tutorial.ipynb

@@ -39,7 +39,7 @@
     "import numpy as np\n",
     "import os\n",
     "import six.moves.urllib as urllib\n",
-    "import sys\n",
+    "import sys,getpass\n",
     "import tarfile\n",
     "import tensorflow as tf\n",
     "import zipfile\n",

traffic_analyzer/object_detection/protos/anchor_generator_pb2.py

@@ -1,7 +1,7 @@
 # Generated by the protocol buffer compiler.  DO NOT EDIT!
 # source: object_detection/protos/anchor_generator.proto
 
-import sys
+import sys,getpass
 _b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1'))
 from google.protobuf import descriptor as _descriptor
 from google.protobuf import message as _message

traffic_analyzer/object_detection/protos/argmax_matcher_pb2.py

@@ -1,7 +1,7 @@
 # Generated by the protocol buffer compiler.  DO NOT EDIT!
 # source: object_detection/protos/argmax_matcher.proto
 
-import sys
+import sys,getpass
 _b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1'))
 from google.protobuf import descriptor as _descriptor
 from google.protobuf import message as _message

traffic_analyzer/object_detection/protos/bipartite_matcher_pb2.py

@@ -1,7 +1,7 @@
 # Generated by the protocol buffer compiler.  DO NOT EDIT!
 # source: object_detection/protos/bipartite_matcher.proto
 
-import sys
+import sys,getpass
 _b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1'))
 from google.protobuf import descriptor as _descriptor
 from google.protobuf import message as _message

traffic_analyzer/object_detection/protos/box_coder_pb2.py

@@ -1,7 +1,7 @@
 # Generated by the protocol buffer compiler.  DO NOT EDIT!
 # source: object_detection/protos/box_coder.proto
 
-import sys
+import sys,getpass
 _b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1'))
 from google.protobuf import descriptor as _descriptor
 from google.protobuf import message as _message

traffic_analyzer/object_detection/protos/box_predictor_pb2.py

@@ -1,7 +1,7 @@
 # Generated by the protocol buffer compiler.  DO NOT EDIT!
 # source: object_detection/protos/box_predictor.proto
 
-import sys
+import sys,getpass
 _b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1'))
 from google.protobuf import descriptor as _descriptor
 from google.protobuf import message as _message

traffic_analyzer/object_detection/protos/calibration_pb2.py

@@ -1,7 +1,7 @@
 # Generated by the protocol buffer compiler.  DO NOT EDIT!
 # source: object_detection/protos/calibration.proto
 
-import sys
+import sys,getpass
 _b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1'))
 from google.protobuf import descriptor as _descriptor
 from google.protobuf import message as _message

traffic_analyzer/object_detection/protos/eval_pb2.py

@@ -1,7 +1,7 @@
 # Generated by the protocol buffer compiler.  DO NOT EDIT!
 # source: object_detection/protos/eval.proto
 
-import sys
+import sys,getpass
 _b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1'))
 from google.protobuf import descriptor as _descriptor
 from google.protobuf import message as _message

traffic_analyzer/object_detection/protos/faster_rcnn_box_coder_pb2.py

@@ -1,7 +1,7 @@
 # Generated by the protocol buffer compiler.  DO NOT EDIT!
 # source: object_detection/protos/faster_rcnn_box_coder.proto
 
-import sys
+import sys,getpass
 _b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1'))
 from google.protobuf import descriptor as _descriptor
 from google.protobuf import message as _message

traffic_analyzer/object_detection/protos/faster_rcnn_pb2.py

@@ -1,7 +1,7 @@
 # Generated by the protocol buffer compiler.  DO NOT EDIT!
 # source: object_detection/protos/faster_rcnn.proto
 
-import sys
+import sys,getpass
 _b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1'))
 from google.protobuf import descriptor as _descriptor
 from google.protobuf import message as _message

traffic_analyzer/object_detection/protos/graph_rewriter_pb2.py

@@ -1,7 +1,7 @@
 # Generated by the protocol buffer compiler.  DO NOT EDIT!
 # source: object_detection/protos/graph_rewriter.proto
 
-import sys
+import sys,getpass
 _b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1'))
 from google.protobuf import descriptor as _descriptor
 from google.protobuf import message as _message

traffic_analyzer/object_detection/protos/grid_anchor_generator_pb2.py

@@ -1,7 +1,7 @@
 # Generated by the protocol buffer compiler.  DO NOT EDIT!
 # source: object_detection/protos/grid_anchor_generator.proto
 
-import sys
+import sys,getpass
 _b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1'))
 from google.protobuf import descriptor as _descriptor
 from google.protobuf import message as _message

traffic_analyzer/object_detection/protos/hyperparams_pb2.py

@@ -1,7 +1,7 @@
 # Generated by the protocol buffer compiler.  DO NOT EDIT!
 # source: object_detection/protos/hyperparams.proto
 
-import sys
+import sys,getpass
 _b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1'))
 from google.protobuf import descriptor as _descriptor
 from google.protobuf import message as _message

traffic_analyzer/object_detection/protos/image_resizer_pb2.py

@@ -1,7 +1,7 @@
 # Generated by the protocol buffer compiler.  DO NOT EDIT!
 # source: object_detection/protos/image_resizer.proto
 
-import sys
+import sys,getpass
 _b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1'))
 from google.protobuf.internal import enum_type_wrapper
 from google.protobuf import descriptor as _descriptor

traffic_analyzer/object_detection/protos/input_reader_pb2.py

@@ -1,7 +1,7 @@
 # Generated by the protocol buffer compiler.  DO NOT EDIT!
 # source: object_detection/protos/input_reader.proto
 
-import sys
+import sys,getpass
 _b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1'))
 from google.protobuf.internal import enum_type_wrapper
 from google.protobuf import descriptor as _descriptor

traffic_analyzer/object_detection/protos/keypoint_box_coder_pb2.py

@@ -1,7 +1,7 @@
 # Generated by the protocol buffer compiler.  DO NOT EDIT!
 # source: object_detection/protos/keypoint_box_coder.proto
 
-import sys
+import sys,getpass
 _b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1'))
 from google.protobuf import descriptor as _descriptor
 from google.protobuf import message as _message

traffic_analyzer/object_detection/protos/losses_pb2.py

@@ -1,7 +1,7 @@
 # Generated by the protocol buffer compiler.  DO NOT EDIT!
 # source: object_detection/protos/losses.proto
 
-import sys
+import sys,getpass
 _b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1'))
 from google.protobuf import descriptor as _descriptor
 from google.protobuf import message as _message