Updated code and README.md

README.md

@@ -1,2 +1,9 @@
 # 144-Client
-This is the code that runs on an external server, in our case a MacBook Air running macOS High Sierra. The main purpose of this code is to perform object recognition(for stop signs) on video that is transmitted from the Raspberry Pi which has a camera module attached. There are three important files:
+This is the code that runs on an external server, in our case a MacBook Air running macOS High Sierra, that performs object recognition (for stop signs) on video that is transmitted from the Raspberry Pi which has a camera module attached. 
+
+There are three important files:
+1. `autonomous_receiver.py`: Takes in one paramater that specifies which protocol to use (either UDP or TCP), sets up the appropriate sockets and receives video frames from the Raspberry Pi for processing. After an initial 10 frames are received, a `start` command is sent to the Pi to signal the car to start driving, then each following frame is passed through our Stop Sign object detector and once a match has been found sends a `stop` command back to the Pi to signal to the car that a stop sign has been found.
+2. `detection/stopsign_detection.py`: Defines a simple `StopSignClassifier` class that loads a pre-trained haar stop sign classifier file (`detection/stopsign_classifier.xml`), and contains a function that given an opencv frame, attempts to detect a stop sign and returns `True` if found else `False`.
+3. `detection/stopsign_classifier.xml`: Pre-trained haar classifier for stop signs.
+
+There is also one irrelevant file (for fun) `client.py`, that allows you to manually drive the mobile RC car from ane external server.

autonomous_receiver.py

@@ -1,22 +1,22 @@
 """
 Receives opencv frames from Rasperry Pi Sender
-to process for object detection.
+to process for object detection and sends car commands back.
 """
 import sys
 import cv2
-import pickle
 import numpy as np
-import struct
 import socket
-import random
 import time
 from detection.stopsign_detection import StopSignClassifier
 
-HOST_IP=''
-SENDING_HOST_IP='10.251.45.1'
+# IP address of Raspberry Pi 
+RPI_IP='10.251.45.1'
+
+# ports to use for transmitting video and receiving commands
 VIDEO_PORT=8018
 COMMAND_PORT=8019
 
+# size of each msg (frame)
 MSG_SZ = 230400
 
 
@@ -37,7 +37,7 @@ def receive_video(protocol):
 
     # bind to host
     print("Binding to port %d..." % VIDEO_PORT)
-    sock.bind((HOST_IP, VIDEO_PORT))
+    sock.bind(('', VIDEO_PORT))
 
     # if TCP listen and accept connection
     conn = None
@@ -49,20 +49,22 @@ def receive_video(protocol):
         print("Established connection with %s..." % addr)
 
     # sleep then establish command socket
-    time.sleep(3)
+    time.sleep(1)
     print("\n\nCreating socket for sending car commands...")
     command_sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
     print("Socket for sending car commands created...")
 
-    print("Connecting sending socket to %s:%d..." % (SENDING_HOST_IP, COMMAND_PORT))
+    print("Connecting sending socket to %s:%d..." % (RPI_IP, COMMAND_PORT))
     while True:
         # try to connect to socket, if not ready sleep and try again
         try:
-            command_sock.connect((SENDING_HOST_IP, COMMAND_PORT))
+            command_sock.connect((RPI_IP, COMMAND_PORT))
             break
         except:
+            print("Connection failed, retrying...")
             time.sleep(1)
-    print("Connected sending socket to %s:%d...\n\n" % (SENDING_HOST_IP, COMMAND_PORT))
+
+    print("Connected sending socket to %s:%d...\n\n" % (RPI_IP, COMMAND_PORT))
 
     # initialize stop sign detection
     print("Initializing stopsign detection classifier...")
@@ -118,19 +120,20 @@ def receive_video(protocol):
         if cv2.waitKey(1) & 0xFF == ord('q'):
             break
 
-        print(num_frame)
+        # start car after 10 frames have been received
         if num_frame == 10:
             print("Starting car...")
-            # start car
+            # send start car command
             command_sock.send('start'.encode('utf-8'))
 
     # close sockets
     sock.close()
     command_sock.close()
 
 
+# check protocol arg, then call receive_video
 if __name__ == '__main__':
-    if len(sys.argv) == 2 and sys.argv[1] in ['tcp', 'udp', 'rdp']:
+    if len(sys.argv) == 2 and sys.argv[1] in ['tcp', 'udp']:
         protocol = sys.argv[1].upper()
         receive_video(protocol)
     else:

detection/stopsign_detection.py

@@ -1,14 +1,13 @@
-import time
-
 import cv2
-import imutils
-import numpy as np
+
 
 class StopSignClassifier:
     def __init__(self, *args, **kwargs):
+        # on init load classifier
         self.load_classifier()
 
     def load_classifier(self):
+        # loads classifier from pre-trained classifier file (must use absolute path)
         self.classifier = cv2.CascadeClassifier("/Users/stevenkekacs/144-Client/detection/stopsign_classifier.xml")
 
     def detect_stopsign(self, img):
@@ -20,16 +19,22 @@ def detect_stopsign(self, img):
         # Detect any stop signs in the image using the classifier at various scales.
         stop_signs = self.classifier.detectMultiScale(gray, 1.02, 10)
 
-        # Draw a rectangle around each detected sign and display it.
-        for (x, y, w, h) in stop_signs:
+        # if stop signs found, draw rectange, calc area and return True
+        if stop_signs.any():
+            # get position and dimensions
+            x, y, w, h = stop_signs[0]
+
+            # draw rectangle around stop sign
             cv2.rectangle(img, (x, y), (x+w , y+h), (255, 0, 0), 2)
 
-            # calculate area of stop sign, if greater than cutoff
-            # return True
+            # calculate area of stop sign
             stopsign_area = w * h
-            print(stopsign_area)
+            print("Stopsign found:", stopsign_area)
+
+            # return True for stopsign found
             return True
 
+        # no stop sign found so return False
         return False