code cleanup

lab1/can_to_ip/can_to_ip.ino

@@ -7,10 +7,8 @@
 
 long unsigned int rxId;
 unsigned char len = 0;
-unsigned char distance[2]; 
+unsigned char distance[2];
 
-// Enter a MAC address and IP address for your controller below.
-// The IP address will be dependent on your local network:
 byte mac[] = {
   0xDE, 0xAD, 0xBE, 0xEF, 0xFE, 0xED
 };
@@ -18,21 +16,21 @@ IPAddress remote_ip(192, 168, 0, 100);
 int remote_port = 3491;
 int local_port = 3495;
 
-char packetBuffer[UDP_TX_PACKET_MAX_SIZE];  // buffer to hold incoming packet,
+char packetBuffer[UDP_TX_PACKET_MAX_SIZE];
 
-MCP_CAN CAN0(9);                               // Set CS to pin 9
+MCP_CAN CAN0(9);
 EthernetUDP udp;
 
 void setup()
 {
   Serial.begin(115200);
-  
+
   // Initialize MCP2515 running at 16MHz with a baudrate of 500kb/s and the masks and filters disabled.
   if(CAN0.begin(MCP_ANY, CAN_500KBPS, MCP_16MHZ) == CAN_OK)
     Serial.println("MCP2515 Initialized Successfully!");
   else
     Serial.println("Error Initializing MCP2515...");
-  
+
   CAN0.setMode(MCP_NORMAL);                     // Set operation mode to normal so the MCP2515 sends acks to received data.
 
   pinMode(CAN0_INT, INPUT);                            // Configuring pin for /INT input
@@ -62,7 +60,7 @@ void loop()
     int result = distance[0]+distance[1]*256;
     Serial.println(result);
   }
- 
+
   // send the message via udp
   udp.beginPacket(remote_ip, remote_port);
   udp.write((char *)distance);
@@ -90,6 +88,6 @@ void loop()
   }
    //send signal to LED
   byte sndStat = CAN0.sendMsgBuf(0x100, 0, 1, (byte*)&packetBuffer);
-  
+
   delay(500);
 }

lab1/sensor_to_can/sensor_to_can.ino

@@ -12,22 +12,22 @@ int distance;
 long unsigned int rxId;
 unsigned char len = 0;
 unsigned char rxBuf[8];
-char msgString[128];                        // Array to store serial string
-unsigned long previousMillis = 0;        // will store last time LED was updated
+char msgString[128];
+unsigned long previousMillis = 0;
 const long interval = 300;           // interval at which to blink (milliseconds)
 int ledState = LOW;             // ledState used to set the LED
 
 MCP_CAN CAN0(10);                               // Set CS to pin 10
 
 void setup() {
-pinMode(trigPin, OUTPUT); 
-pinMode(echoPin, INPUT); 
+pinMode(trigPin, OUTPUT);
+pinMode(echoPin, INPUT);
 pinMode(ledPin, OUTPUT);
-Serial.begin(115200); 
+Serial.begin(115200);
 
-  if(CAN0.begin(MCP_ANY, CAN_500KBPS, MCP_16MHZ) == CAN_OK) 
+  if(CAN0.begin(MCP_ANY, CAN_500KBPS, MCP_16MHZ) == CAN_OK)
     Serial.println("MCP2515 Initialized Successfully!");
-  else 
+  else
     Serial.println("Error Initializing MCP2515...");
 
   CAN0.setMode(MCP_NORMAL);   // Change to normal mode to allow messages to be transmitted
@@ -53,7 +53,7 @@ void loop() {
 
 
   byte sndStat = CAN0.sendMsgBuf(0x100, 0, 2, (byte*)&distance);
-  
+
   delayMicroseconds(150);
 
   if(!digitalRead(CAN0_INT))                         // If CAN0_INT pin is low, read receive buffer
@@ -62,21 +62,21 @@ void loop() {
     //receive yes /no
     Serial.println(rxBuf[0]);
   }
-  if(rxBuf[0] == 'y') 
+  if(rxBuf[0] == 'y')
   {
     unsigned long currentMillis = millis();
 
     if (currentMillis - previousMillis >= interval) {
       // save the last time you blinked the LED
       previousMillis = currentMillis;
-  
+
       // if the LED is off turn it on and vice-versa:
       if (ledState == LOW) {
         ledState = HIGH;
       } else {
         ledState = LOW;
       }
-  
+
       // set the LED with the ledState of the variable:
       digitalWrite(ledPin, ledState);
     }

lab1/tf.py

 import os
 import cv2
 import numpy as np
-from picamera.array import PiRGBArray
-from picamera import PiCamera
 import tensorflow as tf
 import argparse
 import sys
 import socket
-
 import errno
 
+from picamera.array import PiRGBArray
+from picamera import PiCamera
+
 IM_WIDTH = 1280
 IM_HEIGHT = 720
 
 # local port and ip
-IP = "192.168.0.100"
+IP = "192.168.0.100"    # need to change to ip assigned by switch
 PORT = 3491
 TCP_PORT = 3490
 
@@ -26,20 +26,15 @@ sys.path.append('..')
 from utils import label_map_util
 from utils import visualization_utils as vis_util
 
-# Name of the directory containing the object detection module we're using
-MODEL_NAME = 'ssdlite_mobilenet_v2_coco_2018_05_09'
-
 # Grab path to current working directory
 CWD_PATH = os.getcwd()
 
-PATH_TO_CKPT = "/home/pi/Documents/ssd_mobilenet_v1_coco_2018_01_28/frozen_inference_graph.pb"
 PATH_TO_LABELS = os.path.join(CWD_PATH,'data','mscoco_label_map.pbtxt')
 
 # Number of classes the object detector can identify
 NUM_CLASSES = 90
 
 # Load the label map.
-
 label_map = label_map_util.load_labelmap(PATH_TO_LABELS)
 categories = label_map_util.convert_label_map_to_categories(label_map, max_num_classes=NUM_CLASSES, use_display_name=True)
 category_index = label_map_util.create_category_index(categories)
@@ -48,7 +43,7 @@ category_index = label_map_util.create_category_index(categories)
 detection_graph = tf.Graph()
 with detection_graph.as_default():
     od_graph_def = tf.GraphDef()
-    with tf.gfile.GFile(PATH_TO_CKPT, 'rb') as fid:
+    with tf.gfile.GFile('/home/pi/Documents/ssd_mobilenet_v1_coco_2018_01_28/frozen_inference_graph.pb', 'rb') as fid:
         serialized_graph = fid.read()
         od_graph_def.ParseFromString(serialized_graph)
         tf.import_graph_def(od_graph_def, name='')
@@ -82,10 +77,9 @@ freq = cv2.getTickFrequency()
 font = cv2.FONT_HERSHEY_SIMPLEX
 
 for frame1 in camera.capture_continuous(rawCapture, format="bgr",use_video_port=True):
-    
+
     t1 = cv2.getTickCount()
-    # Acquire frame and expand frame dimensions to have shape: [1, None, None, 3]
-    # i.e. a single-column array, where each item in the column has the pixel RGB value
+
     frame = np.copy(frame1.array)
     frame.setflags(write=1)
     frame_expanded = np.expand_dims(frame, axis=0)
@@ -96,19 +90,18 @@ for frame1 in camera.capture_continuous(rawCapture, format="bgr",use_video_port=
         feed_dict={image_tensor: frame_expanded})
 
     # receive signal from ECU
-    
     distance = 1000
     while True:
         try:
             data,addr = serverSock.recvfrom(10)
             distance = int.from_bytes(data, "big")
-            
+
         except socket.error as error:
             if error.errno == errno.EAGAIN:
                 break
             else:
                 print(error.errno)
-        
+
     print(distance)
     # Send signal back to ECU
     if num > 0 and distance < 150:
@@ -118,7 +111,6 @@ for frame1 in camera.capture_continuous(rawCapture, format="bgr",use_video_port=
         serverSock.sendto(b"n", addr)
         led_status = 'OFF'
 
-    # Draw the results of the detection (aka 'visulaize the results')
     vis_util.visualize_boxes_and_labels_on_image_array(
         frame,
         np.squeeze(boxes),
@@ -129,29 +121,25 @@ for frame1 in camera.capture_continuous(rawCapture, format="bgr",use_video_port=
         line_thickness=8,
         min_score_thresh=0.40)
 
-    # All the results have been drawn on the frame, so it's time to display it.
-    # cv2.imshow('Object detector', frame)
     cv2.putText(frame,"FPS: {0:.2f}".format(frame_rate_calc), (30,50),font,1,(255,255,0),2,cv2.LINE_AA)
-    
+
     t2 = cv2.getTickCount()
     time1 = (t2-t1)/freq
     frame_rate_calc = 1/time1
+
+    # save image locally and send to host running dashboard
     cv2.imwrite("/home/pi/Documents/img.png", frame)
-    
+
     sendSock = socket.socket()
     sendSock.connect(("192.168.0.103", 3490))
-    
+
     with open("/home/pi/Documents/img.png", "rb") as img:
         output = str(distance)+"&"+str(led_status)+"&"+"data="
         output = output.encode()
         output += img.read()
         sendSock.send(output)
-    
+
     sendSock.close()
-    
-    # Press 'q' to quit
-    if cv2.waitKey(1) == ord('q'):
-        break
 
     rawCapture.truncate(0)