Difference between revisions of "2021SummerTeam6"

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= '''Our Python Code!''' =
= '''Our Python Code!''' =
  <nowiki># -*- coding: utf-8 -*-
  <nowiki>
"""
import rospy
Created on Mon Mar 29 14:31:14 2021
import cv2
import numpy as np
from std_msgs.msg import Int32, Int32MultiArray
from sensor_msgs.msg import Image
from decoder import decodeImage
import time
from cv_bridge import CvBridge
from elements.yolo import OBJ_DETECTION


@author: Anwar
# Give names for nodes and topics for ROS
"""
STOPSIGN_NODE_NAME = 'stopsign_node'
## You need to install pyaudio to run this example
STOPSIGN_TOPIC_NAME = 'StopSign'
# pip install pyaudio
CAMERA_TOPIC_NAME = 'camera_rgb'


# When using a microphone, the AudioSource `input` parameter would be
# types of objects that can be detected
# initialised as a queue. The pyaudio stream would be continuosly adding
 
# recordings to the queue, and the websocket client would be sending the
Object_classes = ['person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'traffic light',                'fire hydrant', 'stop sign', 'parking meter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow',                'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee',                'skis', 'snowboard', 'sports ball', 'kite', 'baseball bat', 'baseball glove', 'skateboard', 'surfboard',                'tennis racket', 'bottle', 'wine glass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple',                'sandwich', 'orange', 'broccoli', 'carrot', 'hot dog', 'pizza', 'donut', 'cake', 'chair', 'couch',                'potted plant', 'bed', 'dining table', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cell phone',                'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddy bear',                'hair drier', 'toothbrush' ]
# recordings to the speech to text service
 
 
Object_colors = list(np.random.rand(80,3)*255)
Object_detector = OBJ_DETECTION('weights/yolov5s.pt', Object_classes)
 
 
class StopSignDetection:
        def __init__(self):
            self.init_node = rospy.init_node(STOPSIGN_NODE_NAME, anonymous=False)                # initialize the node
            self.StopSign_publisher = rospy.Publisher(STOPSIGN_TOPIC_NAME,Int32, queue_size=1)    # make this node a publisher
            self.camera_subscriber = rospy.Subscriber(CAMERA_TOPIC_NAME,Image,self.detect_stop)  # subscribe to the camera feed
            self.bridge =CvBridge()
            self.stopsign = Int32()
 
        def detect_stop(self,data):
                frame = self.bridge.imgmsg_to_cv2(data)          # get frame from camera feed data
 
                        # detection process
                objs = Object_detector.detect(frame)            # detect the object
 
                        # plotting
                for obj in objs:
                                # print(obj)
                                label = obj['label']
                                score = obj['score']
                                [(xmin,ymin),(xmax,ymax)] = obj['bbox']
                                color = Object_colors[Object_classes.index(label)]
                                frame = cv2.rectangle(frame, (xmin,ymin), (xmax,ymax), color, 2)
                                frame = cv2.putText(frame, f'{label} ({str(score)})', (xmin,ymin),
                cv2.FONT_HERSHEY_SIMPLEX , 0.75, co

Revision as of 00:47, 6 September 2021

Team 6 Members

P1.jpg


From Left to Right

Kevin Bishara (MAE) | William Lynch (ECE) | Anwar Hsu (ECE)

Robot & 3D Modeling Designs

Our Robot

P2.png

Electronics Plate

Cad1.png

Camera Mount

Jetson Nano Case

Cad2.png Cad3.png

Autonomous Laps

    DonkeyCar Laps

Our autonomous laps for DonkeyCar can be found here.

    OpenCV/ROS Laps

Our OpenCV/ROS autonomous laps can be found here.

Final Project Overview

Our Python Code!

<nowiki>

import rospy import cv2 import numpy as np from std_msgs.msg import Int32, Int32MultiArray from sensor_msgs.msg import Image from decoder import decodeImage import time from cv_bridge import CvBridge from elements.yolo import OBJ_DETECTION

  1. Give names for nodes and topics for ROS

STOPSIGN_NODE_NAME = 'stopsign_node' STOPSIGN_TOPIC_NAME = 'StopSign' CAMERA_TOPIC_NAME = 'camera_rgb'

  1. types of objects that can be detected

Object_classes = ['person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'traffic light', 'fire hydrant', 'stop sign', 'parking meter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseball bat', 'baseball glove', 'skateboard', 'surfboard', 'tennis racket', 'bottle', 'wine glass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hot dog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'potted plant', 'bed', 'dining table', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cell phone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddy bear', 'hair drier', 'toothbrush' ]


Object_colors = list(np.random.rand(80,3)*255) Object_detector = OBJ_DETECTION('weights/yolov5s.pt', Object_classes)


class StopSignDetection:

       def __init__(self):
           self.init_node = rospy.init_node(STOPSIGN_NODE_NAME, anonymous=False)                 # initialize the node
           self.StopSign_publisher = rospy.Publisher(STOPSIGN_TOPIC_NAME,Int32, queue_size=1)    # make this node a publisher
           self.camera_subscriber = rospy.Subscriber(CAMERA_TOPIC_NAME,Image,self.detect_stop)   # subscribe to the camera feed
           self.bridge =CvBridge()
           self.stopsign = Int32()
       def detect_stop(self,data):
               frame = self.bridge.imgmsg_to_cv2(data)          # get frame from camera feed data
                       # detection process
               objs = Object_detector.detect(frame)             # detect the object 
                       # plotting
               for obj in objs:
                               # print(obj)
                               label = obj['label']
                               score = obj['score']
                               [(xmin,ymin),(xmax,ymax)] = obj['bbox']
                               color = Object_colors[Object_classes.index(label)]
                               frame = cv2.rectangle(frame, (xmin,ymin), (xmax,ymax), color, 2)
                               frame = cv2.putText(frame, f'{label} ({str(score)})', (xmin,ymin),
                cv2.FONT_HERSHEY_SIMPLEX , 0.75, co