1

我一直在研究对象检测和跟踪系统有一段时间了。当检测到一个人时，我尝试点亮 LED，根据分辨率范围的宽度确定边界框的坐标。截至目前，当我没有插入串行通信功能时，FPS 大约为 30。但是当我插入串行通讯时，fps 会在 7-10 左右下降得太低。什么可能导致这里的问题？

操作系统 = Windows

GPU = GTX 1070

CPU = i7

型号 = Darkflow, yolov2

目标检测代码。

import cv2
from darkflow.net.build import TFNet
import numpy as np
import time
from collections import namedtuple
import luggage_arduino

"""
Main system for running the whole script for object detection and tracking
"""
class NeuralNetwork:
def __init__(self):
    """Define model configuration and weight"""
    options = {
        'model': 'cfg/yolov2.cfg',
        'load': 'bin/yolov2.weights',
        'threshold': 0.8,  # Sets the confidence level of detecting box, range from 0 to 1
        'gpu': 0.8  # If do not want to use gpu, set to 0
    }

    """Define OpenCV configuration"""
    tfnet = TFNet(options)
    colors = [tuple(255 * np.random.rand(3)) for _ in range(10)]  # Set colors for different boxes
    capture = cv2.VideoCapture(0, cv2.CAP_DSHOW)
    capture.set(cv2.CAP_PROP_FRAME_WIDTH, 1280)
    capture.set(cv2.CAP_PROP_FRAME_HEIGHT, 720)

    while True:  # Main loop for object detection and tracking
        stime = time.time()
        ret, frame = capture.read()
        box = cv2.rectangle(frame, (0, 0), (426, 720), (0, 0, 255), 2)  # Parameter of first segment (LEFT)
        box2 = cv2.rectangle(frame, (426, 0), (852, 720), (0, 0, 255), 2)  # Parameter of second segment (CENTER)
        box3 = cv2.rectangle(frame, (852, 0), (1280, 720), (0, 0, 255), 2)  # Parameter of third segment (RIGHT)
        if ret:
            results = tfnet.return_predict(frame)
            for color, result in zip(colors, results):
                tl = (result['topleft']['x'], result['topleft']['y'])
                br = (result['bottomright']['x'], result['bottomright']['y'])
                label = result['label']
                confidence = result['confidence']
                text = '{}: {:.0f}%'.format(label, confidence * 100)
                frame = cv2.rectangle(frame, tl, br, color, 5)
                frame = cv2.putText(frame, text, tl, cv2.FONT_HERSHEY_COMPLEX, 1, (0, 0, 0), 2)
                self.center_of_box(tl, br)  # Calls the function for coordinate calculation
            cv2.imshow('frame', frame)
            print('FPS {:.1f}'.format(1 / (time.time() - stime)))
        if cv2.waitKey(1) & 0xFF == ord('q'):
            break

    capture.release()
    cv2.destroyAllWindows()

def center_of_box(self, tl, br):
    self.tl = tl
    self.br = br
    center_coord = namedtuple("center_coord", ['x', 'y'])  # List of calculated center coord for each FPS
    center_x = ((tl[0] + br[0]) / 2)
    center_y = ((tl[1] + br[1]) / 2)
    center_box = center_coord(center_x, center_y)  # Save center coord of detected box in list
    print(center_box)
    self.box_tracking(center_x)  # Call function for tracking the box coord

def box_tracking(self, center_x):
    self.center_x = center_x
    while True:
        if 0 <= center_x <= 426:
            center = -1
        elif 426 < center_x <= 852:
            center = 0
        elif 852 < center_x <= 1280:
            center = 1
        else:
            center = 2
        break
    luggage_arduino.Arduino(center)  # Calls function for serial comm

pyserial comms 的代码：

import serial
import time

arduino = serial.Serial("com3", 9600)


def serial_comm():  # Pass the function
    pass


"""Main class for serial comm"""


class Arduino:
    def __init__(self, center):
        self.serial_comm(center)  # Calls function of serial comm

    def serial_comm(self, center):
        if center == -1:
            time.sleep(1)
            arduino.write(b'L')  # b can be replaced with str.encode("Your string here")
            serial_comm()
        elif center == 0:
            time.sleep(1)
            arduino.write(b'C')
            serial_comm()
        elif center == 1:
            time.sleep(1)
            arduino.write(b'R')
            serial_comm()
        else:
            center = 2
            time.sleep(1)
            arduino.write(b'N')
            serial_comm()
        time.sleep(2)
4

2 回答 2

0

对于那些有兴趣的人，我会在我想出来的时候发布答案。解决方案是使用线程并同时运行这些类。这是代码！

import cv2
from darkflow.net.build import TFNet
import numpy as np
import time
from collections import namedtuple
import luggage_arduino
import psutil
import threading

"""
Main system for running the whole script for object detection and tracking
"""
center_of_x = []


class NeuralNetwork():
    def __init__(self):
        self.object_detect()

    def object_detect(self):
        options = {
            'model': 'cfg/yolov2.cfg',
            'load': 'bin/yolov2.weights',
            'threshold': 0.8,  # Sets the confidence level of detecting box, range from 0 to 1
            'gpu': 0.8  # If do not want to use gpu, set to 0
        }
        cpu_usage = psutil.cpu_percent(interval=1)
        tfnet = TFNet(options)
        capture = cv2.VideoCapture(0, cv2.CAP_DSHOW)
        capture.set(cv2.CAP_PROP_FRAME_WIDTH, 1280)
        capture.set(cv2.CAP_PROP_FRAME_HEIGHT, 720)
        while True:  # Main loop for object detection and tracking
            stime = time.time()
            ret, frame = capture.read()
            box = cv2.rectangle(frame, (0, 0), (426, 720), (0, 0, 255), 2)  # Parameter of first segment (LEFT)
            box2 = cv2.rectangle(frame, (426, 0), (852, 720), (0, 0, 255), 2)  # Parameter of second segment (CENTER)
            box3 = cv2.rectangle(frame, (852, 0), (1280, 720), (0, 0, 255), 2)  # Parameter of third segment (RIGHT)
            if ret:
                results = tfnet.return_predict(frame)
                for result in results:
                    tl = (result['topleft']['x'], result['topleft']['y'])
                    br = (result['bottomright']['x'], result['bottomright']['y'])
                    label = result['label']
                    confidence = result['confidence']
                    text = '{}: {:.0f}%'.format(label, confidence * 100)
                    frame = cv2.rectangle(frame, tl, br, (255, 153, 255), 2)
                    frame = cv2.putText(frame, text, tl, cv2.FONT_HERSHEY_COMPLEX, 1, (0, 0, 0), 2)
                    self.center_of_box(tl, br)
                cv2.imshow('frame', frame)
                print('FPS {:.1f}'.format(1 / (time.time() - stime)))
                print(cpu_usage)
            if cv2.waitKey(1) & 0xFF == ord('q'):
                break

        capture.release()
        cv2.destroyAllWindows()

    def center_of_box(self, tl, br):
        global center_of_x
        self.tl = tl
        self.br = br
        center_coord = namedtuple("center_coord", ['x', 'y'])  # List of calculated center coord for each FPS
        center_x = ((tl[0] + br[0]) / 2)
        center_y = ((tl[1] + br[1]) / 2)
        center_box = center_coord(center_x, center_y)  # Save center coord of detected box in list
        center_of_x.clear()
        center_of_x.append(center_x)
        print(center_box)
        return center_x


class Ard:
    def __init__(self):
        time.sleep(7)
        while True:
            for i in center_of_x:
                self.box_tracking(i)

    def box_tracking(self, center_x):
        self.center_x = center_x
        while True:
            if 0 <= center_x <= 426:
                center = -1
            elif 426 < center_x <= 852:
                center = 0
            elif 852 < center_x <= 1280:
                center = 1
            else:
                center = 2
            break
        luggage_arduino.Arduino(center)  # Calls function for serial comm


t1 = threading.Thread(target=NeuralNetwork)
t2 = threading.Thread(target=Ard)

t1.start()
t2.start()

这是arduino代码。

int data;
int LED2=2;
int LED3=3;
int LED4=4;


void setup() {
  // put your setup code here, to run once:
  Serial.begin(9600);
  pinMode(LED2, OUTPUT);
  digitalWrite (LED2, LOW);
  pinMode(LED3, OUTPUT);
  digitalWrite (LED3, LOW);
  pinMode(LED4, OUTPUT);
  digitalWrite (LED4, LOW);
}

void loop() {
  // put your main code here, to run repeatedly:
  while (Serial.available()){
    data = Serial.read();
    if(data == 'L'){
      digitalWrite(LED2, HIGH);
      delay(100);
      digitalWrite(LED2, LOW);
      digitalWrite(LED3, LOW);
      digitalWrite(LED4, LOW);
    }
    else if (data == 'C'){
      digitalWrite(LED3, HIGH);
      delay(100);
      digitalWrite(LED3, LOW);
      digitalWrite(LED2, LOW);
      digitalWrite(LED4, LOW);
    }
    else if (data == 'R'){
      digitalWrite(LED4, HIGH);
      delay(100);
      digitalWrite(LED4, LOW);
      digitalWrite(LED2, LOW);
      digitalWrite(LED3, LOW);
    }
    else if (data == 'N'){
      digitalWrite(LED2, LOW);
      digitalWrite(LED3, LOW);
      digitalWrite(LED4, LOW);
    }
  }
}

这是pyserial代码。

import serial
import time

arduino = serial.Serial("com3", 9600)


def serial_comm():  # Pass the function
    pass


"""Main class for serial comm"""


class Arduino:
    def __init__(self, center):
        self.serial_comm(center)  # Calls function of serial comm

    def serial_comm(self, center):
        self.center = center
        if center == -1:
            time.sleep(1)
            arduino.write(b'L')  # b can be replaced with str.encode("Your string here")
            serial_comm()
        elif center == 0:
            time.sleep(1)
            arduino.write(b'C')
            serial_comm()
        elif center == 1:
            time.sleep(1)
            arduino.write(b'R')
            serial_comm()
        else:
            center = 2
            time.sleep(1)
            arduino.write(b'N')
            serial_comm()
        time.sleep(2)
于 2019-12-26T02:44:05.297 回答
0

time.sleep()如果您的函数未在线程中运行，则调用可能是原因。

class Arduino在线程中使用？如果没有，它可能应该。

当您使用Serial.readline()时，这些调用会阻塞并等待数据。

请参阅此答案中的速度改进部分和此处发布的代码。

于 2019-12-26T06:30:22.690 回答