python實(shí)現(xiàn)單目標(biāo)、多目標(biāo)、多尺度、自定義特征的KCF跟蹤算法(實(shí)例代碼)

更新時(shí)間：2020年01月08日 08:59:58 作者：奔跑的Yancy

這篇文章主要介紹了python實(shí)現(xiàn)單目標(biāo)、多目標(biāo)、多尺度、自定義特征的KCF跟蹤算法,本文通過(guò)實(shí)例代碼給大家介紹的非常詳細(xì)，具有一定的參考借鑒價(jià)值，需要的朋友可以參考下

單目標(biāo)跟蹤：

直接調(diào)用opencv中封裝的tracker即可。

#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Sun Jan 5 17:50:47 2020
第四章 kcf跟蹤
@author: youxinlin
"""
import cv2
from items import MessageItem
import time
import numpy as np
'''
監(jiān)視者模塊,負(fù)責(zé)入侵檢測(cè),目標(biāo)跟蹤
'''
class WatchDog(object):
 #入侵檢測(cè)者模塊,用于入侵檢測(cè)
 def __init__(self,frame=None):
  #運(yùn)動(dòng)檢測(cè)器構(gòu)造函數(shù)
  self._background = None
  if frame is not None:
   self._background = cv2.GaussianBlur(cv2.cvtColor(frame,cv2.COLOR_BGR2GRAY),(21,21),0)
  self.es = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (10, 10))
 def isWorking(self):
  #運(yùn)動(dòng)檢測(cè)器是否工作
  return self._background is not None
 def startWorking(self,frame):
  #運(yùn)動(dòng)檢測(cè)器開(kāi)始工作
  if frame is not None:
   self._background = cv2.GaussianBlur(cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY), (21, 21), 0)
 def stopWorking(self):
  #運(yùn)動(dòng)檢測(cè)器結(jié)束工作
  self._background = None
 def analyze(self,frame):
  #運(yùn)動(dòng)檢測(cè)
  if frame is None or self._background is None:
   return
  sample_frame = cv2.GaussianBlur(cv2.cvtColor(frame,cv2.COLOR_BGR2GRAY),(21,21),0)
  diff = cv2.absdiff(self._background,sample_frame)
  diff = cv2.threshold(diff, 25, 255, cv2.THRESH_BINARY)[1]
  diff = cv2.dilate(diff, self.es, iterations=2)
  image, cnts, hierarchy = cv2.findContours(diff.copy(),cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
  coordinate = []
  bigC = None
  bigMulti = 0
  for c in cnts:
   if cv2.contourArea(c) < 1500:
    continue
   (x,y,w,h) = cv2.boundingRect(c)
   if w * h > bigMulti:
    bigMulti = w * h
    bigC = ((x,y),(x+w,y+h))
  if bigC:
   cv2.rectangle(frame, bigC[0],bigC[1], (255,0,0), 2, 1)
  coordinate.append(bigC)
  message = {"coord":coordinate}
  message['msg'] = None
  return MessageItem(frame,message)
class Tracker(object):
 '''
 追蹤者模塊,用于追蹤指定目標(biāo)
 '''
 def __init__(self,tracker_type = "BOOSTING",draw_coord = True):
  '''
  初始化追蹤器種類(lèi)
  '''
  #獲得opencv版本
  (major_ver, minor_ver, subminor_ver) = (cv2.__version__).split('.')
  self.tracker_types = ['BOOSTING', 'MIL','KCF', 'TLD', 'MEDIANFLOW', 'GOTURN']
  self.tracker_type = tracker_type
  self.isWorking = False
  self.draw_coord = draw_coord
  #構(gòu)造追蹤器
  if int(minor_ver) < 3:
   self.tracker = cv2.Tracker_create(tracker_type)
  else:
   if tracker_type == 'BOOSTING':
    self.tracker = cv2.TrackerBoosting_create()
   if tracker_type == 'MIL':
    self.tracker = cv2.TrackerMIL_create()
   if tracker_type == 'KCF':
    self.tracker = cv2.TrackerKCF_create()
   if tracker_type == 'TLD':
    self.tracker = cv2.TrackerTLD_create()
   if tracker_type == 'MEDIANFLOW':
    self.tracker = cv2.TrackerMedianFlow_create()
   if tracker_type == 'GOTURN':
    self.tracker = cv2.TrackerGOTURN_create()
 def initWorking(self,frame,box):
  '''
  追蹤器工作初始化
  frame:初始化追蹤畫(huà)面
  box:追蹤的區(qū)域
  '''
  if not self.tracker:
   raise Exception("追蹤器未初始化")
  status = self.tracker.init(frame,box)
  if not status:
   raise Exception("追蹤器工作初始化失敗")
  self.coord = box
  self.isWorking = True
 def track(self,frame):
  '''
  開(kāi)啟追蹤
  '''
  message = None
  if self.isWorking:
   status,self.coord = self.tracker.update(frame)
   if status:
    message = {"coord":[((int(self.coord[0]), int(self.coord[1])),(int(self.coord[0] + self.coord[2]), int(self.coord[1] + self.coord[3])))]}
    if self.draw_coord:
     p1 = (int(self.coord[0]), int(self.coord[1]))
     p2 = (int(self.coord[0] + self.coord[2]), int(self.coord[1] + self.coord[3]))
     cv2.rectangle(frame, p1, p2, (255,0,0), 2, 1)
     message['msg'] = "is tracking"
  return MessageItem(frame,message)
class ObjectTracker(object):
 def __init__(self,dataSet):
  self.cascade = cv2.CascadeClassifier(dataSet)
 def track(self,frame):
  gray = cv2.cvtColor(frame,cv2.COLOR_BGR2GRAY)
  faces = self.cascade.detectMultiScale(gray,1.03,5)
  for (x,y,w,h) in faces:
   cv2.rectangle(frame,(x,y),(x+w,y+h),(0,0,255),2)
  return frame
if __name__ == '__main__' :
# tracker_types = ['BOOSTING', 'MIL','KCF', 'TLD', 'MEDIANFLOW', 'GOTURN']
 tracker = Tracker(tracker_type="KCF")
# video = cv2.VideoCapture(0)
# video = cv2.VideoCapture("complex1.mov")
 video = cv2.VideoCapture(r"/Users/youxinlin/Desktop/video_data/complex1.MOV") 
 ok, frame = video.read()
 bbox = cv2.selectROI(frame, False)
 tracker.initWorking(frame,bbox)
 while True:
  _,frame = video.read();
  if(_):
   item = tracker.track(frame);
   cv2.imshow("track",item.getFrame())
   k = cv2.waitKey(1) & 0xff
   if k == 27:
    break

附帶items.py，放在同個(gè)文件夾下：

#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Sun Jan 5 17:51:04 2020
@author: youxinlin
"""
import json
from utils import IOUtil
'''
信息封裝類(lèi)
'''
class MessageItem(object):
 #用于封裝信息的類(lèi),包含圖片和其他信息
 def __init__(self,frame,message):
  self._frame = frame
  self._message = message
 def getFrame(self):
  #圖片信息
  return self._frame
 def getMessage(self):
  #文字信息,json格式
  return self._message
 def getBase64Frame(self):
  #返回base64格式的圖片,將BGR圖像轉(zhuǎn)化為RGB圖像
  jepg = IOUtil.array_to_bytes(self._frame[...,::-1])
  return IOUtil.bytes_to_base64(jepg)
 def getBase64FrameByte(self):
  #返回base64格式圖片的bytes
  return bytes(self.getBase64Frame())
 def getJson(self):
  #獲得json數(shù)據(jù)格式
  dicdata = {"frame":self.getBase64Frame().decode(),"message":self.getMessage()}
  return json.dumps(dicdata)
 def getBinaryFrame(self):
  return IOUtil.array_to_bytes(self._frame[...,::-1])

utils.py：也放在同一個(gè)文件夾下。

#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Sun Jan 5 17:51:40 2020
@author: youxinlin
"""
import time
import numpy
import base64
import os
import logging
import sys
from PIL import Image
from io import BytesIO
#工具類(lèi)
class IOUtil(object):
 #流操作工具類(lèi)
 @staticmethod
 def array_to_bytes(pic,formatter="jpeg",quality=70):
  '''
  靜態(tài)方法,將numpy數(shù)組轉(zhuǎn)化二進(jìn)制流
  :param pic: numpy數(shù)組
  :param format: 圖片格式
  :param quality:壓縮比,壓縮比越高,產(chǎn)生的二進(jìn)制數(shù)據(jù)越短
  :return: 
  '''
  stream = BytesIO()
  picture = Image.fromarray(pic)
  picture.save(stream,format=formatter,quality=quality)
  jepg = stream.getvalue()
  stream.close()
  return jepg
 @staticmethod
 def bytes_to_base64(byte):
  '''
  靜態(tài)方法,bytes轉(zhuǎn)base64編碼
  :param byte: 
  :return: 
  '''
  return base64.b64encode(byte)
 @staticmethod
 def transport_rgb(frame):
  '''
  將bgr圖像轉(zhuǎn)化為rgb圖像,或者將rgb圖像轉(zhuǎn)化為bgr圖像
  '''
  return frame[...,::-1]
 @staticmethod
 def byte_to_package(bytes,cmd,var=1):
  '''
  將每一幀的圖片流的二進(jìn)制數(shù)據(jù)進(jìn)行分包
  :param byte: 二進(jìn)制文件
  :param cmd:命令
  :return: 
  '''
  head = [ver,len(byte),cmd]
  headPack = struct.pack("!3I", *head)
  senddata = headPack+byte
  return senddata
 @staticmethod
 def mkdir(filePath):
  '''
  創(chuàng)建文件夾
  '''
  if not os.path.exists(filePath):
   os.mkdir(filePath)
 @staticmethod
 def countCenter(box):
  '''
  計(jì)算一個(gè)矩形的中心
  '''
  return (int(abs(box[0][0] - box[1][0])*0.5) + box[0][0],int(abs(box[0][1] - box[1][1])*0.5) +box[0][1])
 @staticmethod
 def countBox(center):
  '''
  根據(jù)兩個(gè)點(diǎn)計(jì)算出,x,y,c,r
  '''
  return (center[0][0],center[0][1],center[1][0]-center[0][0],center[1][1]-center[0][1])
 @staticmethod
 def getImageFileName():
  return time.strftime("%Y_%m_%d_%H_%M_%S", time.localtime())+'.png'

多目標(biāo)跟蹤：

和單目標(biāo)差不多，改用MultiTracker_create()

#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Sun Jan 5 18:02:33 2020

多目標(biāo)跟蹤

@author: youxinlin
"""import numpy as np
import cv2
import sys
'''
if len(sys.argv) != 2:
 print('Input video name is missing')
 exit()
'''
print('Select multiple tracking targets') 
cv2.namedWindow("tracking")
camera = cv2.VideoCapture(r"/Users/youxinlin/Desktop/video_data/complex6.MOV") 
#camera = cv2.VideoCapture(0)
tracker = cv2.MultiTracker_create() #多目標(biāo)跟蹤
a= cv2.Tracker_c
init_once = False
ok, image=camera.read()
if not ok:
 print('Failed to read video')
 exit()
bbox1 = cv2.selectROI('tracking', image)
bbox2 = cv2.selectROI('tracking', image)
bbox3 = cv2.selectROI('tracking', image)
while camera.isOpened():
 ok, image=camera.read()
 if not ok:
  print ('no image to read')
  break
 if not init_once:
  ok = tracker.add(cv2.TrackerKCF_create(),image,bbox1)
  ok = tracker.add(cv2.TrackerKCF_create( ),image, bbox2)
  ok = tracker.add(cv2.TrackerKCF_create(),image, bbox3)
  init_once = True
 ok, boxes = tracker.update(image)
 for newbox in boxes:
  p1 = (int(newbox[0]), int(newbox[1]))
  p2 = (int(newbox[0] + newbox[2]), int(newbox[1] + newbox[3]))
  cv2.rectangle(image, p1, p2, (0,0,255))
 cv2.imshow('tracking', image)
 k = cv2.waitKey(1)
 if k == 27 : break # esc pressed

多尺度檢測(cè)的KCF、自定義所用特征的KCF

在一些場(chǎng)景下，不想使用默認(rèn)的hog特征跟蹤，或需要對(duì)比不同特征的跟蹤效果，那么封裝好的方法似乎不可用，需要可以自己擼一波kcf的代碼，從而使用自己設(shè)定的特征。

總結(jié)

以上所述是小編給大家介紹的python實(shí)現(xiàn)單目標(biāo)、多目標(biāo)、多尺度、自定義特征的KCF跟蹤算法，希望對(duì)大家有所幫助，如果大家有任何疑問(wèn)請(qǐng)給我留言，小編會(huì)及時(shí)回復(fù)大家的。在此也非常感謝大家對(duì)腳本之家網(wǎng)站的支持！如果你覺(jué)得本文對(duì)你有幫助，歡迎轉(zhuǎn)載，煩請(qǐng)注明出處，謝謝！

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