提起目标跟踪，大家可能会想起的就是camshift，但是camshift跟踪往往达不到我们的跟踪要求，包括稳定性和准确性。
opencv3.1版本发行后，集成了多个跟踪算法，但需要扩展模块，即tracker，大部分都是近年VOT竞赛榜上有名的算法，虽然仍有缺陷存在，但效果还不错。
下面我提供C++ 版本和python版本，大家自行测试
#include <opencv2/opencv.hpp>
#include <opencv2/video.hpp>
#include <opencv2/tracking.hpp>
#include <opencv2/tracking/tracker.hpp>
using namespace cv;
void draw_rectangle(int event, int x, int y, int flags, void*);
Mat firstFrame;
Point previousPoint, currentPoint;
Rect2d bbox;
int main(int argc, char *argv[])
{
VideoCapture capture;
Mat frame;
//frame = capture.open("/home/xiaorun/moving-object-detection/1.mp4");
frame=capture.open(0);
if(!capture.isOpened())
{
printf("can not open ...\n");
return -1;
}
//获取视频的第一帧,并框选目标
capture.read(firstFrame);
if(!firstFrame.empty())
{
namedWindow("output", WINDOW_AUTOSIZE);
imshow("output", firstFrame);
setMouseCallback("output", draw_rectangle, 0);
waitKey();
}
//使用TrackerMIL跟踪
//Ptr<TrackerMIL> tracker= TrackerMIL::create();
//Ptr<TrackerTLD> tracker= TrackerTLD::create();
// Ptr<TrackerKCF> tracker = TrackerKCF::create();
// Ptr<TrackerMedianFlow> tracker = TrackerMedianFlow::create();
Ptr<TrackerBoosting> tracker= TrackerBoosting::create();
capture.read(frame);
tracker->init(frame,bbox);
namedWindow("output", WINDOW_AUTOSIZE);
while (capture.read(frame))
{
tracker->update(frame,bbox);
rectangle(frame,bbox, Scalar(255, 0, 0), 2, 1);
imshow("output", frame);
if(waitKey(20)=='q')
return 0;
}
capture.release();
destroyWindow("output");
return 0;
}
//框选目标
void draw_rectangle(int event, int x, int y, int flags, void*)
{
if (event == EVENT_LBUTTONDOWN)
{
previousPoint = Point(x, y);
}
else if (event == EVENT_MOUSEMOVE && (flags&EVENT_FLAG_LBUTTON))
{
Mat tmp;
firstFrame.copyTo(tmp);
currentPoint = Point(x, y);
rectangle(tmp, previousPoint, currentPoint, Scalar(0, 255, 0, 0), 1, 8, 0);
imshow("output", tmp);
}
else if (event == EVENT_LBUTTONUP)
{
bbox.x = previousPoint.x;
bbox.y = previousPoint.y;
bbox.width = abs(previousPoint.x-currentPoint.x);
bbox.height = abs(previousPoint.y-currentPoint.y);
}
else if (event == EVENT_RBUTTONUP)
{
destroyWindow("output");
}
}python版本测试
import cv2
import sys
(major_ver, minor_ver, subminor_ver) = (cv2.__version__).split('.')
if __name__ == '__main__' :
# Set up tracker.
# Instead of MIL, you can also use
tracker_types = ['BOOSTING', 'MIL','KCF', 'TLD', 'MEDIANFLOW', 'GOTURN', 'MOSSE']
tracker_type = tracker_types[2]
if int(minor_ver) < 3:
tracker = cv2.Tracker_create(tracker_type)
else:
if tracker_type == 'BOOSTING':
tracker = cv2.TrackerBoosting_create()
if tracker_type == 'MIL':
tracker = cv2.TrackerMIL_create()
if tracker_type == 'KCF':
tracker = cv2.TrackerKCF_create()
if tracker_type == 'TLD':
tracker = cv2.TrackerTLD_create()
if tracker_type == 'MEDIANFLOW':
tracker = cv2.TrackerMedianFlow_create()
if tracker_type == 'GOTURN':
tracker = cv2.TrackerGOTURN_create()
if tracker_type == 'MOSSE':
tracker = cv2.TrackerMOSSE_create()
# Read video
video = cv2.VideoCapture("videos/chaplin.mp4")
# Exit if video not opened.
if not video.isOpened():
print "Could not open video"
sys.exit()
# Read first frame.
ok, frame = video.read()
if not ok:
print 'Cannot read video file'
sys.exit()
# Define an initial bounding box
bbox = (287, 23, 86, 320)
# Uncomment the line below to select a different bounding box
bbox = cv2.selectROI(frame, False)
# Initialize tracker with first frame and bounding box
ok = tracker.init(frame, bbox)
while True:
# Read a new frame
ok, frame = video.read()
if not ok:
break
# Start timer
timer = cv2.getTickCount()
# Update tracker
ok, bbox = tracker.update(frame)
# Calculate Frames per second (FPS)
fps = cv2.getTickFrequency() / (cv2.getTickCount() - timer);
# Draw bounding box
if ok:
# Tracking success
p1 = (int(bbox[0]), int(bbox[1]))
p2 = (int(bbox[0] + bbox[2]), int(bbox[1] + bbox[3]))
cv2.rectangle(frame, p1, p2, (255,0,0), 2, 1)
else :
# Tracking failure
cv2.putText(frame, "Tracking failure detected", (100,80), cv2.FONT_HERSHEY_SIMPLEX, 0.75,(0,0,255),2)
# Display tracker type on frame
cv2.putText(frame, tracker_type + " Tracker", (100,20), cv2.FONT_HERSHEY_SIMPLEX, 0.75, (50,170,50),2);
# Display FPS on frame
cv2.putText(frame, "FPS : " + str(int(fps)), (100,50), cv2.FONT_HERSHEY_SIMPLEX, 0.75, (50,170,50), 2);
# Display result
cv2.imshow("Tracking", frame)
# Exit if ESC pressed
k = cv2.waitKey(1) & 0xff
if k == 27 : break多目标追踪
多目标跟踪使用的是MultiTracker，如MultiTracker myTracker(“KCF”)，注意两点，添加目标用其成员函数myTracker.add(Mat src, Rect2d roi)，获得跟踪结果使用myTracker.update(Mat src, vector targets)，跟踪结果的序号即vector的序号。
import numpy as np
import cv2
import sys
'''
if len(sys.argv) != 2:
print('Input video name is missing')
exit()
'''
print('Select 3 tracking targets')
cv2.namedWindow("tracking")
camera = cv2.VideoCapture(0)
tracker = cv2.MultiTracker_create()
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.TrackerMIL_create(), image, bbox1)
ok = tracker.add(cv2.TrackerMIL_create(), image, bbox2)
ok = tracker.add(cv2.TrackerMIL_create(), image, bbox3)
init_once = True
ok, boxes = tracker.update(image)
print ok, boxes
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, (200,0,0))
cv2.imshow('tracking', image)
k = cv2.waitKey(1)
if k == 27 : break # esc pressed