How to convert opencv functions to mexopencv functions useable in matlab? - matlab

Question

My Problem:
I want to use functions of opencv like the MIL-Tracker or MedianFlow-Tracker in Matlab (these functions are not in mexopencv). But I don't know how or understand how to do this. The documentation of opencv/mexopencv doesn't help me. This doesn't help: how do OpenCV shared libraries in matlab? - because the link in the answer is down.
So is there a way to use these functions in Matlab? And if- How?
Why?: As a part of my bachelor thesis I have to compare different already implemented ways to track people.

Answer 1

If you would like to use these functions specifically in MATLAB you could always write your own MEX file in C/C++ and send the data back/forward between the two calls, however this would require some basic C++ knowledge and understanding creating MEX files.
Personally I would definately recommend trying this with Python and the OpenCV Python interface since its so widely used and more supported than using the calls in MATLAB (plus its always a useful skill to be able to switch between Python and MATLAB as and when needed).
There is a full example with the MIL-Tracker and the MedianFlow-Tracker (and others) here (Which demonstrates using them in C++ and Python!).
Python Example :
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']
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()
# 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
I would definately try it using Python (if this is an option). Otherwise if MATLAB is a must then probably try implementing the C++ example code shown in the link before as a MEX file and linking openCV during the compilation i.e.
mex trackerMexOpenCV.cpp 'true filepath location to openCV lib'
I hope this helps!