Object Tracking Using Open CV Python With Source Code
Introduction :
Object tracking in computer vision library is a crucial task . We make it using Open CV , a powerful computer vision library . Through this , object tracking becomes efficient and accessible . It determine the location of object initial frame . Open CV gave several offers to this like colour based tracking , template matching and many more advanced methods like Meanshift , Camshift , etc. This system will firstly detect the object and then track this by moving the object . This system is also used in robotics technology , sports analysis , etc. To make this system , first install packages and then paste the code given below and run the code . After this , you will see the output .
So , Let’s Make .
Language And Interface :-
Object Tracking Using Python , A Versatile Programming Language With Source Code .
Required Modules Or Packages:-
You Need The Packages List Given Below :-
1. cv2 :- It is a library to use in Computer Vision task. You will get basic image processing tools while using cv2 for example, Image Reading and Writing .
How To Run The Code :-
Step 1 . First , You Download and Install Visual Studio Code or VS Code In your PC or Laptop by VS Code Official Website .
Step 2 . Now Open CMD As Administrator and install the above packages using pip .
Step 3 . Now Open Visual Studio Code .
Step 4. Now Make The file named as objecttracking.py .
Step 5 . Now Copy And Paste The Code from the Link Given Below ⬇️
Step 7 . After pasting The code , Save This & Click On Run Button .
Step 8 . Now You will See The Output .
Code Explanation :-
This Python code is used to Tracking Objects from Any Image Files format .
Step-by-Step Guide Given Below:-
Imports :
• cv2 :- It is a library to use in Computer Vision task. You will get basic image processing tools while using cv2 for example, Image Reading and Writing .
Choosing the Tracker :
#tracker = cv2.TrackerBoosting_create()
#tracker = cv2.TrackerMIL_create()
#tracker = cv2.TrackerKCF_create()
#tracker = cv2.TrackerTLD_create()
#tracker = cv2.TrackerMedianFlow_create()
#tracker = cv2.TrackerCSRT_create()
tracker = cv2.TrackerMOSSE_create()
Multiple Trackers are available in Open CV . TrackerMOSSE_create()is a fastest tracking method .
cap = cv2.VideoCapture(1) : This line initialize the video capture from camera .
Drawing the tracking Box :
def drawBox(img, bbox):
x, y, w, h = int(bbox[0]), int(bbox[1]), int(bbox[2]), int(bbox[3])
cv2.rectangle(img, (x, y), ((x + w), (y + h)), (255, 0, 255), 3, 3)
cv2.putText(img, "Tracking", (100, 75), cv2.FONT_HERSHEY_SIMPLEX, 0.7,
(0, 255, 0), 2)
This code draw a rectangle around the detected objects
Tracking success : If the object is detected and tracking , then it draw the rectangle around detected object .
Tracking Failure : If the object is not detected , then this show the text “Lost” .
FPS Calculation :
fps = cv2.getTickFrequency() / (cv2.getTickCount() - timer)
if fps > 60: myColor = (20, 230, 20)
elif fps > 20: myColor = (230, 20, 20)
else: myColor = (20, 20, 230)
cv2.putText(img, str(int(fps)), (75, 40), cv2.FONT_HERSHEY_SIMPLEX, 0.7,
myColor, 2)
This code Calculates the FPS of Objects .
Display Result :
cv2.imshow("Tracking", img)
if cv2.waitKey(1) & 0xff == ord('q'):
break
This code Display the result .
Program Exit :
When The Loop is broken , then the program will exit .
Source Code :-
Output :-
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