Sure! Here is a step-by-step guide to building a person counter using Python and OpenCV:

Step 1: Install OpenCV

Before you start coding, you need to install OpenCV on your system. You can install OpenCV using pip by running the following command in your terminal:

pip install opencv-python

Step 2: Import necessary libraries

Next, you need to import the libraries you'll be using:

import cv2
import numpy as np

Step 3: Load the video file

In this step, you'll load the video file you want to count people in. You can do this using the VideoCapture function in OpenCV:

cap = cv2.VideoCapture('path/to/your/video/file.mp4')


If you're using a webcam, you can use the following instead:


cap = cv2.VideoCapture(0)

Step 4: Create a background subtractor

To count people in a video, you need to detect the presence of people in each frame. One way to do this is by subtracting the background from the current frame. OpenCV provides a BackgroundSubtractorMOG2 class for this purpose:

fgbg = cv2.createBackgroundSubtractorMOG2()


Step 5: Count people in each frame

Now you can loop through each frame in the video, apply the background subtractor, and count the number of people in each frame. Here's the complete code for this step:

while True:
    ret, frame = cap.read()
    if not ret:
        break

    # Apply background subtractor
    fgmask = fgbg.apply(frame)

    # Find contours
    contours, hierarchy = cv2.findContours(fgmask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)

    # Count number of people
    count = 0
    for contour in contours:
        # Ignore small contours
        if cv2.contourArea(contour) < 5000:
            continue

        # Draw bounding box around contour
        (x, y, w, h) = cv2.boundingRect(contour)
        cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 2)

        # Increment count
        count += 1

    # Display count
    cv2.putText(frame, "Count: {}".format(count), (10, 50), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 0, 255), 2)

    # Display frame
    cv2.imshow('frame', frame)

    # Exit if 'q' is pressed
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

Here's what this code does:

It reads each frame from the video using cap.read().
It applies the background subtractor using fgbg.apply(frame).
It finds the contours in the resulting foreground mask using cv2.findContours().
For each contour, it draws a bounding box around it using cv2.rectangle().
It counts the number of people by incrementing a counter variable.
It displays the count on the frame using cv2.putText().
It displays the resulting frame using cv2.imshow().
It exits the loop if the 'q' key is pressed.

Step 6: Release resources

Finally, after you're done counting people, you need to release the video capture and destroy any open windows:

cap.release()
cv2.destroyAllWindows()

And that's about it! let me know if you have any additional questions!
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