Tracks.py

import cv2
from tracker import *

# Create tracker object
tracker = EuclideanDistTracker()
cap = cv2.VideoCapture(r"C:\Users\End User\PycharmProjects\cloudchamber\video\first one min.mp4")

# Object detection from Stable camera
object_detector = cv2.createBackgroundSubtractorMOG2(history=100, varThreshold=40)

while True:
    ret, frame = cap.read()
    height, width, _ = frame.shape

    # Extract Region of interest
    roi = frame[280: 1580, 560: 1720]

    # 1. Object Detection
    mask = object_detector.apply(roi)
    _, mask = cv2.threshold(mask, 254, 255, cv2.THRESH_BINARY)
    contours, _ = cv2.findContours(mask, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
    detections = []
    for cnt in contours:
        # Calculate area and remove small elements
        area = cv2.contourArea(cnt)
        if area > 100:
            # cv2.drawContours ( roi , [ cnt ] , -1 , ( 0 , 255 , 0 ) , 2 )
            x, y, w, h = cv2.boundingRect(cnt)
            cv2.rectangle(roi, (x, y), (x + w, y + h), (0, 255, 0), 3)
            print(x, y, w, h)

            detections.append([x, y, w, h])


    # 2.Object Tracking

    boxes_ids = tracker.update(detections)
    print(boxes_ids)
    for box_id in boxes_ids:
        X, Y, W, h, id = box_id
        #cv2.putText(roi, str(id), (x, y - 15), cv2.FONT_HERSHEY_PLAIN, 4, (255, 0, 0), 4)
        cv2.putText(roi, str('particles'), (x, y - 15), cv2.FONT_HERSHEY_PLAIN, 2, (255, 0, 0), 4)
        # cv2.putText(roi, str('muon'), (x, y - 25), cv2.FONT_HERSHEY_PLAIN, 2, (255, 0, 0), 4)
        # cv2.putText(roi, str('electron'), (x, y - 35), cv2.FONT_HERSHEY_PLAIN, 3, (255, 0, 0), 4)
        # cv2.putText(roi, str('photoelectron'), (x, y - 45), cv2.FONT_HERSHEY_PLAIN, 4, (255, 0, 0), 4)
        cv2.rectangle(roi, (x, y), (x + W, y + h), (0, 255, 0), 3)


    cv2.imshow(" roi ", roi)
    cv2.imshow(" Frame ", frame)
    cv2.imshow(" Mask ", mask)

    key = cv2.waitKey(30)
    if key == 27:
        break

cap.release()
cv2.destroyAllWindows()