purplependulum.py

from collections import deque
from imutils.video import VideoStream
import numpy as np
import argparse
import cv2 as cv
import imutils
import time
from threading import Thread
from playsound import playsound

# Constants
RIGHT_CENTER_X_THRESHOLD = 280  # Adjust this value based on your video frame width
LEFT_CENTER_X_THRESHOLD = 320
DIST_THRESHOLD = 100  # Threshold for distance comparison

def play_sound():
    playsound('Piano_C3.mp3')

# Construct argument parse and parse the arguments
ap = argparse.ArgumentParser()
ap.add_argument("-v", "--video", help="path to the (optional) video file")
ap.add_argument("-b", "--buffer", type=int, default=64, help="max buffer size")
args = vars(ap.parse_args())

# Lower and upper boundaries of the "purple" color in HSV color space
purpleLower = (140, 50, 50)
purpleUpper = (160, 255, 255)
pts = deque(maxlen=args["buffer"])

# Video path not supplied, grab reference to Webcam
if not args.get("video", False):
    vs = VideoStream(src=0).start()
else:
    vs = cv.VideoCapture(args["video"])

while True:
    frame = vs.read()  # Grab current frame
    frame = frame[1] if args.get("video", False) else frame  # Handle frame from VideoCapture or VideoStream

    # Video ended or no frame received
    if frame is None:
        break

    # Resize frame, blur it, and convert it to HSV
    frame = imutils.resize(frame, width=600)
    blurred = cv.GaussianBlur(frame, (11, 11), 0)
    hsv = cv.cvtColor(blurred, cv.COLOR_BGR2HSV)

    # Construct a mask for purple color, perform dilations and erosions to remove blobs
    mask = cv.inRange(hsv, purpleLower, purpleUpper)
    mask = cv.erode(mask, None, iterations=2)
    mask = cv.dilate(mask, None, iterations=2)

    # Find contours in the mask and initialize the current (x, y) center of the ball
    cnts = cv.findContours(mask.copy(), cv.RETR_EXTERNAL, cv.CHAIN_APPROX_SIMPLE)
    cnts = imutils.grab_contours(cnts)
    center = None

    # Proceed when a contour is found
    if len(cnts) > 0:
        c = max(cnts, key=cv.contourArea)  # Find the largest contour in the mask
        ((x, y), radius) = cv.minEnclosingCircle(c)  # Compute the minimum enclosing circle
        M = cv.moments(c)
        if M["m00"] != 0:
            center = (int(M["m10"] / M["m00"]), int(M["m01"] / M["m00"]))  # Centroid

            if radius > 10:
                cv.circle(frame, (int(x), int(y)), int(radius), (0, 255, 255), 2)
                cv.circle(frame, center, 5, (0, 0, 255), -1)

                if center is not None:
                    frame_width = frame.shape[1]
                    middle_x = frame_width // 2
                    if center[0] > middle_x - RIGHT_CENTER_X_THRESHOLD and center[0] < middle_x + LEFT_CENTER_X_THRESHOLD:
                        sound_thread = Thread(target=play_sound)
                        sound_thread.start()

    pts.appendleft(center)

    for i in range(1, len(pts)):
        if pts[i - 1] is None or pts[i] is None:
            continue

        thickness = int(np.sqrt(args["buffer"] / float(i + 1)) * 2.5)
        cv.line(frame, pts[i - 1], pts[i], (0, 0, 255), thickness)

    cv.imshow("Frame", frame)
    key = cv.waitKey(1) & 0xFF

    if key == ord("q"):
        break

if not args.get("video", False):
    vs.stop()
else:
    vs.release()

cv.destroyAllWindows()