VirtualPen.py

#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon Jun 29 17:19:27 2020

@author: shoumik
"""


# import the necessary packages
from color_labeler import ColorLabeler
from collections import deque
from imutils.video import VideoStream
import numpy as np
import argparse
import cv2
import imutils
import time

# construct the 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=1024,
    help="max buffer size")
args = vars(ap.parse_args())

# define the lower and upper boundaries of the color
# ball in the HSV color space, then initialize the
# list of tracked points

greenLower = (63, 114, 120)
greenUpper = (100, 255, 255)
# define the lower and upper boundaries of the colors in HSV color space
blueLower = (69, 165, 169)
blueUpper = (134, 243, 255)

greenLower = (63, 114, 120)
greenUpper = (100, 255, 255)

redLower = (121, 190, 91)
redUpper = (206, 255, 255)

r = (0, 0, 255)
g = (0, 255, 0)
b = (255, 0, 0)
x1, y1 = 0, 0

thickness = 4
cl = ColorLabeler()
canvas = None

pts = deque(maxlen=args["buffer"])

# if a video path was not supplied, grab the reference
# to the webcam
if not args.get("video", False):
    vs = VideoStream(src=0).start()

# otherwise, grab a reference to the video file
else:
    vs = cv2.VideoCapture(args["video"])

# allow the camera or video file to warm up
time.sleep(2.0)

# keep looping
while True:
    # grab the current frame
    frame = vs.read()
    frame = cv2.flip(frame, 1)

    # handle the frame from VideoCapture or VideoStream
    frame = frame[1] if args.get("video", False) else frame

    # if we are viewing a video and we did not grab a frame,
    # then we have reached the end of the video
    if frame is None:
        break

    # resize the frame, blur it, and convert it to the HSV
    # color space
    frame = imutils.resize(frame, width=600)
    blurred = cv2.GaussianBlur(frame, (11, 11), 0)
    hsv = cv2.cvtColor(blurred, cv2.COLOR_BGR2HSV)

    # construct a mask for the color "green", then perform
    # a series of dilations and erosions to remove any small
    # blobs left in the mask
    mask = cv2.inRange(hsv, greenLower, greenUpper)
    mask = cv2.erode(mask, None, iterations=2)
    mask = cv2.dilate(mask, None, iterations=2)

    # find contours in the mask and initialize the current
    # (x, y) center of the ball
    cnts = cv2.findContours(mask.copy(), cv2.RETR_EXTERNAL,
        cv2.CHAIN_APPROX_SIMPLE)
    cnts = imutils.grab_contours(cnts)
    center = None

    # only proceed if at least one contour was found
    if len(cnts) > 0:
          # find the largest contour in the mask, then use
          # it to compute the minimum enclosing circle and
          # centroid
        c = max(cnts, key=cv2.contourArea)
        ((x, y), radius) = cv2.minEnclosingCircle(c)
        area = cv2.contourArea(c)
        M=cv2.moments(c)
        center = (int(M["m10"] / M["m00"]), int(M["m01"] / M["m00"]))

    # update the points queue
    pts.appendleft(center)

    # loop over the set of tracked points
    for i in range(1, len(pts)):
        # if either of the tracked points are None, ignore
        # them
        if pts[i - 1] is None or pts[i] is None:
            continue

        # otherwise, compute the thickness of the line and
        # draw the connecting lines
        thickness = int(np.sqrt(args["buffer"] / float(i + 1)) * 2.5)
        cv2.line(frame, pts[i - 1], pts[i], (0, 0, 255), thickness)
            
    
    # show the frame to our screen
    cv2.imshow("My Virtual Pen", frame)
    key = cv2.waitKey(1) & 0xFF

    # if the 'q' key is pressed, stop the loop
    if key == ord("q"):
        break
# if we are not using a video file, stop the camera video stream
if not args.get("video", False):
    vs.stop()

# otherwise, release the camera
else:
    vs.release()

# close all windows
cv2.destroyAllWindows()