kinect.py

# USAGE
# python object_movement.py --video object_tracking_example.mp4
# python object_movement.py

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

from pynput.keyboard import Key, Controller

print("Imported packages, ashwin")

# 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=32,
	help="max buffer size")
args = vars(ap.parse_args())

keyboard = Controller()

print("Controller set")

# define the lower and upper boundaries of the "green"
# ball in the HSV color space
redLower = (160,20,70)
redUpper = (190,255,255)

# initialize the list of tracked points, the frame counter,
# and the coordinate deltas
pts = deque(maxlen=args["buffer"])
counter = 0
(dX, dY) = (0, 0)
direction = ""

# 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"])

print("All ok video capture started!")

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

# keep looping
while True:
	# grab the current frame
	frame = vs.read()
	# 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, redLower, redUpper)
	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)
		M = cv2.moments(c)
		center = (int(M["m10"] / M["m00"]), int(M["m01"] / M["m00"]))

		# only proceed if the radius meets a minimum size
		if radius > 10:
			# draw the circle and centroid on the frame,
			# then update the list of tracked points
			cv2.circle(frame, (int(x), int(y)), int(radius),
				(0, 255, 255), 2)
			cv2.circle(frame, center, 5, (0, 0, 255), -1)
			pts.appendleft(center)

	# loop over the set of tracked points
	for i in np.arange(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

		# check to see if enough points have been accumulated in
		# the buffer
		if counter >= 10 and i == 1 and pts[-10] is not None:
			# compute the difference between the x and y
			# coordinates and re-initialize the direction
			# text variables
			dX = pts[-10][0] - pts[i][0]
			dY = pts[-10][1] - pts[i][1]
			(dirX, dirY) = ("", "")

			# ensure there is significant movement in the
			# x-direction
			if np.abs(dX) > 30:

				keyboard.press(Key.right) if np.sign(dX) == 1 else keyboard.press(Key.left)
				keyboard.release(Key.right) if np.sign(dX) == 1 else keyboard.release(Key.left)
				
				dirX = "East" if np.sign(dX) == 1 else "West"

			# ensure there is significant movement in the
			# y-direction
			if np.abs(dY) > 30:
				keyboard.press(Key.down) if np.sign(dX) == 1 else keyboard.press(Key.up)
				keyboard.release(Key.down) if np.sign(dX) == 1 else keyboard.release(Key.up)
				dirY = "North" if np.sign(dY) == 1 else "South"

			# handle when both directions are non-empty
			if dirX != "" and dirY != "":
				direction = "{}-{}".format(dirY, dirX)

			# otherwise, only one direction is non-empty
			else:
				direction = dirX if dirX != "" else dirY

		# 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 movement deltas and the direction of movement on
	# the frame
	cv2.putText(frame, direction, (10, 30), cv2.FONT_HERSHEY_SIMPLEX,
		0.65, (0, 0, 255), 3)
	cv2.putText(frame, "dx: {}, dy: {}".format(dX, dY),
		(10, frame.shape[0] - 10), cv2.FONT_HERSHEY_SIMPLEX,
		0.35, (0, 0, 255), 1)

	# show the frame to our screen and increment the frame counter
	cv2.imshow("Frame", frame)
	key = cv2.waitKey(1) & 0xFF
	counter += 1

	# if the 'q' key is pressed, stop the loop
	if key == ord("q"):
		print("You quit on me !")
		break

# if we are not using a video file, stop the camera video stream
if not args.get("video", False):
	vs.stop()
	print("I Didn't get any camera ashwin")

# otherwise, release the camera
else:
	vs.release()
	print("Bye ashwin")

# close all windows
cv2.destroyAllWindows()