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colors.py
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colors.py
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#python color_tracking.py --video balls.mp5
#python color_tracking.py
# import the necessary packages
from collections import deque
import numpy as np
import argparse
import imutils
import cv2
import urllib #for reading image from URL
import os
import math
import time
from picamera.array import PiRGBArray
from picamera import PiCamera
import io
#from espeak import espeak
def checkdist(x1,y1,r1,x2,y2,r2):
d = math.sqrt(((x1-x2)**2)+((y1-y2)**2))
if d <= r1+r2:
return 1
else:
return 0
p = 0
# 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=64,
help="max buffer size")
args = vars(ap.parse_args())
# define the lower and upper boundaries of the colors in the HSV color space (66, 122, 129)
lower = {'red':(166, 84, 141), 'green':(66, 50, 129), 'blue':(97, 100, 117)} #assign new item lower['blue'] = (93, 10, 0)
upper = {'red':(186,255,255), 'green':(86,255,255), 'blue':(117,255,255)}
# define standard colors for circle around the object
colors = {'red':(0,0,255), 'green':(0,255,0), 'blue':(255,0,0)}
#pts = deque(maxlen=args["buffer"])
# if a video path was not supplied, grab the reference
# to the webcam
#if not args.get("video", False):
#camera = cv2.VideoCapture(0)
camera = PiCamera()
camera.resolution= (640, 480)
camera.framerate = 32
rawCapture = PiRGBArray(camera, size=(640, 480))
time.sleep(0.1)
# otherwise, grab a reference to the video file
#else:
#camera = cv2.VideoCapture(args["video"])
# keep looping
for fr in camera.capture_continuous(rawCapture, format="bgr", use_video_port=True):
frame = np.asarray(fr.array)
rawCapture.truncate()
rawCapture.seek(0)
#os.system("espeak no")
#espeak.synth("no")
# grab the current frame
#(grabbed, frame) = camera.read()
# if we are viewing a video and we did not grab a frame,
# then we have reached the end of the video
if args.get("video") and not grabbed:
break
#IP webcam image stream
#URL = 'http://10.254.254.102:8080/shot.jpg'
#urllib.urlretrieve(URL, 'shot1.jpg')
#frame = cv2.imread('shot1.jpg')
# 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)
#for each color in dictionary check object in frame
radiuses = []
centers = []
count = 0
for key, value in upper.items():
# construct a mask for the color from dictionary`1, then perform
# a series of dilations and erosions to remove any small
# blobs left in the mask
kernel = np.ones((9,9),np.uint8)
mask = cv2.inRange(hsv, lower[key], upper[key])
mask = cv2.morphologyEx(mask, cv2.MORPH_OPEN, kernel)
mask = cv2.morphologyEx(mask, cv2.MORPH_CLOSE, kernel)
# 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)[-2]
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. Correct this value for your obect's size
if radius > 0.3:
# draw the circle and centroid on the frame,
# then update the list of tracked points
cv2.circle(frame, (int(x), int(y)), int(radius), colors[key], 2)
cv2.putText(frame,key + " ball", (int(x-radius),int(y-radius)), cv2.FONT_HERSHEY_SIMPLEX, 0.6,colors[key],2)
radiuses.append(radius)
centers.append(x)
centers.append(y)
count += 1
if count >= 3:
if checkdist(centers[0],centers[1], radiuses[0],centers[2],centers[3], radiuses[1]) and checkdist(centers[0],centers[1], radiuses[0],centers[4],centers[5], radiuses[2]):
p += 1
print(p)
#else:
#os.system("espeak no")
# show the frame to our screen
cv2.imshow("Frame", frame)
key = cv2.waitKey(1) & 0xFF
# if the 'q' key is pressed, stop the loop
if key == ord("q"):
break
# cleanup the camera and close any open windows
camera.release()
cv2.destroyAllWindows()