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powercells.py
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powercells.py
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# import the necessary packages
from collections import deque
import numpy as np
import cv2
# lower and upper boundaries of the "yellow" in HSV
yellowLower = (20, 100, 100)
yellowUpper = (30, 255, 255)
# use the webcam
camera = cv2.VideoCapture(0)
# otherwise, grab a reference to the video file
# infinite loop
while True:
# grab the current frame -- propriedades
(grabbed, frame) = camera.read()
# resize the frame, blur
# it, and convert it to the HSV color space
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, yellowLower, yellowUpper)
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 = None
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
NBolas = 3
c = []
listaDeContornos = [((0, 0), 0),
((0, 0), 0),
((0, 0), 0)]
center = []
maximo = 0
for countour in range(NBolas):
bolas_suficientes = True
try:
maximo = max(cnts, key=cv2.contourArea)
except:
bolas_suficientes = False
if countour>0:
print("Há apenas {} bolas".format(countour))
else:
print("Não há bolas")
if(bolas_suficientes):
c.append(maximo)
listaDeContornos[countour]=(cv2.minEnclosingCircle(maximo))
m = cv2.moments(maximo)
center.append((int(m["m10"] / m["m00"]), int(m["m01"] / m["m00"])))
try:
cnts.remove(maximo)
if countour==2:
print("Deu tudo certo")
except:
print("ops, este é o", countour )
# only proceed if the radius meets a minimum size
i=0
for contorno in listaDeContornos:
radius = contorno[1]
x = contorno[0][0]
y = contorno[0][1]
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[i], 5, (0, 0, 255), -1)
i+=1
# show the frame to our screen
cv2.imshow("Frame", frame)
# cv2.imshow("Frame", mask)
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()