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assignment1.py
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import numpy as np
import cv2
from Camera import Camera
VIDEO_SOURCE = 0
class ROI:
def __init__(self,center,size):
x = center[0]
y = center[1]
self.start = (x-size,y-size)
self.end = (x+size,y+size)
def drawBoundary(self,frame):
cv2.rectangle(frame,self.start,self.end,(0,255,0),1)
def getROI(self,frame):
return frame[ self.start[1]:self.end[1] , self.start[0]:self.end[0] ]
class Parameters:
def __init__(self,source=0):
# Selected base color
# fourth one is not used
self.hsv = (0,0,0,0)
self.hsv2 = (0,0,0,0)
self.hsv3 = (0,0,0,0)
# Thresholds
self.ht = 0
self.st = 180
self.vt = 200
self.ht_ = 0
self.st_ = 180
self.vt_ = 200
# Co-ords for the color selection square
# self.start = (0,0)
# self.end = (0,0)
self.center = (0,0)
# Boolean to check weather
# the colors are locked or not
self.locked = False
# Get the camera object
self.cam = Camera(source)
def findCenter(self):
# Read a frame
frame = self.cam.read()
# Calculate the co-ordinates for the center pixel
y = frame.shape[0]/2
x = frame.shape[1]/2
self.center = (x,y)
def threshChanged1(val):
params.ht = val
def threshChanged2(val):
params.st = val
def threshChanged3(val):
params.vt = val
def threshChanged4(val):
params.ht_ = val
def threshChanged5(val):
params.st_ = val
def threshChanged6(val):
params.vt_ = val
params = Parameters(VIDEO_SOURCE)
# get the co-ords for the square in the center
params.findCenter()
# Create an output window
cv2.namedWindow('controls')
# Create trackbars in the output window
cv2.createTrackbar('h+', 'controls',0,179,threshChanged1)
cv2.createTrackbar('s+', 'controls',0,255,threshChanged2)
cv2.createTrackbar('v+', 'controls',0,255,threshChanged3)
cv2.createTrackbar('h-', 'controls',0,179,threshChanged4)
cv2.createTrackbar('s-', 'controls',0,255,threshChanged5)
cv2.createTrackbar('v-', 'controls',0,255,threshChanged6)
# cam = cv2.VideoCapture(VIDEO_SOURCE)
# roihist = None
def getMask(frame,hsv):
lower = np.array([0,0,0], dtype=np.uint8)
upper = np.array([0,0,0], dtype=np.uint8)
lower[0] = hsv[0]-params.ht_
lower[1] = hsv[1]-params.st_
lower[2] = 0
upper[0] = hsv[0]+params.ht
upper[1] = hsv[1]+params.st
upper[2] = 255
return cv2.inRange(frame,lower,upper)
reigon1 = ROI((params.center[0]+16,params.center[1]+16),10)
# reigon2 = ROI((params.center[0]+5,params.center[1]),5)
# reigon3 = ROI((params.center[0]-5,params.center[1]-5),5)
while(True):
# Read a frame from the camera
frame = params.cam.read()
# reigon2.drawBoundary(frame)
# Convert to hsv space
hsv = cv2.cvtColor(frame,cv2.COLOR_BGR2HSV)
# hsv = frame
# # # Blur the image for filtering
cv2.medianBlur(hsv,5)
cv2.GaussianBlur(hsv,(5,5),0)
if not params.locked:
# Calculate average color
params.hsv = cv2.mean(reigon1.getROI(hsv))
# params.hsv2 = cv2.mean(reigon2.getROI(hsv))
# params.hsv3 = cv2.mean(reigon3.getROI(hsv))
mask = getMask(hsv,params.hsv)
# mask = mask + getMask(hsv,params.hsv2)
# mask = mask + getMask(hsv,params.hsv3)
disc = cv2.getStructuringElement(cv2.MORPH_ELLIPSE,(7,7))
cv2.filter2D(mask,-1,disc,mask)
cv2.imshow('mask1',mask)
# cv2.imshow('mask2',mask2)
# cv2.imshow('mask3',mask3)
reigon1.drawBoundary(frame)
# reigon2.drawBoundary(frame)
# reigon3.drawBoundary(frame)
# cv2.imshow('original',frame)
_,contours,_ = cv2.findContours(mask,cv2.RETR_TREE,cv2.CHAIN_APPROX_NONE)
# get the contour with the greatest area
max_area = -1
ci = -1
for i in range(len(contours)):
cnt=contours[i]
area = cv2.contourArea(cnt)
if(area>max_area):
max_area=area
ci=i
if(ci != -1):
cnt=contours[ci]
# cv2.imshow('mask',mask)
# # Draw a rectangle in the center
# frame = cv2.rectangle(frame,params.start,params.end,(0,255,0),1)
if(ci != -1):
# Find and draw the hull around the largest contour
hull = cv2.convexHull(cnt)
cv2.drawContours(frame,[hull],0,(0,255,0),2)
cv2.imshow('image',frame)
k = cv2.waitKey(5) & 0xFF
if k == 27:
break
elif k == ord('l'):
print 'locked'
params.locked = True
elif k == ord('u'):
print 'un-locked'
params.locked = False
elif k == ord('c'):
print 'mask captured'
cv2.imwrite('mask.png',mask)
params.cam.stop()
cv2.destroyAllWindows()