import cv2

import numpy as np

cap = cv2.VideoCapture(0)

#Noise is fluctuating. Maybe take a couple frames (3 or 4)

#Threshold For being in 2/3 of them.

copies = 4

N=1 #Downsamples

_, frame = cap.read()

_, frame = cap.read()

gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)

for i in range(N):

gray = cv2.pyrDown(gray)

mybuffer = np.zeros((gray.shape[0],gray.shape[1],copies)

for i in range(copies):

_, frame = cap.read()

gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)

for i in range(N):

gray = cv2.pyrDown(gray)

mybuffer[:,:,i] = gray

currentindex = 0

while(1):

# Take each frame

_, frame = cap.read()

gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)

N=1

for i in range(N):

gray = cv2.pyrDown(gray)

#gray = cv2.pyrDown(gray)

#gray = cv2.adaptiveThreshold(gray,255,cv2.ADAPTIVE_THRESH_GAUSSIAN_C,cv2.THRESH_BINARY,51,0)

kernel = np.ones((2,2),np.uint8)

#erosion = cv2.erode(gray,kernel,iterations = 1)

#blur = cv2.GaussianBlur(gray,(11,11),0)

thres = cv2.adaptiveThreshold(gray,255,cv2.ADAPTIVE_THRESH_GAUSSIAN_C,cv2.THRESH_BINARY,15,2)

#ret3,th3 = cv2.threshold(blur,0,255,cv2.THRESH_BINARY+cv2.THRESH_OTSU)

closing = cv2.morphologyEx(thres, cv2.MORPH_CLOSE, kernel)

opening = cv2.morphologyEx(closing, cv2.MORPH_OPEN, kernel)

#closing = cv2.morphologyEx(opening, cv2.MORPH_CLOSE, kernel)

edges = cv2.Canny(closing,100,200)

#edges = cv2.cornerHarris(gray, 5)

#ret,thresh = cv2.threshold(gray,50,255,cv2.THRESH_BINARY)

empty = np.zeros(frame.shape, dtype=np.uint8)

#kernel = np.ones((5,5),np.uint8)

#edges = cv2.dilate(edges,kernel,iterations = 2) # really chunks it up

#contours,hierarchy= cv2.findContours(closing,cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)

#cv2.drawContours(empty, contours, -1, (0,0,255), 1)

#cv2.imshow('res',cv2.pyrDown(empty))

show = closing

for i in range(N-1):

show = cv2.pyrUp(show)

cv2.imshow('gray',gray)

cv2.imshow('gld',show)

#cv2.imshow('contours',empty)

#cv2.imshow('res',cv2.pyrDown(edges))

k = cv2.waitKey(5) & 0xFF

if k == 27:

break

cv2.destroyAllWindows()