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import cv2 | |
import numpy as np | |
import time | |
cap = cv2.VideoCapture(0) | |
time.sleep(3) | |
background=0 | |
#Memorizamos el fondo antes de comenzar | |
for i in range(30): | |
ret,background = cap.read() | |
background = np.flip(background,axis=1) | |
while(cap.isOpened()): | |
ret, img = cap.read() | |
img = np.flip(img,axis=1) | |
#Convertimos la imagen a HSV para su saturación | |
hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV) | |
value = (35, 35) | |
blurred = cv2.GaussianBlur(hsv, value,0) | |
# Definimos el rango inferior del color que queremos saturar | |
# Recordar que son los valores en HSV | |
lower_color = np.array([0,120,70]) | |
upper_color = np.array([10,255,255]) | |
mask1 = cv2.inRange(hsv,lower_color,upper_color) | |
# Definimos el rango superior del color que queremos saturar | |
lower_color = np.array([170,120,70]) | |
upper_color = np.array([180,255,255]) | |
mask2 = cv2.inRange(hsv,lower_color,upper_color) | |
# Sumamos ambas mascaras | |
mask = mask1+mask2 | |
mask = cv2.morphologyEx(mask, cv2.MORPH_OPEN, np.ones((5,5),np.uint8)) | |
# Remplazamos los pixeles del color saturado con los del fondo anteriormente guardado | |
img[np.where(mask==255)] = background[np.where(mask==255)] | |
cv2.imshow('Display',img) | |
if cv2.waitKey(10)==27: | |
break | |
#Thanks Kaustubh Sadekar |
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