search ROI in opencv
:
Consider (0,0) as the top-left corner of the image with left-to-right as the x-direction and top-to-bottom as the y-direction. If we have (x1,y1) as the top-left and (x2,y2) as the bottom-right vertex of a ROI, we can use Numpy slicing to crop the image with:
ROI = image[y1:y2, x1:x2]
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see this python example code:
# Python 2/3 compatibility
from __future__ import print_function
# Allows use of print like a function in Python 2.x
# Import OpenCV and Numpy modules
import numpy as np
import cv2
try:
# Create a named window to display video output
cv2.namedWindow('Watermark', cv2.WINDOW_NORMAL)
# Load logo image
dog = cv2.imread('Intel_Logo.png')
#
rows,cols,channels = dog.shape
# Convert the logo to grayscale
dog_gray = cv2.cvtColor(dog,cv2.COLOR_BGR2GRAY)
# Create a mask of the logo and its inverse mask
ret, mask = cv2.threshold(dog_gray, 10, 255, cv2.THRESH_BINARY)
mask_inv = cv2.bitwise_not(mask)
# Now just extract the logo
dog_fg = cv2.bitwise_and(dog,dog,mask = mask)
# Initialize Default Video Web Camera for capture.
webcam = cv2.VideoCapture(0)
# Check if Camera initialized correctly
success = webcam.isOpened()
if success == False:
print('Error: Camera could not be opened')
else:
print('Sucess: Grabbing the camera')
webcam.set(cv2.CAP_PROP_FPS,30);
webcam.set(cv2.CAP_PROP_FRAME_WIDTH,1024);
webcam.set(cv2.CAP_PROP_FRAME_HEIGHT,768);
while(True):
# Read each frame in video stream
ret, frame = webcam.read()
# Perform operations on the video frames here
# To put logo on top-left corner, create a Region of Interest (ROI)
roi = frame[0:rows, 0:cols ]
# Now blackout the area of logo in ROI
frm_bg = cv2.bitwise_and(roi,roi,mask = mask_inv)
# Next add the logo to each video frame
dst = cv2.add(frm_bg,dog_fg)
frame[0:rows, 0:cols ] = dst
# Overlay Text on the video frame with Exit instructions
font = cv2.FONT_HERSHEY_SIMPLEX
cv2.putText(frame, "Type q to Quit:",(50,700), font, 1,(255,255,255),2,cv2.LINE_AA)
# Display the resulting frame
# Display the resulting frame
cv2.imshow('Watermark',frame)
# Wait for exit key "q" to quit
if cv2.waitKey(1) & 0xFF == ord('q'):
break
# Release all resources used
webcam.release()
cv2.destroyAllWindows()
except cv2.error as e:
print('Please correct OpenCV Error')