Develop Reference

How do I add an image overlay to my live video using cv2?

This is my code, I've looked at some tutorials but can't find what I'm looking for
I want to overlay the Frame.png image on my webcam. I tried to add the image directly but it didn't work either. If possible, Is there a way to add an image, not to overlay but to keep the image at a certain coordinate in the live webcam window
import cv2
import numpy as np
def detect_and_save():
alpha = 0.2
beta = 1-alpha
cap = cv2.VideoCapture(0)
sciframe = cv2.imread('Frame.png')
classifier = cv2.CascadeClassifier("haarcascade_frontalface_default.xml")
while True:
ret ,frame = cap.read()
overlay = frame.copy()
output = frame.copy()
gray = cv2.cvtColor(frame,cv2.COLOR_BGR2GRAY)
faces = classifier.detectMultiScale(gray,1.5,5)
cv2.putText(output, "HUD Test",(175, 50), cv2.FONT_HERSHEY_SIMPLEX, 2, (255, 50, 50), 3)
cv2
for face in faces:
x,y,w,h = face
cv2.rectangle(overlay,(x,y),(x+w,y+h),(255,200,0),-1)
cv2.rectangle(overlay,(x,y),(x+w,y+h),(255,0,0),1)
cv2.rectangle(overlay,(x,y-20),(x+w,y),(25,20,0),-1)
cv2.addWeighted(overlay,alpha,output,beta,0,output)
cv2.putText(output,"Human",(x+10,y-10),cv2.FONT_HERSHEY_SIMPLEX,
0.35, (0, 0, 255), 1)
if not ret:
continue
cv2.imshow("HUD",output)
key = cv2.waitKey(1)
if key == ord('q'):
break
elif key == ord('s'):
cv2.imwrite('./images/CID_{}.png'.format(time.strftime('%d%m%y_%H_%M_%S')),output)
cap.release()
cv2.destroyAllWindows()
if __name__ == "__main__":
import time
detect_and_save()

You can directly add one image on top of another one at any coordinate easily in opencv.
cap = cv2.VideoCapture(0)
im_height = 50 #define your top image size here
im_width = 50
im = cv2.resize(cv2.imread("Frame.png"), (im_width, im_height))
while (True):
ret, frame = cap.read()
frame[0:im_width, 0:im_height] = im #for top-left corner, 0:50 and 0:50 for my image; select your region here like 200:250
cv2.imshow("live camera", frame)
if cv2.waitKey(1) == ord("q"):
break
cap.release()
cv2.destroyAllWindows()

Python Image Inpainting Produces Poor Results

I am trying to create a python script that removes the watermark from an image. In order to do that, I have decided to use the cv2.inpaint method. These are the steps that I follow in order to remove the watermark:
Get the image from the user
Ask the user to shade on the watermark
Create a mask out of the user's shading
Inpaint the image with the mask created in order to remove the watermark
This is my code:
import cv2
import numpy as np
drawing = False # true if mouse is pressed
pt1_x , pt1_y = None , None
def nothing(x):
pass
def line_drawing(event,x,y,flags,param):
global pt1_x,pt1_y,drawing
if event==cv2.EVENT_LBUTTONDOWN:
drawing=True
pt1_x,pt1_y=x,y
elif event==cv2.EVENT_MOUSEMOVE:
if drawing==True:
cv2.line(img,(pt1_x,pt1_y),(x,y),color=(0,0,255),thickness= cv2.getTrackbarPos('Thickness','Damaged Image'))
cv2.line(mask, (pt1_x, pt1_y), (x, y), color=(255,255,255), thickness=cv2.getTrackbarPos('Thickness', 'Damaged Image'))
pt1_x,pt1_y=x,y
elif event==cv2.EVENT_LBUTTONUP:
drawing=False
cv2.line(img,(pt1_x,pt1_y),(x,y),color=(0,0,255),thickness= cv2.getTrackbarPos('Thickness','Damaged Image'))
cv2.line(mask, (pt1_x, pt1_y), (x, y), color=(255,255,255), thickness=cv2.getTrackbarPos('Thickness', 'Damaged Image'))
img = cv2.imread('D:\\Watermark.jpg')
ratio = img.shape[1]/img.shape[0]
height = 600
width = height * ratio
img = cv2.resize(img, (int(width),height))
mask = np.zeros(img.shape[:-1], dtype = np.uint8)
#mask = cv2.integral(mask)
cv2.namedWindow('Mask')
cv2.namedWindow('Damaged Image')
cv2.setMouseCallback('Damaged Image',line_drawing)
cv2.createTrackbar('Thickness','Damaged Image', 10, 50, nothing)
while(1):
cv2.imshow('Damaged Image',img)
cv2.imshow('Mask', mask)
if cv2.waitKey(1) & 0xFF == 27:
break
elif cv2.waitKey(1) & 0xFF == ord('a'):
pass
elif cv2.waitKey(1) & 0xFF == ord('s'):
restored = cv2.inpaint(img, mask, 3, cv2.INPAINT_TELEA)
cv2.namedWindow('Restored Image')
cv2.imshow('Restored Image', restored)
cv2.destroyAllWindows()
This is the image from which I am trying to remove the watermark:
This is the mask:
This is the output:
Why is the output so poor? And what can I do to improve the quality of the output? Any help would be appreciated. Thanks!

Select a static ROI on webcam video on python openCV

I need to selec a ROI (region of interest), or work area, on a live video from my webcam and take a snapshot of ONLY this work area or ROI, but I can't found how to do this.
In this page https://www.learnopencv.com/how-to-select-a-bounding-box-roi-in-opencv-cpp-python/ have a code for draw a ROI but only with images, not a live video.
import cv2
cam = cv2.VideoCapture(0)
cam.set(cv2.CAP_PROP_FRAME_WIDTH, 1280)
cam.set(cv2.CAP_PROP_FRAME_HEIGHT, 720)
cv2.namedWindow("test")
img_counter = 0
while True:
ret, frame = cam.read()
cv2.imshow("test", frame)
if not ret:
break
k = cv2.waitKey(1)
if k % 256 == 27:
# ESC pressed
print("Escape hit, closing...")
break
elif k % 256 == 32:
# SPACE pressed
img_name = "opencv_frame_{}.png".format(img_counter)
cv2.imwrite(img_name, frame)
print("{} written!".format(img_name))
img_counter += 1
cam.release()
cv2.destroyAllWindows()
This code take a snapshot with space key but not draw a ROI area.
Thanks in advance!

Here's a widget to select static ROIs from a video frame. Essentially the idea is to use cv2.setMouseCallback() and event handlers to detect if the mouse has been clicked or released. For this implementation, you can extract coordinates by holding down the left mouse button and dragging to select the desired ROI. You can reset the ROI using the right mouse button. To use the widget, press c to pause the video and start cropping. Then you are free to select the ROI. Once you have selected your ROI, press c again to crop the desired section. To resume the video, press r.
import cv2
class staticROI(object):
def __init__(self):
self.capture = cv2.VideoCapture('fedex.mp4')
# Bounding box reference points and boolean if we are extracting coordinates
self.image_coordinates = []
self.extract = False
self.selected_ROI = False
self.update()
def update(self):
while True:
if self.capture.isOpened():
# Read frame
(self.status, self.frame) = self.capture.read()
cv2.imshow('image', self.frame)
key = cv2.waitKey(2)
# Crop image
if key == ord('c'):
self.clone = self.frame.copy()
cv2.namedWindow('image')
cv2.setMouseCallback('image', self.extract_coordinates)
while True:
key = cv2.waitKey(2)
cv2.imshow('image', self.clone)
# Crop and display cropped image
if key == ord('c'):
self.crop_ROI()
self.show_cropped_ROI()
# Resume video
if key == ord('r'):
break
# Close program with keyboard 'q'
if key == ord('q'):
cv2.destroyAllWindows()
exit(1)
else:
pass
def extract_coordinates(self, event, x, y, flags, parameters):
# Record starting (x,y) coordinates on left mouse button click
if event == cv2.EVENT_LBUTTONDOWN:
self.image_coordinates = [(x,y)]
self.extract = True
# Record ending (x,y) coordintes on left mouse bottom release
elif event == cv2.EVENT_LBUTTONUP:
self.image_coordinates.append((x,y))
self.extract = False
self.selected_ROI = True
# Draw rectangle around ROI
cv2.rectangle(self.clone, self.image_coordinates[0], self.image_coordinates[1], (0,255,0), 2)
# Clear drawing boxes on right mouse button click
elif event == cv2.EVENT_RBUTTONDOWN:
self.clone = self.frame.copy()
self.selected_ROI = False
def crop_ROI(self):
if self.selected_ROI:
self.cropped_image = self.frame.copy()
x1 = self.image_coordinates[0][0]
y1 = self.image_coordinates[0][1]
x2 = self.image_coordinates[1][0]
y2 = self.image_coordinates[1][1]
self.cropped_image = self.cropped_image[y1:y2, x1:x2]
print('Cropped image: {} {}'.format(self.image_coordinates[0], self.image_coordinates[1]))
else:
print('Select ROI to crop before cropping')
def show_cropped_ROI(self):
cv2.imshow('cropped image', self.cropped_image)
if __name__ == '__main__':
static_ROI = staticROI()

I would like to define a Region of Interest in a video and only process that area

I am having problems understanding regions of interest in opencv. I have some code that does a simple background subtraction from my first_frame. I am also able to draw a rectangle with my mouse_draw_rect function.
Now, I would like the background subtraction to only happen inside the rectangle that I draw because I would like to speed up the algorithm processing. I know I have to set some sort of Region of Interest but I tried it all yesterday and today and nothing that I have tried from tutorials have worked. Can someone help guide me through this process please?
EDIT: attempted to fix code
import numpy as np
import cv2
import matplotlib.pyplot as plt
cap = cv2.VideoCapture(0)
_, first_frame = cap.read()
def mouse_draw_rect(event, x, y, flags, params):
global point1, point2, drawing, first_frame, x1, x2, y1, y2
if event == cv2.EVENT_LBUTTONDOWN:
if drawing is False:
drawing = True
point1 = (x, y)
x1 = (x)
y1 = (y)
else:
drawing = False
elif event == cv2.EVENT_MOUSEMOVE:
if drawing is True:
point2 = (x, y)
x2 = (x)
y2 = (y)
elif event == cv2.EVENT_MBUTTONDOWN:
first_frame = frame
drawing = False
point1 = ()
point2 = ()
x1 = ()
x2 = ()
y1 = ()
y2 = ()
cv2.namedWindow('Original')
cv2.setMouseCallback("Original", mouse_draw_rect)
while True:
ret, frame = cap.read( )
if point1 and point2:
cv2.rectangle(frame, point1, point2, (0, 0, 0),5)
difference = cv2.absdiff(first_frame[y1:y2, x1:x2], frame[y1:y2, x1:x2])
difference = cv2.GaussianBlur(difference, (3, 3), 0)
_, difference = cv2.threshold(difference, 18, 255, cv2.THRESH_BINARY)
cv2.imshow('first frame (1)', first_frame)
cv2.imshow('Original', frame)
cv2.imshow('difference', difference)
key = cv2.waitKey(30) & 0xff
if key == 27:
break
cap.release()
cv2.destroyAllWindows()

The main problem is with the ROI selection event and how it is being called currently. The current implementation is not dynamic which means we are unable to visualize what ROI we are trying to select. Also, we have started processing before even selecting the ROI.
The proper way to select the ROI is that once we have captured the first frame, register the mouse click event and visualize the frame indefinitely with imshow and waitKey(n) until some specific key is pressed. Alternatively, we may be able to achieve the same effect without the infinite loop by using waitKey(0) (Not tested).
At this stage, we should be able to draw the desired ROI rectangle. The key factor here is the execution must be halted either by using an infinite loop or waitKey(0). Just registering the event is not enough. After ROI selection is done, then proceed with the rest of the code.
Some recommendations are as follows:
Avoid the usage of global variables where possible
Create separate window for ROI selection and discard it afterwards
Create separate functions for each individual task
Following is the complete code demonstrating correct usage of mouse click event to select the ROI for video processing:
import numpy as np
import cv2
import matplotlib.pyplot as plt
ORIGINAL_WINDOW_TITLE = 'Original'
FIRST_FRAME_WINDOW_TITLE = 'First Frame'
DIFFERENCE_WINDOW_TITLE = 'Difference'
canvas = None
drawing = False # true if mouse is pressed
#Retrieve first frame
def initialize_camera(cap):
_, frame = cap.read()
return frame
# mouse callback function
def mouse_draw_rect(event,x,y,flags, params):
global drawing, canvas
if drawing:
canvas = params[0].copy()
if event == cv2.EVENT_LBUTTONDOWN:
drawing = True
params.append((x,y)) #Save first point
elif event == cv2.EVENT_MOUSEMOVE:
if drawing:
cv2.rectangle(canvas, params[1],(x,y),(0,255,0),2)
elif event == cv2.EVENT_LBUTTONUP:
drawing = False
params.append((x,y)) #Save second point
cv2.rectangle(canvas,params[1],params[2],(0,255,0),2)
def select_roi(frame):
global canvas
canvas = frame.copy()
params = [frame]
ROI_SELECTION_WINDOW = 'Select ROI'
cv2.namedWindow(ROI_SELECTION_WINDOW)
cv2.setMouseCallback(ROI_SELECTION_WINDOW, mouse_draw_rect, params)
roi_selected = False
while True:
cv2.imshow(ROI_SELECTION_WINDOW, canvas)
key = cv2.waitKey(10)
#Press Enter to break the loop
if key == 13:
break;
cv2.destroyWindow(ROI_SELECTION_WINDOW)
roi_selected = (3 == len(params))
if roi_selected:
p1 = params[1]
p2 = params[2]
if (p1[0] == p2[0]) and (p1[1] == p2[1]):
roi_selected = False
#Use whole frame if ROI has not been selected
if not roi_selected:
print('ROI Not Selected. Using Full Frame')
p1 = (0,0)
p2 = (frame.shape[1] - 1, frame.shape[0] -1)
return roi_selected, p1, p2
if __name__ == '__main__':
cap = cv2.VideoCapture(0)
#Grab first frame
first_frame = initialize_camera(cap)
#Select ROI for processing. Hit Enter after drawing the rectangle to finalize selection
roi_selected, point1, point2 = select_roi(first_frame)
#Grab ROI of first frame
first_frame_roi = first_frame[point1[1]:point2[1], point1[0]:point2[0], :]
#An empty image of full size just for visualization of difference
difference_image_canvas = np.zeros_like(first_frame)
while cap.isOpened():
ret, frame = cap.read()
if ret:
#ROI of current frame
roi = frame[point1[1]:point2[1], point1[0]:point2[0], :]
difference = cv2.absdiff(first_frame_roi, roi)
difference = cv2.GaussianBlur(difference, (3, 3), 0)
_, difference = cv2.threshold(difference, 18, 255, cv2.THRESH_BINARY)
#Overlay computed difference image onto the whole image for visualization
difference_image_canvas[point1[1]:point2[1], point1[0]:point2[0], :] = difference.copy()
cv2.imshow(FIRST_FRAME_WINDOW_TITLE, first_frame)
cv2.imshow(ORIGINAL_WINDOW_TITLE, frame)
cv2.imshow(DIFFERENCE_WINDOW_TITLE, difference_image_canvas)
key = cv2.waitKey(30) & 0xff
if key == 27:
break
else:
break
cap.release()
cv2.destroyAllWindows()
Pro Tip:
Sometimes, when a camera is initialized, it takes some time to warm-up depending upon the ambient light present in the room. You may consider skipping a few initial frames to let the camera settle from the initialization phase. It can be done by defining the initialize_camera function in the above code as follows:
def initialize_camera(cap):
for i in range(0,60): #Skip first 60 frames
_, frame = cap.read()
return frame

Simply crop by the area in the rectangle you have drawn.
Instead of
difference = cv2.absdiff(first_frame, frame)
use
difference = cv2.absdiff(first_frame[y1:y2, x1:x2], frame[y1:y2, x1:x2])

On each frame you can create a subimage using subimage = image[y1:y2,x1:x2] And then use the subimage for processing.
A quick and dirty implementation in you code:
Replace
elif event == cv2.EVENT_MOUSEMOVE:
with
elif event == cv2.EVENT_LBUTTONUP:
And add the subimage:
if point1 and point2:
cv2.rectangle(frame, point1, point2, (0, 0, 0),5)
subimg = frame[point1[1]:point2[1],point1[0]:point2[0]]
cv2.imshow("Subimage",subimg)

track a image in video and replace with another image using opencv

I have to track a window in a video and need to paste an image on window,I have used camshift to track the window, but it did not track it correct.My window is in brown color so I have given the following color range.
np.array((110,0,0)--lower
np.array((130,255,255)--higher..
I have red many documents in opencv but not able to figure out which method to follow.I am using opencv2.4.9 with python.
Below is the code which I tried.Please help me out to figure out the exact location of window.emphasized text
#!/usr/bin/env python
import numpy as np
import cv2
cap = cv2.VideoCapture("myvideo.mp4")
# take first frame of the video
ret,frame = cap.read()
#print frame
#print ret
# setup initial location of window
r,h,c,w = 157,40,337,40
track_window = (c,r,w,h)
# set up the ROI for tracking
roi = frame[r:r+h, c:c+w]
hsv_roi = cv2.cvtColor(roi, cv2.COLOR_BGR2HSV)
mask = cv2.inRange(hsv_roi, np.array((110,0,0)), np.array((130,255,255)))
roi_hist = cv2.calcHist([hsv_roi],[0],mask,[255],[0,255])
cv2.imshow('img2',roi_hist)
#print roi_hist
cv2.normalize(roi_hist,roi_hist,0,255,cv2.NORM_MINMAX)
# Setup the termination criteria, either 10 iteration or move by at least 1 pt
term_crit = ( cv2.TERM_CRITERIA_EPS | cv2.TERM_CRITERIA_COUNT, 10, 1 )
i = 1
while(1):
ret ,frame = cap.read()
if ret == True:
i += 1
hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
dst = cv2.calcBackProject([hsv],[0],roi_hist,[0,255],1)
# apply meanshift to get the new location
ret, track_window = cv2.CamShift(dst, track_window, term_crit)
#print track_window
# Draw it on image
x,y,w,h = track_window
img2 = cv2.rectangle(frame, (x,y), (x+w,y+h), 255,2)
cv2.imshow('img2',frame)
k = cv2.waitKey(200) & 0xff
if k == 27:
break
else:
# print "comes here2";
cv2.imwrite(str(i)+"test.jpg",frame)
#break
else:
break
cv2.destroyAllWindows()
cap.release()