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()
Related
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()
I have written a code in python to detect a red color in OpenCV. I am getting proper output,but I want to give user input in the code to detect a specific color. Eg: If I will give blue as a user input, it should show only blue on the output. I also want to add few attributes as a output, such as time of that object get detected and location of the live video. I am new to python and opencv, it would be great if I will get some guidance.
My existing code is as below:
import cv2
import numpy as np
# Capture the input frame from webcam
def get_frame(cap, scaling_factor):
# Capture the frame from video capture object
ret, frame = cap.read()
# Resize the input frame
frame = cv2.resize(frame, None, fx=scaling_factor,
fy=scaling_factor, interpolation=cv2.INTER_AREA)
return frame
if __name__=='__main__':
cap = cv2.VideoCapture(0)
scaling_factor = 0.5
# Iterate until the user presses ESC key
while True:
frame = get_frame(cap, scaling_factor)
# Convert the HSV colorspace
hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
# Define 'blue' range in HSV colorspace
lower = np.array([60,100,100])
upper = np.array([180,255,255])
# Threshold the HSV image to get only blue color
mask = cv2.inRange(hsv, lower, upper)
# Bitwise-AND mask and original image
res = cv2.bitwise_and(frame, frame, mask=mask)
res = cv2.medianBlur(res, 5)
cv2.imshow('Original image', frame)
cv2.imshow('Color Detector', res)
# Check if the user pressed ESC key
c = cv2.waitKey(5)
if c == 27:
break
cv2.destroyAllWindows()
Your code seems to work correctly. Looking at the equations about converting from RGB to HSV bearing in mind that boundaries in OpenCV are between 0-180 for H channel and 0-255 for S and V channels, we can generalize the code to work for all colors.
import cv2
import numpy as np
# Capture the input frame from webcam
def get_frame(cap, scaling_factor):
# Capture the frame from video capture object
ret, frame = cap.read()
# Resize the input frame
frame = cv2.resize(frame, None, fx=scaling_factor,
fy=scaling_factor, interpolation=cv2.INTER_AREA)
return frame
# Define the color range in HSV colorspace
lower1 = np.array([0,100,100])
upper1 = np.array([60,255,255])
lower2 = np.array([120,100,100])
upper2 = np.array([180,255,255])
def color_range(degree):
# Degree is between 0-360
# OpenCV uses 0-180 range for H channel
degree = int(degree/2);
global lower1, upper1, lower2, upper2
if degree < 60:
lower1 = np.array([int(0),100,100])
upper1 = np.array([degree+60,255,255])
lower2 = np.array([degree+120,100,100])
upper2 = np.array([int(180),255,255])
elif degree > 120:
lower1 = np.array([degree-60,100,100])
upper1 = np.array([int(180),255,255])
lower2 = np.array([int(0),100,100])
upper2 = np.array([degree-120,255,255])
else:
lower1 = np.array([degree-60,100,100])
upper1 = np.array([degree+60,255,255])
# ineffective variables
lower2 = np.array([181,100,100])
upper2 = np.array([181,255,255])
if __name__=='__main__':
cap = cv2.VideoCapture(0)
scaling_factor = 0.5
# create trackbar for color change
winname = 'Color Detector'
cv2.namedWindow(winname)
cv2.createTrackbar('Color', winname, 0, 360, color_range)
# Iterate until the user presses ESC key
while True:
frame = get_frame(cap, scaling_factor)
# Convert the HSV colorspace
hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
# Threshold the HSV image to get only desired color
mask1 = cv2.inRange(hsv, lower1, upper1)
mask2 = cv2.inRange(hsv, lower2, upper2)
mask = cv2.bitwise_or(mask1, mask2)
# Bitwise-AND mask and original image
res = cv2.bitwise_and(frame, frame, mask=mask)
cv2.imshow('Original image', frame)
cv2.imshow(winname, res)
# Check if the user pressed ESC key
c = cv2.waitKey(1) & 0xFF
if c == 27:
break
cv2.destroyAllWindows()
cap.release()
I have written a python code using opencv to detect a rectangle (displaying height, and width) also determine the distance from camera to the object but when i run the code i get this error(can be found below) i don't know what am doing wrong please i would appreciate it if anyone could help me out i have tried every possible solution that i could find but still can't rid of the error.
ERROR
yuv_red = cv2.cvtColor(frame, cv2.COLOR_BGR2YUV)
error: C:\builds\master_PackSlaveAddon-win32-vc12-static\opencv\modules\imgproc\src\color.cpp:8059: error: (-215) scn == 3 || scn == 4 in function cv::cvtColor
import sys
sys.path.append('C:\Python27\Lib\site-packages')
import cv2
import numpy as np
import argparse
import math
############################# Capturing Video Through Camera ########################
cap = cv2.VideoCapture(0)
############# Distance to Camera initial value set to zero ##########################
Distance_to_Camera=0
while(True):
################################# Capture frame-by-frame ###########################
ret, frame = cap.read()
############################ Converting frame(img i.e BGR to YUV) ###################
yuv_red = cv2.cvtColor(frame, cv2.COLOR_BGR2YUV)
red_color = np.uint8([[[0,0,255]]])
yuv_color = cv2.cvtColor(red_color,cv2.COLOR_BGR2YUV)
print yuv_color
############################### Processing of Image ##############################
##################### Defining the Range of Red Colour ###########################
red_lower = np.array([136,87,111],np.uint8)
red_upper = np.array([180,255,255],np.uint8)
##################### Finding the Range of Red Colour in the image ###################
mask = cv2.inRange(yuv_red, red_lower,red_upper)
####################### Morphological Transformation, Dilation #######################
res = cv2.bitwise_and(frame, frame, mask = mask)
#####################################################################################
gray = cv2.cvtColor(res,cv2.COLOR_BGR2GRAY) #Converting the BGR res to Gray
blurred = cv2.GaussianBlur(gray, (5,5), 5) #Blur Image to remove noise
blur = cv2.bilateralFilter(blurred, 5,50,50) #Smooth the image
median = cv2.medianBlur(blur,5) #Reduce noise from image
thresh = cv2.threshold(median, 3, 255, cv2.THRESH_BINARY)[1] #To achieve a better output of white and black
frame2, contour, hierarchy = cv2.findContours(thresh,cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)
##################### Splitting and Merging Image channels ###########################
b,g,r = cv2.split(res)
ttl = res.size/3
Ra = float(np.sum(r))/ ttl
print Ra
if Ra > 1:
c = contours[0]
M = cv2.moments(c)
x = int(M['m10']/M['m00'])
y = int(M['m01']/M['m00'])
x,y,w,h = cv2.boundingRect(c)
epsilon = 0.01*cv2.arcLength(c, True)
approx = cv2.approxPolyDP(c, epsilon, True)
perimeter = cv2.approxLength(c,True)
area = cv2.contourArea(c)
ah = h/40
aw = w/40
Distance_to_Camera = round(math.sqrt(315/area),4)
print Distance_to_Camera
approx = cv2.approxPolyDP(c, epsilon, True)
print len(approx)
shape = len(approx)
if shape == 4:
print " 4 Sides"
rect = cv2.minAreaRect(c)
box = cv2.boxPoints(rect)
box = np.int0(box)
cv2.drawContours(frame,ArithmeticError[box],0,(0,0,255),0)
print box
if ah == aw:
################################ Displaying Text on the Image ################################
print "Unknown"
cv2.putTextputText(frame,"Unknown",(x+150,y+150),cv2.FONT_HERSHEY_SIMPLEX,2,(255,255,255),4)
else:
################################ Displaying Text on the Image ################################
print "Rectangle"
cv2.putTextputText(frame,"Rectangle",(x+150,y+150),cv2.FONT_HERSHEY_SIMPLEX,2,(255,255,255),4)
output = ("Distance="+str((round((distance+0.0004)*1000))) + "cm" + "X=" + str(aw)+"cm" +"Y="+str(ah)+"cm"+"Perimeter=" +str(round(perimeter/40))+"cm"+"Area="+str(round((area/1.64)/1000))+"cm^2")
cv2.imshow('gray',frame)
else:
cv2.imshow('gray',frame)
########################################## Output ##########################################
cv2.imshow('gray',frame)
cv2.imshow('grayscaled',thresh)
if cv2.waitKey(20) & 0xFF == 27:
break
##if k == 27: # wait for ESC key to exit
## cv2.destroyAllWindows()
# When everything done, release the capture
cv2.destroyAllWindows()
cap.release()
[1]: https://i.stack.imgur.com/qB2rx.png
In the line implementing a bilateral filter you have an erroneous parenthesis:
blur = cv2.bilateralFilter(blurred, (5,50,50)
Check out the docs for cv2.bilateralFilter() to see the proper use.
thanks for taking the time to read, and hopefully help me.
I have an AR.Drone 2.0 that I have already started to program/develop. I am using python for coding with opencv for the image processing. I want to be able to feedback this code to the drone. I was thinking about obtaining frames from the video stream and have the AR.Drone perform some tasks based upon the images. I, however, don't know where to start. It would be helpful for me if someone can point me in the right direction.
import numpy as np
import cv2
# open the camera
cap = cv2.VideoCapture('tcp://192.168.1.1:5555')
def nothing(x):
pass
cv2.namedWindow('result')
# Starting with 100's to prevent error while masking
h,s,v = 100,100,100
# Creating track bar
cv2.createTrackbar('h', 'result',0,179,nothing)
cv2.createTrackbar('s', 'result',0,255,nothing)
cv2.createTrackbar('v', 'result',0,255,nothing)
while True:
#read the image from the camera
ret, frame = cap.read()
#You will need this later
frame = cv2.cvtColor(frame, 35)
#converting to HSV
hsv = cv2.cvtColor(frame,cv2.COLOR_BGR2HSV)
# get info from track bar and appy to result
h = cv2.getTrackbarPos('h','result')
s = cv2.getTrackbarPos('s','result')
v = cv2.getTrackbarPos('v','result')
# Normal masking algorithm
lower_blue = np.array([h,s,v])
upper_blue = np.array([180,255,255])
mask = cv2.inRange(hsv,lower_blue, upper_blue)
result = cv2.bitwise_and(frame,frame,mask = mask)
cv2.imshow('result',result)
#find center
cnts=cv2.findContours(mask.copy(), cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE)[-2]
center=None
if len(cnts)>0:
c=max(cnts, key=cv2.contourArea)
((x,y),radius)=cv2.minEnclosingCircle(c)
M=cv2.moments(c)
center=(int(M["m10"] / M["m00"]), int(M["m01"] / M["m00"]))
if radius>10:
#cv2.circle(frame, (int(x),int(y)), int(radius), 2)
cv2.circle(frame, center,5,(0,0,255),-1)
# color detection limits
lB = 5
lG = 50
lR = 50
hB = 15
hG = 255
hR = 255
lowerLimits = np.array([lB, lG, lR])
upperLimits = np.array([hB, hG, hR])
# Our operations on the frame come here
thresholded = cv2.inRange(frame, lowerLimits, upperLimits)
outimage = cv2.bitwise_and(frame, frame, mask = thresholded)
cv2.imshow('original', frame)
# Display the resulting frame
cv2.imshow('processed',outimage)
# Quit the program when Q is pressed
if cv2.waitKey(1) & 0xFF == ord('q'):
break
# When everything done, release the capture
print 'closing program'
cap.release()
cv2.destroyAllWindows()'
I am using opencv to detect the color of objects by using HSV trackbars values and I want my python code to save the latest changes I would make to the trackbars in opencv , when I start the code again, the trackbars will have the last values? below is my code
import numpy as np
import cv2
# open the camera
cap = cv2.VideoCapture(0)
def nothing(x):
pass
cv2.namedWindow('result')
# Starting with 100's to prevent error while masking
h,s,v = 100,100,100
# Creating track bar
cv2.createTrackbar('h', 'result',0,179,nothing)
cv2.createTrackbar('s', 'result',0,255,nothing)
cv2.createTrackbar('v', 'result',0,255,nothing)
while True:
#read the image from the camera
ret, frame = cap.read()
#You will need this later
frame = cv2.cvtColor(frame, 35)
#converting to HSV
hsv = cv2.cvtColor(frame,cv2.COLOR_BGR2HSV)
# get info from track bar and appy to result
h = cv2.getTrackbarPos('h','result')
s = cv2.getTrackbarPos('s','result')
v = cv2.getTrackbarPos('v','result')
# Normal masking algorithm
lower_blue = np.array([h,s,v])
upper_blue = np.array([180,255,255])
mask = cv2.inRange(hsv,lower_blue, upper_blue)
result = cv2.bitwise_and(frame,frame,mask = mask)
cv2.imshow('result',result)
#find center
cnts=cv2.findContours(mask.copy(), cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE)[-2]
center=None
if len(cnts)>0:
c=max(cnts, key=cv2.contourArea)
((x,y),radius)=cv2.minEnclosingCircle(c)
M=cv2.moments(c)
center=(int(M["m10"] / M["m00"]), int(M["m01"] / M["m00"]))
if radius>10:
#cv2.circle(frame, (int(x),int(y)), int(radius), 2)
cv2.circle(frame, center,5,(0,0,255),-1)
# color detection limits
lB = 5
lG = 50
lR = 50
hB = 15
hG = 255
hR = 255
lowerLimits = np.array([lB, lG, lR])
upperLimits = np.array([hB, hG, hR])
# Our operations on the frame come here
thresholded = cv2.inRange(frame, lowerLimits, upperLimits)
outimage = cv2.bitwise_and(frame, frame, mask = thresholded)
cv2.imshow('original', frame)
# Display the resulting frame
cv2.imshow('processed',outimage)
# Quit the program when Q is pressed
if cv2.waitKey(1) & 0xFF == ord('q'):
break
# When everything done, release the capture
print 'closing program'
cap.release()
cv2.destroyAllWindows()
One option is to write the values to a text file somewhere, then when the program starts, read the file and parse the values written in the file.
See: How could I save data after closing my program?