I am trying to detect BLUE colored CIRCLE and it's CENTER. Then draw a circle on the detected circle and a very small circle on it's center. But I get a few errors. (I am using OpenCV 3.1.0, Python 2.7 Anaconda 64 bits, PyCharm as an IDE) (Please help me using python codes) I run the following code:
import cv2
import numpy as np
cap = cv2.VideoCapture(0)
if cap.isOpened():
while(True):
frame, _ = cap.read()
# blurring the frame that's captured
frame_gau_blur = cv2.GaussianBlur(frame, (3, 3), 0)
# converting BGR to HSV
hsv = cv2.cvtColor(frame_gau_blur, cv2.COLOR_BGR2HSV)
# the range of blue color in HSV
lower_blue = np.array([110, 50, 50])
higher_blue = np.array([130, 255, 255])
# getting the range of blue color in frame
blue_range = cv2.inRange(hsv, lower_blue, higher_blue)
# getting the V channel which is the gray channel
blue_s_gray = blue_range[::2]
# applying HoughCircles
circles = cv2.HoughCircles(blue_s_gray, cv2.HOUGH_GRADIENT, 1, 10, 100, 30, 5, 50)
circles = np.uint16(np.around(circles))
for i in circles[0,:]:
# drawing on detected circle and its center
cv2.circle(frame,(i[0],i[1]),i[2],(0,255,0),2)
cv2.circle(frame,(i[0],i[1]),2,(0,0,255),3)
cv2.imshow('circles', frame)
k = cv2.waitKey(5) & 0xFF
if k == 27:
break
cv2.destroyAllWindows()
else:
print "Can't find camera"
The error I get when I run the code is:
OpenCV Error: Assertion failed (depth == CV_8U || depth == CV_16U || depth == CV_32F) in cv::cvtColor, file C:\builds\master_PackSlaveAddon-win64-vc12-static\opencv\modules\imgproc\src\color.cpp, line 7935 Traceback (most recent call last): File "C:/Users/Meliodas/PycharmProjects/OpenCV_By_Examples/code_tester.py", line 11, in hsv = cv2.cvtColor(frame_gau_blur, cv2.COLOR_BGR2HSV) cv2.error: C:\builds\master_PackSlaveAddon-win64-vc12-static\opencv\modules\imgproc\src\color.cpp:7935: error: (-215) depth == CV_8U || depth == CV_16U || depth == CV_32F in function cv::cvtColor Thanks a lot in advance for your help!
I have solved the my problem and after looking up the meanings of the errors online (the one's that I got), I was able to find the solutions for them and hence I was able to solve them. If you run the following code given below you should be able to detect blue circles pretty well. Thanks a lot to the people who tried to help me to solve my problem.
The code is given below:
import cv2
import numpy as np
cap = cv2.VideoCapture(0)
if cap.isOpened():
while(True):
ret, frame = cap.read()
# blurring the frame that's captured
frame_gau_blur = cv2.GaussianBlur(frame, (3, 3), 0)
# converting BGR to HSV
hsv = cv2.cvtColor(frame_gau_blur, cv2.COLOR_BGR2HSV)
# the range of blue color in HSV
lower_blue = np.array([110, 50, 50])
higher_blue = np.array([130, 255, 255])
# getting the range of blue color in frame
blue_range = cv2.inRange(hsv, lower_blue, higher_blue)
res_blue = cv2.bitwise_and(frame_gau_blur,frame_gau_blur, mask=blue_range)
blue_s_gray = cv2.cvtColor(res_blue, cv2.COLOR_BGR2GRAY)
canny_edge = cv2.Canny(blue_s_gray, 50, 240)
# applying HoughCircles
circles = cv2.HoughCircles(canny_edge, cv2.HOUGH_GRADIENT, dp=1, minDist=10, param1=10, param2=20, minRadius=100, maxRadius=120)
cir_cen = []
if circles != None:
# circles = np.uint16(np.around(circles))
for i in circles[0,:]:
# drawing on detected circle and its center
cv2.circle(frame,(i[0],i[1]),i[2],(0,255,0),2)
cv2.circle(frame,(i[0],i[1]),2,(0,0,255),3)
cir_cen.append((i[0],i[1]))
print cir_cen
cv2.imshow('circles', frame)
cv2.imshow('gray', blue_s_gray)
cv2.imshow('canny', canny_edge)
k = cv2.waitKey(5) & 0xFF
if k == 27:
break
cv2.destroyAllWindows()
else:
print 'no cam'