I am trying to use OpenCV with Python in order to detect squares in a live video feed from a Raspberry Pi camera. However, the cv2.GaussianBlur
and cv2.Canny
functions in the code below are causing the following error: "TypeError: numpy.ndarray' object is not callable".
I cannot seem to resolve the error. Any help is appreciated.
import cv2
# load the video
camera = cv2.VideoCapture(0)
# keep looping
while True:
# grab the current frame and initialize the status text
(grabbed, frame) = camera.read()
status = "No Targets"
# check to see if we have reached the end of the
# video
if not grabbed:
break
# convert the frame to grayscale, blur it, and detect edges
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
blurred = cv2.GaussianBlur(gray, (7, 7), 0)
edged = cv2.Canny(blurred, 50, 150)
# find contours in the edge map
(cnts, _) = cv2.findContours(edged.copy(), cv2.RETR_EXTERNAL,
cv2.CHAIN_APPROX_SIMPLE)
# loop over the contours
for c in cnts:
# approximate the contour
peri = cv2.arcLength(c, True)
approx = cv2.approxPolyDP(c, 0.01 * peri, True)
# ensure that the approximated contour is "roughly" rectangular
if len(approx) >= 4 and len(approx) <= 6:
# compute the bounding box of the approximated contour and
# use the bounding box to compute the aspect ratio
(x, y, w, h) = cv2.boundingRect(approx)
aspectRatio = w / float(h)
# compute the solidity of the original contour
area = cv2.contourArea(c)
hullArea = cv2.contourArea(cv2.convexHull(c))
solidity = area / float(hullArea)
# compute whether or not the width and height, solidity, and
# aspect ratio of the contour falls within appropriate bounds
keepDims = w > 25 and h > 25
keepSolidity = solidity > 0.9
keepAspectRatio = aspectRatio >= 0.8 and aspectRatio <= 1.2
# ensure that the contour passes all our tests
if keepDims and keepSolidity and keepAspectRatio:
# draw an outline around the target and update the status
# text
cv2.drawContours(frame, [approx], -1, (0, 0, 255), 4)
status = "Target(s) Acquired"
# draw the status text on the frame
cv2.putText(frame, status, (20, 30), cv2.FONT_HERSHEY_SIMPLEX, 0.5,
(0, 0, 255), 2)
# show the frame and record if a key is pressed
cv2.imshow("Frame", frame)
key = cv2.waitKey(1) & 0xFF
# if the 'q' key is pressed, stop the loop
if key == ord("q"):
break
# cleanup the camera and close any open windows
camera.release()
cv2.destroyAllWindows()
An alternative to work with 2.x 、3.x、4.x is:
cnts, hiers = cv2.findContours(...)[-2:]
Notice:
cv2.findContours
has changed since OpenCV 3.x
, but in OpenCV 4.0
it changes back!!!
In OpenCV 3.4:
findContours(image, mode, method[, contours[, hierarchy[, offset]]]) -> image, contours, hierarchy
In OpenCV 4.0:
findContours(image, mode, method[, contours[, hierarchy[, offset]]]) -> contours, hierarchy