Hello! I also cannot access USB webcam via OpenCV Python wrapper.
But to be honest, next code is working on MacBook Pro (because it’s camera is embedded)
# OpenCV_test_3.py
# this program tracks a red ball
# (no motor control is performed to move the camera, we will get to that later in the tutorial)
import os
import cv2
import numpy as np
###################################################################################################
def main():
capWebcam = cv2.VideoCapture(0) # declare a VideoCapture object and associate to webcam, 0 => use 1st webcam
# show original resolution
print("default resolution = " + str(capWebcam.get(cv2.CAP_PROP_FRAME_WIDTH)) + "x" + str(
capWebcam.get(cv2.CAP_PROP_FRAME_HEIGHT)))
capWebcam.set(cv2.CAP_PROP_FRAME_WIDTH, 320.0) # change resolution to 320x240 for faster processing
capWebcam.set(cv2.CAP_PROP_FRAME_HEIGHT, 240.0)
# show updated resolution
print("updated resolution = " + str(capWebcam.get(cv2.CAP_PROP_FRAME_WIDTH)) + "x" + str(
capWebcam.get(cv2.CAP_PROP_FRAME_HEIGHT)))
if capWebcam.isOpened() == False: # check if VideoCapture object was associated to webcam successfully
print("error: capWebcam not accessed successfully\n\n") # if not, print error message to std out
os.system("pause") # pause until user presses a key so user can see error message
return # and exit function (which exits program)
# end if
while cv2.waitKey(1) != 27 and capWebcam.isOpened(): # until the Esc key is pressed or webcam connection is lost
blnFrameReadSuccessfully, imgOriginal = capWebcam.read() # read next frame
if not blnFrameReadSuccessfully or imgOriginal is None: # if frame was not read successfully
print("error: frame not read from webcam\n") # print error message to std out
os.system("pause") # pause until user presses a key so user can see error message
break # exit while loop (which exits program)
# end if
imgHSV = cv2.cvtColor(imgOriginal, cv2.COLOR_BGR2HSV)
imgThreshLow = cv2.inRange(imgHSV, np.array([0, 135, 135]), np.array([18, 255, 255]))
imgThreshHigh = cv2.inRange(imgHSV, np.array([165, 135, 135]), np.array([179, 255, 255]))
imgThresh = cv2.add(imgThreshLow, imgThreshHigh)
imgThresh = cv2.GaussianBlur(imgThresh, (3, 3), 2)
imgThresh = cv2.dilate(imgThresh, np.ones((5, 5), np.uint8))
imgThresh = cv2.erode(imgThresh, np.ones((5, 5), np.uint8))
intRows, intColumns = imgThresh.shape
circles = cv2.HoughCircles(imgThresh, cv2.HOUGH_GRADIENT, 5,
intRows / 4) # fill variable circles with all circles in the processed image
if circles is not None: # this line is necessary to keep program from crashing on next line if no circles were found
for circle in circles[0]: # for each circle
x, y, radius = circle # break out x, y, and radius
print("ball position x = " + str(x) + ", y = " + str(y) + ", radius = " + str(
radius)) # print ball position and radius
cv2.circle(imgOriginal, (x, y), 3, (0, 255, 0),
-1) # draw small green circle at center of detected object
cv2.circle(imgOriginal, (x, y), radius, (0, 0, 255), 3) # draw red circle around the detected object
# end for
# end if
cv2.namedWindow("imgOriginal", cv2.WINDOW_AUTOSIZE) # create windows, use WINDOW_AUTOSIZE for a fixed window size
cv2.namedWindow("imgThresh", cv2.WINDOW_AUTOSIZE) # or use WINDOW_NORMAL to allow window resizing
cv2.imshow("imgOriginal", imgOriginal) # show windows
cv2.imshow("imgThresh", imgThresh)
# end while
cv2.destroyAllWindows() # remove windows from memory
return
if __name__ == '__main__':
main()