def main():
compute_and_render([
AABBoxParams(get_image_path('mercedesspritesheets.png'), 132, 236),
AABBoxParams(get_image_path('trump_run.png'), 230, 290),
AABBoxParams(
get_image_path('volt_sprite_sheet_by_kwelfury-d5hx008.png'),
632, 676)
])
def main():
im = cv2.imread(str(get_image_path('balls.png')))
imgray = cv2.cvtColor(im, cv2.COLOR_BGR2GRAY)
cv2.imshow("imgray", imgray)
# bug: marrant la valeur de threshold est sensible ...
# surement lie a la compression ou format de l'image
minThreshold = 121 # valeur dans le tuto = 127
maxThreshold = 255
ret, thresh = cv2.threshold(imgray, minThreshold, maxThreshold, 0)
cv2.imshow("thresh", thresh)
contours, hierarchy = cv2.findContours(thresh, cv2.RETR_TREE,
cv2.CHAIN_APPROX_SIMPLE)
logger.info(f"len(contours): {len(contours)}")
# coef_approx = 0.0 # suit exactement les contours detectes
coef_approx = 0.01 # suit (presque) les contours detectes
# coef_approx = 0.10 # affiche un rectanble englobant
for h, cnt in enumerate(contours):
approx = cv2.approxPolyDP(cnt, coef_approx * cv2.arcLength(cnt, True),
True)
logger.info(f"len(approx): {len(approx)}")
cv2.drawContours(im, [approx], -1, (0, 255, 0), 3)
cv2.imshow("approx", im)
while True:
k = cv2.waitKey(1) & 0xFF
if k == 27:
break
def main():
im = cv2.imread(str(get_image_path('test.jpg')))
imgray = cv2.cvtColor(im, cv2.COLOR_BGR2GRAY)
ret, thresh = cv2.threshold(imgray, 127, 255, 0)
contours, hierarchy = cv2.findContours(thresh, cv2.RETR_TREE,
cv2.CHAIN_APPROX_SIMPLE)
logger.info(f"nombre de contours: {len(contours)}")
cnt = contours[0]
logger.info(f"nombre de points dans le contour 1: {len(cnt)}")
cv2.drawContours(im, contours, -1, (0, 255, 0), 3)
cv2.imshow("contours - borders", im)
cv2.drawContours(im, contours, -1, (0, 0, 255), -1)
cv2.imshow("contours - fill", im)
while True:
k = cv2.waitKey(1) & 0xFF
if k == 27:
break
def main():
im = cv2.imread(str(get_image_path('balls.png')))
imgray = cv2.cvtColor(im, cv2.COLOR_BGR2GRAY)
cv2.imshow("imgray", imgray)
# bug: marrant la valeur de threshold est sensible ...
# surement lie a la compression ou format de l'image
minThreshold = 121 # valeur dans le tuto = 127
maxThreshold = 255
ret, thresh = cv2.threshold(imgray, minThreshold, maxThreshold, 0)
cv2.imshow("thresh", thresh)
contours, hierarchy = cv2.findContours(thresh, cv2.RETR_TREE,
cv2.CHAIN_APPROX_SIMPLE)
logger.info(f"len(contours): {len(contours)}")
for h, cnt in enumerate(contours):
mask = np.zeros(imgray.shape, np.uint8)
cv2.drawContours(mask, [cnt], 0, 255, -1)
cv2.mean(im, mask=mask)
cv2.imshow("Masks", mask)
cv2.waitKey(0)
def main():
im = cv2.imread(str(get_image_path('balls.png')))
imgray = cv2.cvtColor(im, cv2.COLOR_BGR2GRAY)
cv2.imshow("imgray", imgray)
# bug: marrant la valeur de threshold est sensible ...
# surement lie a la compression ou format de l'image
min_threshold = 121 # valeur dans le tuto = 127
max_threshold = 255
ret, thresh = cv2.threshold(imgray, min_threshold, max_threshold, 0)
cv2.imshow("thresh", thresh)
contours, hierarchy = cv2.findContours(thresh, cv2.RETR_TREE,
cv2.CHAIN_APPROX_SIMPLE)
logger.info(f"len(contours): {len(contours)}")
# coef_approx = 0.0 # suit exactement les contours detectes
coef_approx = 0.01 # suit (presque) les contours detectes
# coef_approx = 0.10 # affiche un rectanble englobant
for h, cnt in enumerate(contours):
approx = cv2.approxPolyDP(cnt, coef_approx * cv2.arcLength(cnt, True),
True)
print(f"len(approx): {len(approx)}")
cv2.drawContours(im, [approx], -1, (0, 255, 0), 3)
cv2.imshow("approx", im)
# url: http://docs.opencv.org/3.0-beta/doc/py_tutorials/py_gui/py_trackbar/py_trackbar.html
def nothing(_x):
pass
# height, width = im.shape[:2]
# Create a black image, a window
cv2.namedWindow('image')
# create trackbars for color change
cv2.createTrackbar('minThreshold', 'image', 1, 255, nothing)
cv2.createTrackbar('maxThreshold', 'image', 1, 255, nothing)
# create switch for ON/OFF functionality
switch = '0 : OFF \n1 : ON'
cv2.createTrackbar(switch, 'image', 0, 1, nothing)
while True:
k = cv2.waitKey(1) & 0xFF
if k == 27:
break
# get current positions of four trackbars
min_threshold = cv2.getTrackbarPos('minThreshold', 'image')
max_threshold = cv2.getTrackbarPos('maxThreshold', 'image')
s = cv2.getTrackbarPos(switch, 'image')
if s == 0:
img = imgray
else:
logger.info(
f"minThreshold={min_threshold}, maxThreshold={max_threshold}")
ret, thresh = cv2.threshold(imgray, min_threshold, max_threshold, 0)
img = thresh
cv2.imshow('image', img)
cv2.destroyAllWindows()