import argparse
parser = argparse.ArgumentParser(description="Interactively experiment with HoughLinesP parameters.")
parser.add_argument("file", help="image to threshold", type=str)
# add a command line parameter for every slider parameter
cvparams.addCommandLineArgs(cvparam_dict, parser)
args = parser.parse_args()
cvparams.setValuesFromCommandLine(cvparam_dict, args)
from glob import glob
for filename in glob(args.file):
img = get_image(filename)
h, w = img.shape[:2]
img = cv2.GaussianBlur(img, (5, 5), 0)
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
edges = cv2.Canny(gray, 600, 600, apertureSize=5)
cv2.imshow("results", img) # window needs to exist before we add sliders
cvparams.addSlidersToWindow(cvparam_dict, "results")
updateImage()
ch = cv2.waitKey()
if ch == 27:
break
cv2.destroyAllWindows()
cvparams.dump(cvparam_dict)
parser = argparse.ArgumentParser(
description=
"Interactively experiment with morphology gradient parameters.")
parser.add_argument('file', help='image to threshold', type=str)
# add a command line parameter for every slider parameter
cvparam.addCommandLineArgs(cvparam_dict, parser)
args = parser.parse_args()
cvparam.setValuesFromCommandLine(cvparam_dict, args)
from glob import glob
for filename in glob(args.file):
img = cv2.imread(filename)
assert img is not None, "File " + args.file + " was not found."
# img = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
h, w = img.shape[:2]
cv2.imshow('results',
img) # window needs to exist before we add sliders
cvparam.addSlidersToWindow(cvparam_dict, "results")
updateImage()
ch = cv2.waitKey()
if ch == 27:
break
cv2.destroyAllWindows()
# print selected parameters to console
cvparam.dump(cvparam_dict)
"Color Kernel Size", 150, 109, updateImage)
import argparse
parser = argparse.ArgumentParser(
description="Apply bilateral (edge preserving) blur operator.")
parser.add_argument('file', help='image to blur (wildcards ok)', type=str)
# add a command line parameter for every slider parameter
cvparams.addCommandLineArgs(cvparam_dict, parser)
args = parser.parse_args()
cvparams.setValuesFromCommandLine(cvparam_dict, args)
from glob import glob
for filename in glob(args.file):
img = cv2.imread(filename)
assert img is not None, "File " + args.file + " was not found."
h, w = img.shape[:2]
cv2.imshow('results',
img) # window needs to exist before we add sliders
cvparams.addSlidersToWindow(cvparam_dict, "results")
updateImage()
ch = cv2.waitKey()
if ch == 27:
break
cv2.destroyAllWindows()
cvparams.dump(cvparam_dict)
cvparam_dict['blockSize'] = cvparam.kernelparam("Block Size (3,5,..)", 21, 5, updateImage)
import argparse
parser = argparse.ArgumentParser(description="Interactively experiment with adaptiveThreshold parameters.")
parser.add_argument('file', help='image to threshold', type=str)
# add a command line parameter for every slider parameter
cvparam.addCommandLineArgs(cvparam_dict, parser)
args = parser.parse_args()
cvparam.setValuesFromCommandLine(cvparam_dict, args)
from glob import glob
for filename in glob(args.file):
img = cv2.imread(filename)
assert img is not None, "File " + args.file + " was not found."
img = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
h, w = img.shape[:2]
cv2.imshow('results', img) # window needs to exist before we add sliders
cvparam.addSlidersToWindow(cvparam_dict, "results")
updateImage()
ch = cv2.waitKey()
if ch == 27:
break
cv2.destroyAllWindows()
# print selected parameters to console
cvparam.dump(cvparam_dict)
