def main():
parser = argparse.ArgumentParser(description='Visualizes the line for hough transform.')
parser.add_argument('filename')
args = parser.parse_args()
# img = cv2.imread(args.filename, cv2.IMREAD_GRAYSCALE)
img = cv2.imread(args.filename)
cv2.imshow('input', img)
blur_image = SmoothImage('Blur', img, average_filter_size=5, gaussian_filter_size=1, median_filter_size=1, bilateral_filter_size=1)
edge_finder = EdgeFinder('Edge', blur_image.processedImage(), min_threshold=28, max_threshold=115)
blur_image.addProcessor (edge_finder.onImageChange)
# will inforce refresh for all pipeline.
blur_image.refresh()
cv2.waitKey(0)
# print ("Edge parameters: %s")
# print ("GaussianBlur Filter Size: %f" % edge_finder.filterSize())
# print ("Threshold2: %f" % edge_finder.threshold2())
(head, tail) = os.path.split(args.filename)
(root, ext) = os.path.splitext(tail)
smoothed_filename = os.path.join("output_images", root + "-smoothed" + ext)
edge_filename = os.path.join("output_images", root + "-edges" + ext)
cv2.imwrite(smoothed_filename, edge_finder.processedImage())
cv2.imwrite(edge_filename, edge_finder.processedImage())
cv2.destroyAllWindows()
def main():
parser = argparse.ArgumentParser(
description='Visualizes the line hough transform.')
parser.add_argument('filename')
args = parser.parse_args()
img = cv2.imread(args.filename, cv2.IMREAD_GRAYSCALE)
cv2.imshow('input', img)
edge_finder = EdgeFinder(img,
filter_size=13,
threshold1=28,
threshold2=115)
print "Edge parameters:"
print "GaussianBlur Filter Size: %f" % edge_finder.filterSize()
print "Threshold1: %f" % edge_finder.threshold1()
print "Threshold2: %f" % edge_finder.threshold2()
(head, tail) = os.path.split(args.filename)
(root, ext) = os.path.splitext(tail)
smoothed_filename = os.path.join("output_images", root + "-smoothed" + ext)
edge_filename = os.path.join("output_images", root + "-edges" + ext)
cv2.imwrite(smoothed_filename, edge_finder.smoothedImage())
cv2.imwrite(edge_filename, edge_finder.edgeImage())
cv2.destroyAllWindows()
def main():
# parser for the command line input (automaticlly generates help)
parser = argparse.ArgumentParser(
description='Visualizes the line for hough transform.')
parser.add_argument('filename')
# save the arguments
args = parser.parse_args()
# read the image given as an argument
img = cv2.imread(args.filename)
# create the edge finding and gui class
edge_finder = EdgeFinder(img, kernel_size=5)
cv2.destroyAllWindows()
def main():
__init_logger()
parser = argparse.ArgumentParser(description='Visualizes the line for hough transform.')
parser.add_argument('filename')
args = parser.parse_args()
# img = cv2.imread(args.filename, cv2.IMREAD_GRAYSCALE)
img = cv2.imread(args.filename)
cv2.imshow('input', img)
blur_image = SmoothImage('Bluring Config', img, average_filter_size=5, gaussian_filter_size=1, median_filter_size=1, bilateral_filter_size=1)
edge_finder = EdgeFinder('Edge Finder Config', blur_image.processedImage(), min_threshold=28, max_threshold=115)
blur_image.addProcessor (edge_finder.onImageChange)
region_mask = RegionMask('Region Masked dimensions', edge_finder.processedImage())
edge_finder.addProcessor (region_mask.onImageChange)
hough_lines = HoughLines('Hough Lines Config', region_mask.processedImage())
region_mask.addProcessor (hough_lines.onImageChange)
image_blender = ImageBlender('Image Mix Config', hough_lines.processedImage(), img)
hough_lines.addProcessor (image_blender.onImageChange)
# will inforce refresh for all pipeline.
blur_image.refresh()
cv2.waitKey(0)
print ("Adjust the parameters as desired. Hit any key to close. Your configuration will be in Tuning_info_out.log")
logger.info("Configuration parameters:\n %s %s %s %s %s", blur_image, edge_finder, region_mask, hough_lines, image_blender)
logger.debug("Configuration parameters:\n %s %s %s %s %s", blur_image, edge_finder, region_mask, hough_lines, image_blender)
(head, tail) = os.path.split(args.filename)
(root, ext) = os.path.splitext(tail)
smoothed_filename = os.path.join("output_images", root + blur_image.name() + ext)
edge_filename = os.path.join("output_images", root + edge_finder.name() + ext)
maskeed_filename = os.path.join("output_images", root + region_mask.name() + ext)
hough_filename = os.path.join("output_images", root + hough_lines.name() + ext)
blended_filename = os.path.join("output_images", root + image_blender.name() + ext)
cv2.imwrite(smoothed_filename, blur_image.processedImage())
cv2.imwrite(edge_filename, edge_finder.processedImage())
cv2.imwrite(maskeed_filename, region_mask.processedImage())
cv2.imwrite(hough_filename, hough_lines.processedImage())
cv2.imwrite(blended_filename, image_blender.processedImage())
cv2.destroyAllWindows()
def main():
parser = argparse.ArgumentParser(
description='Visualizes the line for hough transform.')
parser.add_argument('filename')
args = parser.parse_args()
file_list = os.listdir(args.filename)
for image_name in file_list:
print(f'****************{image_name}*******************')
initial_img = mpimg.imread(args.filename + image_name)
edge_finder = EdgeFinder(initial_img,
filter_size=13,
threshold1=28,
threshold2=115)
print("Edge parameters:")
print("GaussianBlur Filter Size: %f" % edge_finder.filterSize())
print("Threshold1: %f" % edge_finder.threshold1())
print("Threshold2: %f" % edge_finder.threshold2())
print("Rho: %f" % edge_finder.rho())
print("Theta: %f" % edge_finder.theta())
print("Points Threshold: %f" % edge_finder.threshold())
print("max_line_gap: %f" % edge_finder.max_line_gap())
print("min_line_len: %f" % edge_finder.min_line_len())
(head, tail) = (args.filename, image_name)
(root, ext) = os.path.splitext(tail)
final_filename = os.path.join("output_images", root + "-final" + ext)
edge_filename = os.path.join("output_images", root + "-edges" + ext)
cv2.imwrite(edge_filename, edge_finder.edgeImage())
cv2.imwrite(final_filename, edge_finder.finalImage())
cv2.destroyAllWindows()