def main():
parser = arg.parser
parser = argparse.ArgumentParser(
description='Estimate areas of furigana in segmented raw manga scan.')
parser.add_argument('infile',
help='Input (color) raw Manga scan image to clean.')
parser.add_argument(
'segmentation_file',
help=
'Input 3 channel segmentation of input image, with text areas in R channel.'
)
parser.add_argument('-o',
'--output',
dest='outfile',
help='Output (color) cleaned raw manga scan image.')
#parser.add_argument('-m','--mask', dest='mask', default=None, help='Output (binary) mask for non-graphical regions.')
#parser.add_argument('-b','--binary', dest='binary', default=None, help='Binarized version of input file.')
parser.add_argument(
'-v',
'--verbose',
help='Verbose operation. Print status messages during processing',
action="store_true")
parser.add_argument(
'--display',
help='Display output using OPENCV api and block program exit.',
action="store_true")
parser.add_argument('-d',
'--debug',
help='Overlay input image into output.',
action="store_true")
#parser.add_argument('--sigma', help='Std Dev of gaussian preprocesing filter.',type=float,default=None)
#parser.add_argument('--segment_threshold', help='Threshold for nonzero pixels to separete vert/horiz text lines.',type=int,default=1)
arg.value = parser.parse_args()
infile = arg.string_value('infile')
segmentation_file = arg.string_value('segmentation_file')
outfile = arg.string_value('outfile',
default_value=infile + '.furigana.png')
if not os.path.isfile(infile) or not os.path.isfile(segmentation_file):
print(
'Please provide a regular existing input file. Use -h option for help.'
)
sys.exit(-1)
if arg.boolean_value('verbose'):
print('\tProcessing file ' + infile)
print('\tWith segmentation file ' + segmentation_file)
print('\tAnd generating output ' + outfile)
furigana = estimate_furigana_from_files(infile, segmentation_file)
imsave(outfile, furigana)
if arg.boolean_value('display'):
cv2.imshow('Furigana', furigana)
if cv2.waitKey(0) == 27:
cv2.destroyAllWindows()
cv2.destroyAllWindows()
def main():
parser = arg.parser
parser = argparse.ArgumentParser(description='Segment raw Manga scan image.')
parser.add_argument('infile', help='Input (color) raw Manga scan image to clean.')
parser.add_argument('-o','--output', dest='outfile', help='Output (color) cleaned raw manga scan image.')
#parser.add_argument('-m','--mask', dest='mask', default=None, help='Output (binary) mask for non-graphical regions.')
#parser.add_argument('-b','--binary', dest='binary', default=None, help='Binarized version of input file.')
parser.add_argument('-v','--verbose', help='Verbose operation. Print status messages during processing', action="store_true")
parser.add_argument('--display', help='Display output using OPENCV api and block program exit.', action="store_true")
parser.add_argument('-d','--debug', help='Overlay input image into output.', action="store_true")
parser.add_argument('--sigma', help='Std Dev of gaussian preprocesing filter.',type=float,default=None)
parser.add_argument('--binary_threshold', help='Binarization threshold value from 0 to 255.',type=float,default=defaults.BINARY_THRESHOLD)
parser.add_argument('--furigana', help='Attempt to suppress furigana characters to improve OCR.', action="store_true")
parser.add_argument('--segment_threshold', help='Threshold for nonzero pixels to separete vert/horiz text lines.',type=int,default=defaults.SEGMENTATION_THRESHOLD)
parser.add_argument('--additional_filtering', help='Attempt to filter false text positives by histogram processing.', action="store_true")
arg.value = parser.parse_args()
infile = arg.string_value('infile')
outfile = arg.string_value('outfile', default_value=infile + '.segmented.png')
binary_outfile = infile + '.binary.png'
if not os.path.isfile(infile):
print('Please provide a regular existing input file. Use -h option for help.')
sys.exit(-1)
if arg.boolean_value('verbose'):
print('\tProcessing file ' + infile)
print('\tGenerating output ' + outfile)
segmented = segment_image_file(infile)
imsave(outfile,segmented)
#cv2.imwrite(outfile,segmented)
#if binary is not None:
# cv2.imwrite(binary_outfile, binary)
if arg.boolean_value('display'):
cv2.imshow('Segmented', segmented)
#cv2.imshow('Cleaned',cleaned)
#if args.mask is not None:
# cv2.imshow('Mask',mask)
if cv2.waitKey(0) == 27:
cv2.destroyAllWindows()
cv2.destroyAllWindows()
def main():
parser = arg.parser
parser = argparse.ArgumentParser(description='Segment raw Manga scan image.')
parser.add_argument('infile', help='Input (color) raw Manga scan image to clean.')
parser.add_argument('-o','--output', dest='outfile', help='Output (color) cleaned raw manga scan image.')
#parser.add_argument('-m','--mask', dest='mask', default=None, help='Output (binary) mask for non-graphical regions.')
#parser.add_argument('-b','--binary', dest='binary', default=None, help='Binarized version of input file.')
parser.add_argument('-v','--verbose', help='Verbose operation. Print status messages during processing', action="store_true")
parser.add_argument('--display', help='Display output using OPENCV api and block program exit.', action="store_true")
parser.add_argument('-d','--debug', help='Overlay input image into output.', action="store_true")
parser.add_argument('--sigma', help='Std Dev of gaussian preprocesing filter.',type=float,default=None)
parser.add_argument('--binary_threshold', help='Binarization threshold value from 0 to 255.',type=float,default=defaults.BINARY_THRESHOLD)
parser.add_argument('--furigana', help='Attempt to suppress furigana characters to improve OCR.', action="store_true")
parser.add_argument('--segment_threshold', help='Threshold for nonzero pixels to separete vert/horiz text lines.',type=int,default=defaults.SEGMENTATION_THRESHOLD)
parser.add_argument('--additional_filtering', help='Attempt to filter false text positives by histogram processing.', action="store_true")
arg.value = parser.parse_args()
infile = arg.string_value('infile')
outfile = arg.string_value('outfile', default_value=infile + '.segmented.png')
binary_outfile = infile + '.binary.png'
if not os.path.isfile(infile):
print 'Please provide a regular existing input file. Use -h option for help.'
sys.exit(-1)
if arg.boolean_value('verbose'):
print '\tProcessing file ' + infile
print '\tGenerating output ' + outfile
segmented = segment_image_file(infile)
imsave(outfile,segmented)
#cv2.imwrite(outfile,segmented)
#if binary is not None:
# cv2.imwrite(binary_outfile, binary)
if arg.boolean_value('display'):
cv2.imshow('Segmented', segmented)
#cv2.imshow('Cleaned',cleaned)
#if args.mask is not None:
# cv2.imshow('Mask',mask)
if cv2.waitKey(0) == 27:
cv2.destroyAllWindows()
cv2.destroyAllWindows()
def main():
parser = arg.parser
parser = argparse.ArgumentParser(description='Basic OCR on raw manga scan.')
parser.add_argument('infile', help='Input (color) raw Manga scan image to clean.')
parser.add_argument('-o','--output', dest='outfile', help='Output (color) cleaned raw manga scan image.')
parser.add_argument('-v','--verbose', help='Verbose operation. Print status messages during processing', action="store_true")
#parser.add_argument('-d','--debug', help='Overlay input image into output.', action="store_true")
parser.add_argument('--sigma', help='Std Dev of gaussian preprocesing filter.',type=float,default=None)
parser.add_argument('--binary_threshold', help='Binarization threshold value from 0 to 255.',type=int,default=defaults.BINARY_THRESHOLD)
parser.add_argument('--furigana', help='Attempt to suppress furigana characters to improve OCR.', action="store_true")
parser.add_argument('--segment_threshold', help='Threshold for nonzero pixels to separete vert/horiz text lines.',type=int,default=defaults.SEGMENTATION_THRESHOLD)
arg.value = parser.parse_args()
infile = arg.string_value('infile')
outfile = arg.string_value('outfile', default_value=infile + '.html')
if not os.path.isfile(infile):
print ('Please provide a regular existing input file. Use -h option for help.')
sys.exit(-1)
if arg.boolean_value('verbose'):
print ('\tProcessing file ' + infile)
print ('\tGenerating output ' + outfile)
img = cv2.imread(infile)
gray = clean.grayscale(img)
binary = clean.binarize(gray)
segmented = segmentation.segment_image_file(infile)
components = cc.get_connected_components(segmented)
#perhaps do more strict filtering of connected components because sections of characters
#will not be dripped from run length smoothed areas? Yes. Results quite good.
#filtered = cc.filter_by_size(img,components,average_size*100,average_size*1)
blurbs = ocr_on_bounding_boxes(binary, components)
for blurb in blurbs:
print (str(blurb.x)+','+str(blurb.y)+' '+str(blurb.w)+'x'+str(blurb.h)+' '+ str(blurb.confidence)+'% :'+ blurb.text)
def main():
parser = arg.parser
parser = argparse.ArgumentParser(description='Basic OCR on raw manga scan.')
parser.add_argument('infile', help='Input (color) raw Manga scan image to clean.')
parser.add_argument('-o','--output', dest='outfile', help='Output (color) cleaned raw manga scan image.')
parser.add_argument('-v','--verbose', help='Verbose operation. Print status messages during processing', action="store_true")
#parser.add_argument('-d','--debug', help='Overlay input image into output.', action="store_true")
parser.add_argument('--sigma', help='Std Dev of gaussian preprocesing filter.',type=float,default=None)
parser.add_argument('--binary_threshold', help='Binarization threshold value from 0 to 255.',type=int,default=defaults.BINARY_THRESHOLD)
parser.add_argument('--furigana', help='Attempt to suppress furigana characters to improve OCR.', action="store_true")
parser.add_argument('--segment_threshold', help='Threshold for nonzero pixels to separete vert/horiz text lines.',type=int,default=defaults.SEGMENTATION_THRESHOLD)
arg.value = parser.parse_args()
infile = arg.string_value('infile')
outfile = arg.string_value('outfile', default_value=infile + '.html')
if not os.path.isfile(infile):
print 'Please provide a regular existing input file. Use -h option for help.'
sys.exit(-1)
if arg.boolean_value('verbose'):
print '\tProcessing file ' + infile
print '\tGenerating output ' + outfile
img = cv2.imread(infile)
gray = clean.grayscale(img)
binary = clean.binarize(gray)
segmented = segmentation.segment_image_file(infile)
components = cc.get_connected_components(segmented)
#perhaps do more strict filtering of connected components because sections of characters
#will not be dripped from run length smoothed areas? Yes. Results quite good.
#filtered = cc.filter_by_size(img,components,average_size*100,average_size*1)
blurbs = ocr_on_bounding_boxes(binary, components)
for blurb in blurbs:
print str(blurb.x)+','+str(blurb.y)+' '+str(blurb.w)+'x'+str(blurb.h)+' '+ str(blurb.confidence)+'% :'+ blurb.text
def main():
parser = arg.parser
parser = argparse.ArgumentParser(description='Estimate areas of furigana in segmented raw manga scan.')
parser.add_argument('infile', help='Input (color) raw Manga scan image to clean.')
parser.add_argument('segmentation_file', help='Input 3 channel segmentation of input image, with text areas in R channel.')
parser.add_argument('-o','--output', dest='outfile', help='Output (color) cleaned raw manga scan image.')
#parser.add_argument('-m','--mask', dest='mask', default=None, help='Output (binary) mask for non-graphical regions.')
#parser.add_argument('-b','--binary', dest='binary', default=None, help='Binarized version of input file.')
parser.add_argument('-v','--verbose', help='Verbose operation. Print status messages during processing', action="store_true")
parser.add_argument('--display', help='Display output using OPENCV api and block program exit.', action="store_true")
parser.add_argument('-d','--debug', help='Overlay input image into output.', action="store_true")
#parser.add_argument('--sigma', help='Std Dev of gaussian preprocesing filter.',type=float,default=None)
#parser.add_argument('--segment_threshold', help='Threshold for nonzero pixels to separete vert/horiz text lines.',type=int,default=1)
arg.value = parser.parse_args()
infile = arg.string_value('infile')
segmentation_file = arg.string_value('segmentation_file')
outfile = arg.string_value('outfile',default_value=infile + '.furigana.png')
if not os.path.isfile(infile) or not os.path.isfile(segmentation_file):
print 'Please provide a regular existing input file. Use -h option for help.'
sys.exit(-1)
if arg.boolean_value('verbose'):
print '\tProcessing file ' + infile
print '\tWith segmentation file ' + segmentation_file
print '\tAnd generating output ' + outfile
furigana = estimate_furigana_from_files(infile, segmentation_file)
imsave(outfile,furigana)
if arg.boolean_value('display'):
cv2.imshow('Furigana', furigana)
if cv2.waitKey(0) == 27:
cv2.destroyAllWindows()
cv2.destroyAllWindows()
parser.add_argument('--sigma',
help='Std Dev of gaussian preprocesing filter.',
type=float,
default=None)
parser.add_argument('--binary_threshold',
help='Binarization threshold value from 0 to 255.',
type=int,
default=defaults.BINARY_THRESHOLD)
#parser.add_argument('--segment_threshold', help='Threshold for nonzero pixels to separete vert/horiz text lines.',type=int,default=1)
parser.add_argument(
'--additional_filtering',
help='Attempt to filter false text positives by histogram processing.',
action="store_true")
arg.value = parser.parse_args()
infile = arg.string_value('infile')
outfile = arg.string_value('outfile',
default_value=infile + '.text_areas.png')
if not os.path.isfile(infile):
print(
'Please provide a regular existing input file. Use -h option for help.'
)
sys.exit(-1)
img = cv2.imread(infile)
gray = clean.grayscale(img)
binary_threshold = arg.integer_value(
'binary_threshold', default_value=defaults.BINARY_THRESHOLD)
if arg.boolean_value('verbose'):
print('Binarizing with threshold value of ' + str(binary_threshold))
return temp_mask
if __name__ == '__main__':
parser = arg.parser
parser = argparse.ArgumentParser(description='Clean raw Manga scan image.')
parser.add_argument('infile', help='Input (color) raw Manga scan image to clean.')
parser.add_argument('-o','--output', dest='outfile', help='Output (color) cleaned raw manga scan image.')
parser.add_argument('-m','--mask', dest='mask', default=None, help='Output (binary) mask for non-graphical regions.')
parser.add_argument('-b','--binary', dest='binary', default=None, help='Binarized version of input file.')
parser.add_argument('-v','--verbose', help='Verbose operation. Print status messages during processing', action="store_true")
parser.add_argument('--display', help='Display output using OPENCV api and block program exit.', action="store_true")
arg.value = parser.parse_args()
infile = arg.string_value('infile')
outfile = arg.string_value('outfile',default_value=infile + '.cleaned.png')
binary_outfile = arg.string_value('binary',default_value=infile + '.binary.png')
mask = arg.boolean_value('mask')
if not os.path.isfile(infile):
print 'Please provide a regular existing input file. Use -h option for help.'
sys.exit(-1)
if arg.boolean_value('verbose'):
print '\tProcessing file ' + infile
print '\tGenerating output ' + outfile
(binary,mask,cleaned) = clean_image_file(infile)
cv2.imwrite(outfile,cleaned)
#parser.add_argument('--segment_threshold', help='Threshold for nonzero pixels to separete vert/horiz text lines.',type=int,default=1)
parser.add_argument(
'--additional_filtering',
help='Attempt to filter false text positives by histogram processing.',
action="store_true")
parser.add_argument('--bounding_boxes',
help="added bounding boxes for ocr regions",
type=bool,
default=False)
parser.add_argument('--target_lang',
help="target language of translation,",
type=str,
default="en")
arg.value = parser.parse_args()
infile = arg.string_value('infile')
outfile = arg.string_value('outfile',
default_value=infile + '.text_areas.png')
if not os.path.isfile(infile):
print(
'Please provide a regular existing input file. Use -h option for help.'
)
sys.exit(-1)
img = cv2.imread(infile)
translate_page(img,
boxes=arg.value.bounding_boxes,
target_lang=arg.string_value('target_lang'))
cv2.imwrite(arg.string_value('outfile'), img)
cv2.imshow("Hi", img)
cv2.waitKey(0)
'--binary',
dest='binary',
default=None,
help='Binarized version of input file.')
parser.add_argument(
'-v',
'--verbose',
help='Verbose operation. Print status messages during processing',
action="store_true")
parser.add_argument(
'--display',
help='Display output using OPENCV api and block program exit.',
action="store_true")
arg.value = parser.parse_args()
infile = arg.string_value('infile')
outfile = arg.string_value('outfile',
default_value=infile + '.cleaned.png')
binary_outfile = arg.string_value('binary',
default_value=infile + '.binary.png')
mask = arg.boolean_value('mask')
if not os.path.isfile(infile):
print(
'Please provide a regular existing input file. Use -h option for help.'
)
sys.exit(-1)
if arg.boolean_value('verbose'):
print('\tProcessing file ' + infile)
print('\tGenerating output ' + outfile)
parser = arg.parser
parser = argparse.ArgumentParser(description='Generate HTML annotation for raw manga scan with detected OCR\'d text.')
parser.add_argument('infile', help='Input (color) raw Manga scan image to annoate.')
parser.add_argument('-o','--output', dest='outfile', help='Output html file.')
parser.add_argument('-v','--verbose', help='Verbose operation. Print status messages during processing', action="store_true")
parser.add_argument('--display', help='Display output using OPENCV api and block program exit.', action="store_true")
parser.add_argument('--furigana', help='Attempt to suppress furigana characters which interfere with OCR.', action="store_true")
#parser.add_argument('-d','--debug', help='Overlay input image into output.', action="store_true")
parser.add_argument('--sigma', help='Std Dev of gaussian preprocesing filter.',type=float,default=None)
parser.add_argument('--binary_threshold', help='Binarization threshold value from 0 to 255.',type=int,default=defaults.BINARY_THRESHOLD)
#parser.add_argument('--segment_threshold', help='Threshold for nonzero pixels to separete vert/horiz text lines.',type=int,default=1)
parser.add_argument('--additional_filtering', help='Attempt to filter false text positives by histogram processing.', action="store_true")
arg.value = parser.parse_args()
infile = arg.string_value('infile')
outfile = arg.string_value('outfile',default_value=infile + '.text_areas.png')
if not os.path.isfile(infile):
print 'Please provide a regular existing input file. Use -h option for help.'
sys.exit(-1)
img = cv2.imread(infile)
gray = clean.grayscale(img)
binary_threshold=arg.integer_value('binary_threshold',default_value=defaults.BINARY_THRESHOLD)
if arg.boolean_value('verbose'):
print 'Binarizing with threshold value of ' + str(binary_threshold)
inv_binary = cv2.bitwise_not(clean.binarize(gray, threshold=binary_threshold))
binary = clean.binarize(gray, threshold=binary_threshold)
segmented_image = seg.segment_image(gray)