def process_folder(f):
global args
dst = f.replace("_polygons.json", f"_label{args.id_type}s.png")
# do the conversion
try:
json2labelImg(f, dst, args.id_type)
except:
tqdm.write("Failed to convert: {}".format(f))
raise
if args.instance:
dst = f.replace("_polygons.json", f"_instance{args.id_type}s.png")
# do the conversion
# try:
json2instanceImg(f, dst, args.id_type)
# except:
# tqdm.write("Failed to convert: {}".format(f))
# raise
if args.color:
# create the output filename
dst = f.replace("_polygons.json", f"_labelColors.png")
# do the conversion
try:
json2labelImg(f, dst, 'color')
except:
tqdm.write("Failed to convert: {}".format(f))
raise
def main():
# Where to look for Cityscapes
if 'CITYSCAPES_DATASET_INDIA' in os.environ:
cityscapesPath = os.environ['CITYSCAPES_DATASET_INDIA']
else:
cityscapesPath = os.path.join(
os.path.dirname(os.path.realpath(__file__)), '..', '..')
# how to search for all ground truth
searchFine = os.path.join(cityscapesPath, "gtFine", "*", "*",
"*_gt*_polygons.json")
searchCoarse = os.path.join(cityscapesPath, "gtCoarse", "*", "*",
"*_gt*_polygons.json")
# search files
filesFine = glob.glob(searchFine)
filesFine.sort()
filesCoarse = glob.glob(searchCoarse)
filesCoarse.sort()
# concatenate fine and coarse
#files = filesFine + filesCoarse
files = filesFine # use this line if fine is enough for now.
# quit if we did not find anything
if not files:
printError("Did not find any files. Please consult the README.")
# a bit verbose
print("Processing {} annotation files".format(len(files)))
# iterate through files
progress = 0
print("Progress: {:>3} %".format(progress * 100 / len(files)), end=' ')
for f in files:
# create the output filename
dst = f.replace("_polygons.json", "_labelTrainIds.png")
# do the conversion
# encoding can be set to
# - "ids" : classes are encoded using the regular label IDs
# - "trainIds" : classes are encoded using the training IDs
# - "color" : classes are encoded using the corresponding colors
try:
json2labelImg(f, dst, "trainIds")
except:
print("Failed to convert: {}".format(f))
raise
# status
progress += 1
print("\rProgress: {:>3} %".format(progress * 100 / len(files)),
end=' ')
sys.stdout.flush()
def main():
# Where to look for Cityscapes
if 'CITYSCAPES_DATASET' in os.environ:
cityscapesPath = os.environ['CITYSCAPES_DATASET']
else:
cityscapesPath = os.path.join(
os.path.dirname(os.path.realpath(__file__)), '..', '..')
# how to search for all ground truth
#searchFine = os.path.join( cityscapesPath , "gtFine" , "*" , "*" , "*_gt*_polygons.json" )
searchFine = os.path.join('/home/bctsai/gtFine/val', "*",
"*_gt*_polygons.json") ###CVPR_eval
searchCoarse = os.path.join(cityscapesPath, "gtCoarse", "*", "*",
"*_gt*_polygons.json")
# search files
#pdb.set_trace()
filesFine = glob.glob(searchFine)
filesFine.sort()
filesCoarse = glob.glob(searchCoarse)
filesCoarse.sort()
# concatenate fine and coarse
files = filesFine + filesCoarse
# files = filesFine # use this line if fine is enough for now.
# quit if we did not find anything
if not files:
printError("Did not find any files. Please consult the README.")
# a bit verbose
print("Processing {} annotation files".format(len(files)))
# iterate through files
progress = 0
print("Progress: {:>3} %".format(progress * 100 / len(files)), end=' ')
for f in files:
# create the output filename
dst = f.replace("_polygons.json", "_CVPR_eval.png")
# do the conversion
try:
json2labelImg(f, dst, "trainIds")
except:
print("Failed to convert: {}".format(f))
raise
# status
progress += 1
print("\rProgress: {:>3} %".format(progress * 100 / len(files)),
end=' ')
sys.stdout.flush()
def process_folder(f):
global args
dst = f.replace("_polygons.json", f"_label{args.id_type}s.png")
# do the conversion
try:
json2labelImg(f, dst, args.id_type)
except:
tqdm.write("Failed to convert: {}".format(f))
raise
if args.instance:
dst = f.replace("_polygons.json", f"_instance{args.id_type}s.png")
# do the conversion
# try:
json2instanceImg(f, dst, args.id_type)
# except:
# tqdm.write("Failed to convert: {}".format(f))
# raise
if args.color:
# create the output filename
dst = f.replace("_polygons.json", f"_labelColors.png")
# do the conversion
try:
json2labelImg(f, dst, 'color')
except:
tqdm.write("Failed to convert: {}".format(f))
raise
if args.panoptic and args.instance:
dst = f.replace("_polygons.json", f"_panoptic{args.id_type}s.png")
seg_anno = f.replace("_polygons.json", f"_label{args.id_type}s.png")
inst_anno = f.replace("_polygons.json",
f"_instance{args.id_type}s.png")
seg_tail = f"_gtFine_label{args.id_type}s.png"
inst_tail = f"_gtFine_instance{args.id_type}s.png"
pan_tail = f"_gtFine_panoptic{args.id_type}s.png"
seg_img = imread(seg_anno)
inst_img = imread(inst_anno)
sh = (seg_img.shape[0], seg_img.shape[1], 2)
twoch_img = np.zeros(sh, dtype=np.uint16)
twoch_img[:, :, 0] = seg_img
twoch_img[:, :, 1] = inst_img
write_png(seg_anno.replace(seg_tail, pan_tail), twoch_img)
def main():
# Where to look for Cityscapes
# Where to look for Cityscapes
# if 'CITYSCAPES_DATASET' in os.environ:
# cityscapesPath = os.environ['CITYSCAPES_DATASET']
# else:
# cityscapesPath = os.path.join(os.path.dirname(os.path.realpath(__file__)),'..','..')
cityscapesPath = os.path.expanduser('~/exp/datasets/cityscapes/gtFine_trainvaltest')
# how to search for all ground truth
searchFine = os.path.join( cityscapesPath , "gtFine" , "*" , "*" , "*_gt*_polygons.json" )
searchCoarse = os.path.join( cityscapesPath , "gtCoarse" , "*" , "*" , "*_gt*_polygons.json" )
# search files
filesFine = glob.glob( searchFine )
filesFine.sort()
filesCoarse = glob.glob( searchCoarse )
filesCoarse.sort()
# concatenate fine and coarse
files = filesFine + filesCoarse
# files = filesFine # use this line if fine is enough for now.
# quit if we did not find anything
if not files:
printError( "Did not find any files. Please consult the README." )
# a bit verbose
print "Processing {} annotation files".format(len(files))
# iterate through files
progress = 0
print "Progress: {:>3} %".format( progress * 100 / len(files) ) ,
for f in files:
# create the output filename
dst = f.replace( "_polygons.json" , "_labelTrainIds.png" )
# do the conversion
try:
json2labelImg( f , dst , "trainIds" )
except:
print "Failed to convert: {}".format(f)
raise
# status
progress += 1
print "\rProgress: {:>3} %".format( progress * 100 / len(files) ) ,
sys.stdout.flush()
def main():
# Where to look for Cityscapes
if 'CITYSCAPES_DATASET' in os.environ:
cityscapesPath = os.environ['CITYSCAPES_DATASET']
else:
cityscapesPath = 'data/cityscapes'
# how to search for all ground truth
searchFine = os.path.join(cityscapesPath, "gtFine", "*", "*",
"*_gt*_polygons.json")
searchCoarse = os.path.join(cityscapesPath, "gtCoarse", "*", "*",
"*_gt*_polygons.json")
# search files
filesFine = glob.glob(searchFine)
filesFine.sort()
filesCoarse = glob.glob(searchCoarse)
filesCoarse.sort()
# concatenate fine and coarse
files = filesFine + filesCoarse
# quit if we did not find anything
if not files:
print("Did not find any files. Please consult the README.")
# a bit verbose
print("Processing {} annotation files".format(len(files)))
# iterate through files
progress = 0
print("Progress: {:>3} %".format(progress * 100 / len(files)))
for f in files:
# create the output filename
dst = f.replace("_polygons.json", "_labelTrainIds.png")
# do the conversion
try:
json2labelImg(f, dst, "trainIds")
except:
print("Failed to convert: {}".format(f))
raise
# status
progress += 1
print("Progress: {:>3} %".format(progress * 100 / len(files)))
sys.stdout.flush()
def main():
cityscapesPath = "/Users/ht/Documents/dataset/cityscapes/gtFine_trainvaltest"
# how to search for all ground truth
searchFine = os.path.join(cityscapesPath, "gtFine", "*", "*",
"*_gt*_polygons.json")
searchCoarse = os.path.join(cityscapesPath, "gtCoarse", "*", "*",
"*_gt*_polygons.json")
# search files
filesFine = glob.glob(searchFine)
filesFine.sort()
filesCoarse = glob.glob(searchCoarse)
filesCoarse.sort()
# concatenate fine and coarse
#files = filesFine + filesCoarse
files = filesFine # use this line if fine is enough for now.
# quit if we did not find anything
if not files:
printError("Did not find any files. Please consult the README.")
# a bit verbose
print("Processing {} annotation files".format(len(files)))
# iterate through files
progress = 0
print("Progress: {:>3} %".format(progress * 100 / len(files)), end=' ')
for f in files:
# create the output filename
dst = f.replace("_polygons.json", "_labelTrainIds.png")
# do the conversion
try:
json2labelImg(f, dst, "trainIds")
except:
print("Failed to convert: {}".format(f))
raise
# status
progress += 1
print("\rProgress: {:>3} %".format(progress * 100 / len(files)),
end=' ')
sys.stdout.flush()
def process_folder(fn):
global args
dst = fn.replace("_polygons.json", "_label{}s.png".format(args.id_type))
# do the conversion
try:
json2labelImg(fn, dst, args.id_type)
except:
tqdm.write("Failed to convert: {}".format(fn))
raise
if args.color:
# create the output filename
dst = fn.replace("_polygons.json", "_labelColors.png")
# do the conversion
try:
json2labelImg(fn, dst, 'color')
except:
tqdm.write("Failed to convert: {}".format(f))
raise
def main():
# how to search for all ground truth
searchFine = os.path.join( '/media/psf/Home/code/dataset/03.labelled/' , "*.json" )
# search files
filesFine = glob.glob( searchFine )
filesFine.sort()
# concatenate fine and coarse
files = filesFine
# quit if we did not find anything
if not files:
printError( "Did not find any files. Please consult the README." )
# a bit verbose
print("Processing {} annotation files".format(len(files)))
# iterate through files
progress = 0
print("Progress: {:>3} %".format( progress * 100 / len(files) ), end=' ')
for f in files:
# create the output filename
labelIdFileName = f.replace( ".json" , "_labelIds.png" )
colorFileName = f.replace( ".json" , "_color.png" )
# do the conversion
try:
json2labelImg(f, labelIdFileName)
json2labelImg(f, colorFileName, encoding='color')
except:
print("Failed to convert: {}".format(f))
raise
# status
progress += 1
print("\rProgress: {:>3} %".format( progress * 100 / len(files) ), end=' ')
sys.stdout.flush()