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__)), '..', '../dataset')
# 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")
print("searchFine:" + searchFine)
print("searchCoarse:" + searchCoarse)
# 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" , "_instanceTrainIds.png" )
dst = f.replace("_polygons.json", "_instanceIds.png")
print("Processing file:{}".format(dst))
# do the conversion
try:
# json2instanceImg( f , dst , "trainIds" )
json2instanceImg(f, dst)
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
# 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():
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 main():
# Where to look for Cityscapes
root = '../../../data/cityscape'
os.environ['CITYSCAPES_DATASET'] = root
store_path = 'gtFine_allperson'
label_tochose = 'rider'
set = 'val'
gtset_name = 'gtFine'
print(label_tochose, set, gtset_name, store_path)
# city="darmstadt"
# if not os.path.exists(store_path):
# os.mkdir(store_path)
# set_path=os.path.join(store_path,set)
# if not os.path.exists(set_path):
# os.mkdir(set_path)
# city_path=os.path.join(set_path,city)
# if not os.path.exists(city_path):
# os.mkdir(city_path)
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, gtset_name, set, "*",
"*_gt*_polygons.json")
# search files
filesFine = glob.glob(searchFine)
filesFine.sort()
# concatenate fine and coarse
files = filesFine
# 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 = -1
numIns_all = 0
numimg_selected = 0
# print("Progress: {:>3} %".format( progress * 100 / len(files) ), end=' ')
for i, f in enumerate(files):
# create the output filename
progress += 1
# print("\rProgress: {:>3} %".format( progress * 100 / len(files) ), end=' ')
print('Processing........', i, len(files), i * 1.0 / len(files))
# if numIns_all>=1000:
# break
# do the conversion
try:
# json2instanceImg( f , dst , "trainIds" )
print(i, 'image............', numIns_all, 'ins selected now')
insImg_arr, insIds_arr, Sizes_arr, num_instances = json2instanceArr(
f, 'trainIds', label_tochose=label_tochose)
if num_instances == 0:
# progress += 1
continue
numIns_all += num_instances
numimg_selected += 1
for instance, id, size in zip(insImg_arr, insIds_arr, Sizes_arr):
try:
dst = f.replace("_gtFine_polygons.json",
"_" + str(id) + ".png")
dst = dst.replace("gtFine", store_path)
n_last = len(dst.split('/')[-1])
parent_dir = dst[:-n_last]
pathtodir(parent_dir)
imsave(dst, instance)
except:
print("Failed to save: {}".format(id))
raise
except:
print("Failed to convert: {}".format(f))
raise
# status
sys.stdout.flush()
print('Ins count all', numIns_all, ',all imgs', len(files),
',seleced imgs', numimg_selected,
',average instances per img selected',
numIns_all * 1.0 / numimg_selected, ',ave ins per img all',
numIns_all * 1.0 / len(files))
