def main():
parser = argparse.ArgumentParser()
parser.add_argument('im_file_raw')
parser.add_argument('im_file_out')
parser.add_argument('--rescale_type', type=str, default='tot_8band',
help="Can be tot_3band or tot_8band")
args = parser.parse_args()
apls_tools.convert_to_8Bit(args.im_file_raw, args.im_file_out,
outputPixType='Byte',
outputFormat='GTiff',
rescale_type=rescale[args.rescale_type])
return
def main():
parser = argparse.ArgumentParser()
parser.add_argument('datasets', type=str, nargs='+')
parser.add_argument('--training', action='store_true')
parser.add_argument('--rgb', action='store_true')
parser.add_argument('--mul', action='store_true')
parser.add_argument('--pan', action='store_true')
args = parser.parse_args()
buffer_meters = 2
burnValue = 255
path_apls = r'/wdata'
path_png = os.path.join(path_apls, 'output_png')
test = not args.training
save_rgb = args.rgb
save_mul = args.mul
save_pan = args.pan
path_outputs = os.path.join(path_apls, 'train' if not test else 'test', 'masks{}m'.format(buffer_meters))
path_images_8bit = os.path.join(path_apls, 'train' if not test else 'test', 'images')
for d in [path_outputs, path_images_8bit, path_png]:
shutil.rmtree(d, ignore_errors=True)
os.makedirs(d, exist_ok=True)
for path_data in args.datasets:
path_data = path_data.rstrip('/')
test_data_name = os.path.split(path_data)[-1]
test_data_name = '_'.join(test_data_name.split('_')[:3]) + '_'
path_images_raw = os.path.join(path_data, 'RGB-PanSharpen')
path_images_mul = os.path.join(path_data, 'MUL')
path_images_pan = os.path.join(path_data, 'PAN')
path_labels = os.path.join(path_data, 'geojson/spacenetroads')
# iterate through images, convert to 8-bit, and create masks
im_files = os.listdir(path_images_raw)
m = defaultdict(list)
for im_file in im_files:
if not im_file.endswith('.tif'):
continue
name_root = im_file.split('_')[-1].split('.')[0]
# create 8-bit image
im_file_raw = os.path.join(path_images_raw, im_file)
im_file_out = os.path.join(path_images_8bit, test_data_name + name_root + '.tif')
im_file_rgb = os.path.join(path_png,test_data_name + name_root + "_rgb.png")
im_file_mul = os.path.join(path_png,test_data_name + name_root + "_mul.png")
im_file_pan = os.path.join(path_png,test_data_name + name_root + "_pan.png")
# continue
rescale_type = test_data_name.split('_')[1]
if not os.path.isfile(im_file_out):
apls_tools.convert_to_8Bit(im_file_raw, im_file_out,
outputPixType='Byte',
outputFormat='GTiff',
rescale_type=rescale[rescale_type],
percentiles=[2,98])
if not os.path.isfile(im_file_rgb) and save_rgb:
apls_tools.convert_to_8Bit(im_file_raw, im_file_rgb,
outputPixType='Byte',
outputFormat='png',
percentiles=[0,100])
if not os.path.isfile(im_file_mul) and save_mul:
apls_tools.convert_to_8Bit(im_file_mul, im_file_mul,
outputPixType='Byte',
outputFormat='png',
percentiles=[0,100])
if not os.path.isfile(im_file_pan) and save_pan:
apls_tools.convert_to_8Bit(im_file_pan, im_file_pan,
outputPixType='Byte',
outputFormat='png',
percentiles=[0,100])
if test:
continue
# determine output files
label_file = os.path.join(path_labels, 'spacenetroads_' + test_data_name + name_root + '.geojson')
label_file_tot = os.path.join(path_labels, label_file)
output_raster = os.path.join(path_outputs, test_data_name + name_root + '.png')
print("\nname_root:", name_root)
print(" output_raster:", output_raster)
# create masks
mask, gdf_buffer = apls_tools.get_road_buffer(label_file_tot, im_file_out,
output_raster,
buffer_meters=buffer_meters,
burnValue=burnValue,
bufferRoundness=6,
plot_file=None,
figsize= (6,6), #(13,4),
fontsize=8,
dpi=200, show_plot=False,
verbose=False)
for k, v in m.items():
print(test_data_name, k, np.mean(v, axis=0))
def main():
parser = argparse.ArgumentParser()
parser.add_argument('config_path')
parser.add_argument('--training', action='store_true')
#parser.add_argument('datasets', type=str, nargs='+')
#parser.add_argument('mode', type=str, default='test', help='test or train')
#parser.add_argument('--buffer_meters', type=float, default=2, help='road width (m)')
args = parser.parse_args()
#buffer_meters = args.buffer_meters
# get config
with open(args.config_path, 'r') as f:
cfg = json.load(f)
config = Config(**cfg)
# set values
if config.num_channels == 3:
image_format_path = 'RGB-PanSharpen'
else:
image_format_path = 'MUL-PanSharpen'
imfile_prefix = image_format_path + '_'
label_path_extra = 'geojson/spacenetroads'
geojson_prefix = 'spacenetroads_'
burnValue = 255
buffer_meters = float(config.mask_width_m)
buffer_meters_str = str(np.round(buffer_meters, 1)).replace('.', 'p')
test = not args.training
paths_data_raw = []
#############
# output directories
# put all training images in one directory so training can find em all
if not test:
path_masks = os.path.join(config.path_data_root,
config.train_data_refined_dir,
'masks{}m'.format(buffer_meters_str))
path_images_8bit = os.path.join(config.path_data_root,
config.train_data_refined_dir,
'images')
# make dirs
for d in [path_masks, path_images_8bit]:
print("cleaning and remaking:", d)
shutil.rmtree(d, ignore_errors=True)
os.makedirs(d, exist_ok=True)
# set path_data_raw
for dpart in config.data_train_raw_parts.split(','):
paths_data_raw.append(os.path.join(config.path_data_root, dpart))
else:
path_masks = os.path.join(config.path_data_root,
config.test_data_refined_dir,
'masks{}m'.format(buffer_meters_str))
path_images_8bit = os.path.join(config.path_data_root,
config.test_data_refined_dir)
# make dirs
for d in [path_images_8bit]:
print("cleaning and remaking:", d)
shutil.rmtree(d, ignore_errors=True)
os.makedirs(d, exist_ok=True)
# set path_data_raw
for dpart in config.data_test_raw_parts.split(','):
paths_data_raw.append(os.path.join(config.path_data_root, dpart))
#path_masks = os.path.join(config.path_data_root, config.data_refined_name+'_train' if not test else config.data_refined_name+'_test', 'masks{}m'.format(buffer_meters))
#path_images_8bit = os.path.join(config.path_data_root, config.data_refined_name+'_train' if not test else config.data_refined_name+'_test', 'images')
# make dirs
for d in [path_masks, path_images_8bit]:
print("cleaning and remaking:", d)
shutil.rmtree(d, ignore_errors=True)
os.makedirs(d, exist_ok=True)
# iterate through dirs
for path_data in paths_data_raw:
path_data = path_data.strip().rstrip('/')
# get test_data_name for rescaling (if needed)
#test_data_name = os.path.split(path_data)[-1]
#test_data_name = '_'.join(test_data_name.split('_')[:3]) + '_'
path_images_raw = os.path.join(path_data, image_format_path)
path_labels = os.path.join(path_data, label_path_extra)
# iterate through images, convert to 8-bit, and create masks
im_files = os.listdir(path_images_raw)
#m = defaultdict(list)
for im_file in im_files:
if not im_file.endswith('.tif'):
continue
#name_root_small = im_file.split('_')[-1].split('.')[0]
name_root_full = im_file.split(imfile_prefix)[-1].split('.')[0]
# create 8-bit image
im_file_raw = os.path.join(path_images_raw, im_file)
im_file_out = os.path.join(path_images_8bit, im_file)
#im_file_out = os.path.join(path_images_8bit, test_data_name + name_root + '.tif')
# convert to 8bit
# m = calc_rescale(im_file_raw, m, percentiles=[2,98])
# continue
####################
# SET RESCALE TYPE
#rescale_type = test_data_name.split('_')[1]
if config.num_channels == 3:
rescale_type = 'tot_3band' #test_data_name.split('_')[1]
else:
rescale_type = 'tot_8band' #test_data_name.split('_')[1]
####################
if not os.path.isfile(im_file_out):
apls_tools.convert_to_8Bit(im_file_raw,
im_file_out,
outputPixType='Byte',
outputFormat='GTiff',
rescale_type=rescale[rescale_type])
if test:
continue
else:
# determine mask output files
label_name = geojson_prefix + name_root_full + '.geojson'
label_file_tot = os.path.join(path_labels, label_name)
output_raster = os.path.join(path_masks, im_file)
print("\nname_root:", name_root_full)
print(" output_mask_raster:", output_raster)
# create masks
mask, gdf_buffer = apls_tools.get_road_buffer(
label_file_tot,
im_file_out,
output_raster,
buffer_meters=buffer_meters,
burnValue=burnValue,
bufferRoundness=6,
plot_file=None,
figsize=(6, 6), #(13,4),
fontsize=8,
dpi=200,
show_plot=False,
verbose=False)
def main():
parser = argparse.ArgumentParser()
parser.add_argument('datasets', type=str, nargs='+')
parser.add_argument('--training', action='store_true')
args = parser.parse_args()
buffer_meters = 2
burnValue = 255
path_apls = r'/wdata'
test = not args.training
path_outputs = os.path.join(path_apls, 'train' if not test else 'test', 'masks{}m'.format(buffer_meters))
path_images_8bit = os.path.join(path_apls, 'train' if not test else 'test', 'images')
for d in [path_outputs, path_images_8bit]:
shutil.rmtree(d, ignore_errors=True)
os.makedirs(d, exist_ok=True)
for path_data in args.datasets:
path_data = path_data.rstrip('/')
test_data_name = os.path.split(path_data)[-1]
test_data_name = '_'.join(test_data_name.split('_')[:3]) + '_'
path_images_raw = os.path.join(path_data, 'RGB-PanSharpen')
path_labels = os.path.join(path_data, 'geojson/spacenetroads')
# iterate through images, convert to 8-bit, and create masks
im_files = os.listdir(path_images_raw)
m = defaultdict(list)
for im_file in im_files:
if not im_file.endswith('.tif'):
continue
name_root = im_file.split('_')[-1].split('.')[0]
# create 8-bit image
im_file_raw = os.path.join(path_images_raw, im_file)
im_file_out = os.path.join(path_images_8bit, test_data_name + name_root + '.tif')
# convert to 8bit
# m = calc_rescale(im_file_raw, m, percentiles=[2,98])
# continue
rescale_type = test_data_name.split('_')[1]
if not os.path.isfile(im_file_out):
apls_tools.convert_to_8Bit(im_file_raw, im_file_out,
outputPixType='Byte',
outputFormat='GTiff',
rescale_type=rescale[rescale_type],
percentiles=[2,98])
if test:
continue
# determine output files
label_file = os.path.join(path_labels, 'spacenetroads_' + test_data_name + name_root + '.geojson')
label_file_tot = os.path.join(path_labels, label_file)
output_raster = os.path.join(path_outputs, test_data_name + name_root + '.png')
print("\nname_root:", name_root)
print(" output_raster:", output_raster)
# create masks
mask, gdf_buffer = apls_tools.get_road_buffer(label_file_tot, im_file_out,
output_raster,
buffer_meters=buffer_meters,
burnValue=burnValue,
bufferRoundness=6,
plot_file=None,
figsize= (6,6), #(13,4),
fontsize=8,
dpi=200, show_plot=False,
verbose=False)
for k, v in m.items():
print(test_data_name, k, np.mean(v, axis=0))