import argparse
import os.path as ops
import time
import cv2
import matplotlib.pyplot as plt
import numpy as np
import tensorflow as tf
from lanenet_model import lanenet
from lanenet_model import lanenet_postprocess
from local_utils.config_utils import parse_config_utils
from local_utils.log_util import init_logger
CFG = parse_config_utils.lanenet_cfg
LOG = init_logger.get_logger(log_file_name_prefix='lanenet_test')
def init_args():
"""
:return:
"""
parser = argparse.ArgumentParser()
parser.add_argument('--image_path',
type=str,
help='The image path or the src image save dir')
parser.add_argument('--weights_path',
type=str,
help='The model weights path')
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
# @Time : 2019/12/13 下午5:46
# @Author : MaybeShewill-CV
# @Site : https://github.com/MaybeShewill-CV/bisenetv2-tensorflow
# @File : train_bisenetv2_celebamaskhq.py
# @IDE: PyCharm
"""
Train bisenetv2 on celebamaskhq dataset
"""
from trainner.celebamask_hq import celebamask_hq_bisenetv2_single_gpu_trainner as single_gpu_trainner
from trainner.celebamask_hq import celebamask_hq_bisenetv2_multi_gpu_trainner as multi_gpu_trainner
from local_utils.log_util import init_logger
from local_utils.config_utils import parse_config_utils
LOG = init_logger.get_logger('train_bisenetv2_celebamaskhq')
CFG = parse_config_utils.celebamask_hq_cfg
def train_model():
"""
:return:
"""
if CFG.TRAIN.MULTI_GPU.ENABLE:
LOG.info('Using multi gpu trainner ...')
worker = multi_gpu_trainner.BiseNetV2CelebamaskhqMultiTrainer()
else:
LOG.info('Using single gpu trainner ...')
worker = single_gpu_trainner.BiseNetV2CelebamaskhqTrainer()
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
# @Time : 2019/12/13 下午5:46
# @Author : MaybeShewill-CV
# @Site : https://github.com/MaybeShewill-CV/bisenetv2-tensorflow
# @File : train_bisenet_cityscapes.py
# @IDE: PyCharm
"""
Train bisenet on cityscapes dataset
"""
from trainner.cityscapes import cityscapes_bisenet_trainner as trainner
from local_utils.log_util import init_logger
LOG = init_logger.get_logger('train_bisenet_cityscapes')
def train_model():
"""
:return:
"""
worker = trainner.BiseNetCityScapesTrainer()
worker.train()
return
if __name__ == '__main__':
"""
main function
"""
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
# @Time : 2019/12/13 下午5:46
# @Author : MaybeShewill-CV
# @Site : https://github.com/MaybeShewill-CV/bisenetv2-tensorflow
# @File : train_bisenetv2_cityscapes.py
# @IDE: PyCharm
"""
Train bisenetv2 on cityscapes dataset
"""
from trainner.segcomp import segcomp_bisenetv2_single_gpu_trainner as single_gpu_trainner
from local_utils.log_util import init_logger
from local_utils.config_utils import parse_config_utils
LOG = init_logger.get_logger('train_bisenetv2_segcomp')
CFG = parse_config_utils.segcomp_cfg
def train_model():
"""
:return:
"""
# if CFG.TRAIN.MULTI_GPU.ENABLE:
# LOG.info('Using multi gpu trainner ...')
# worker = multi_gpu_trainner.BiseNetV2CityScapesMultiTrainer()
LOG.info('Using single gpu trainner ...')
worker = single_gpu_trainner.BiseNetV2CityScapesTrainer()
worker.train()
return
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
# @Time : 2020/5/8 下午8:29
# @Author : MaybeShewill-CV
# @Site : https://github.com/MaybeShewill-CV/bisenetv2-tensorflow
# @File : make_tusimple_tfrecords.py
# @IDE: PyCharm
"""
Generate cityscapes tfrecords tools
"""
import sys
sys.path.append('/home/erdos/workspace/lanenet-lane-detection')
from data_provider import lanenet_data_feed_pipline
from local_utils.log_util import init_logger
LOG = init_logger.get_logger(
log_file_name_prefix='generate_tusimple_tfrecords')
def generate_tfrecords():
"""
:return:
"""
producer = lanenet_data_feed_pipline.LaneNetDataProducer()
producer.generate_tfrecords()
return
if __name__ == '__main__':
"""
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
# @Time : 2019/12/13 下午5:46
# @Author : MaybeShewill-CV
# @Site : https://github.com/MaybeShewill-CV/sfnet-tensorflow
# @File : train_sfnet_cityscapes.py
# @IDE: PyCharm
"""
Train sfnet on cityscapes dataset
"""
from trainner.cityscapes import cityscapes_sfnet_single_gpu_trainner as single_gpu_trainner
from trainner.cityscapes import cityscapes_sfnet_multi_gpu_trainner as multi_gpu_trainner
from local_utils.log_util import init_logger
from local_utils.config_utils import parse_config_utils
LOG = init_logger.get_logger('train_sfnet_cityscapes')
CFG = parse_config_utils.SFNET_CITYSCAPES_CFG
def train_model():
"""
:return:
"""
if CFG.TRAIN.MULTI_GPU.ENABLE:
LOG.info('Using multi gpu trainner ...')
worker = multi_gpu_trainner.SFNetCityScapesMultiTrainer(cfg=CFG)
else:
LOG.info('Using single gpu trainner ...')
worker = single_gpu_trainner.SFNetCityScapesTrainer(cfg=CFG)
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
# @Time : 2020/5/8 下午8:29
# @Author : MaybeShewill-CV
# @Site : https://github.com/MaybeShewill-CV/sfnet-tensorflow
# @File : make_cityscapes_tfrecords.py
# @IDE: PyCharm
"""
Generate cityscapes tfrecords tools
"""
from data_provider.cityscapes import cityscapes_tf_io
from local_utils.log_util import init_logger
from local_utils.config_utils import parse_config_utils
LOG = init_logger.get_logger(log_file_name_prefix='generate_cityscapes_tfrecords')
CFG = parse_config_utils.CITYSCAPES_CFG
def generate_tfrecords():
"""
:return:
"""
io = cityscapes_tf_io.CityScapesTfIO(cfg=CFG)
io.writer.write_tfrecords()
return
if __name__ == '__main__':
"""
import os
import os.path as ops
import time
import cv2
import numpy as np
import tensorflow as tf
import tqdm
from lanenet_model import lanenet
from lanenet_model import lanenet_postprocess
from local_utils.config_utils import parse_config_utils
from local_utils.log_util import init_logger
CFG = parse_config_utils.lanenet_cfg
LOG = init_logger.get_logger(log_file_name_prefix='lanenet_eval')
def init_args():
"""
:return:
"""
parser = argparse.ArgumentParser()
parser.add_argument('--image_dir',
type=str,
help='The source tusimple lane test data dir')
parser.add_argument('--weights_path',
type=str,
help='The model weights path')
parser.add_argument('--save_dir',
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
# @Time : 2019/12/13 下午5:46
# @Author : MaybeShewill-CV
# @Site : https://github.com/MaybeShewill-CV/bisenetv2-tensorflow
# @File : train_bisenetv2_cityscapes.py
# @IDE: PyCharm
"""
Train bisenetv2 on cityscapes dataset
"""
from trainner.carla import carla_bisenetv2_single_gpu_trainner as single_gpu_trainner #, \
#cityscapes_bisenetv2_multi_gpu_trainner as multi_gpu_trainner
from local_utils.log_util import init_logger
from local_utils.config_utils import parse_config_utils
LOG = init_logger.get_logger('train_bisenetv2_carla')
CFG = parse_config_utils.carla_cfg_v2
def train_model():
"""
:return:
"""
#if CFG.TRAIN.MULTI_GPU.ENABLE:
#LOG.info('Using multi gpu trainner ...')
#worker = multi_gpu_trainner.BiseNetV2CityScapesMultiTrainer()
#else:
LOG.info('Using single gpu trainner ...')
worker = single_gpu_trainner.BiseNetV2CarlaTrainer()
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
# @Time : 2019/12/13 下午5:46
# @Author : MaybeShewill-CV
# @Site : https://github.com/MaybeShewill-CV/sfnet-tensorflow
# @File : train_sfnet_cityscapes.py
# @IDE: PyCharm
"""
Train sfnet on cityscapes dataset
"""
from trainner.cityscapes import cityscapes_resnetfcn_multi_gpu_trainner as multi_gpu_trainner
from local_utils.log_util import init_logger
from local_utils.config_utils import parse_config_utils
LOG = init_logger.get_logger('train_resnetfcn_cityscapes')
CFG = parse_config_utils.RESNET_FCN_CITYSCAPES_CFG
def train_model():
"""
:return:
"""
if CFG.TRAIN.MULTI_GPU.ENABLE:
LOG.info('Using multi gpu trainner ...')
worker = multi_gpu_trainner.ResNetFCNCityScapesMultiTrainer(cfg=CFG)
else:
raise NotImplementedError
worker.train()
return
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
# @Time : 2020/5/8 下午8:29
# @Author : MaybeShewill-CV
# @Site : https://github.com/MaybeShewill-CV/bisenetv2-tensorflow
# @File : make_celebamask_hq_tfrecords.py
# @IDE: PyCharm
"""
Generate celebamask_hq tfrecords tools
"""
from data_provider.celebamask_hq import celebamask_hq_tf_io
from local_utils.log_util import init_logger
LOG = init_logger.get_logger(
log_file_name_prefix='generate_celebamask_hq_tfrecords')
def generate_tfrecords():
"""
:return:
"""
io = celebamask_hq_tf_io.CelebamaskhqTfIO()
io.writer.write_tfrecords()
return
if __name__ == '__main__':
"""
test
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
# @Time : 2020/5/8 下午8:29
# @Author : MaybeShewill-CV
# @Site : https://github.com/MaybeShewill-CV/bisenetv2-tensorflow
# @File : make_segcomp_tfrecords.py
# @IDE: PyCharm
"""
Generate cityscapes tfrecords tools
"""
from data_provider.segcomp import segcomp_tf_io
from local_utils.log_util import init_logger
LOG = init_logger.get_logger(log_file_name_prefix='generate_segcomp_tfrecords')
def generate_tfrecords():
"""
:return:
"""
io = segcomp_tf_io.CityScapesTfIO()
io.writer.write_tfrecords()
return
if __name__ == '__main__':
"""
test
"""
import sys
file='/home/levon/MyProjects/Paper_Reading/SemanticSegmentation/BiSeNet-V2-Ours/'
# sys.path.insert(0, '/'.join(__file__.split('/')[:-3]))
sys.path.insert(0, file)
from trainner.mixed_8K import mixed_8K_bisenetv2_single_gpu_trainner as single_gpu_trainner
from trainner.mixed_8K import mixed_8K_bisenetv2_multi_gpu_trainner as multi_gpu_trainner
from local_utils.log_util import init_logger
from local_utils.config_utils import parse_config_utils
LOG = init_logger.get_logger('train_bisenetv2_mixed_8k_mask')
CFG = parse_config_utils.mixed_8K_cfg
def train_model():
"""
:return:
"""
if CFG.TRAIN.MULTI_GPU.ENABLE:
LOG.info('Using multi gpu trainner ...')
# worker = multi_gpu_trainner.BiseNetV2CelebamaskhqMultiTrainer()
else:
LOG.info('Using single gpu trainner ...')
worker = single_gpu_trainner.BiseNetV2Mixed8KTrainer()
worker.train()
return
if __name__ == '__main__':
"""
import sys
file = '/home/levon/MyProjects/Paper_Reading/SemanticSegmentation/BiSeNet-V2-Ours/'
# sys.path.insert(0, '/'.join(__file__.split('/')[:-3]))
sys.path.insert(0, file)
from data_provider.mixed_8K import mixed_8K_tf_io
from local_utils.log_util import init_logger
LOG = init_logger.get_logger(
log_file_name_prefix='generate_mixed_8K_tfrecords')
def generate_tfrecords():
"""
:return:
"""
io = mixed_8K_tf_io.mixed_8K_TfIO()
io.writer.write_tfrecords()
return
if __name__ == '__main__':
"""
test
"""
generate_tfrecords()
