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()