def __init__(self):
self.img_channel = 2
self.gray_encoder = C3D_Test_ENCODER(input_channel=1,model_scope_name='gray_encoder', bn_tag = False)
self.gray_encoder.encoder_channel_num = [64, 64, 64, 1]
self.gray_encoder.encoder_stride_num = [[1, 1, 1],[1, 1, 1],[1, 1, 1],[1, 1, 1] ]
self.gray_encoder.encoder_kernel_size = [[2, 3, 3],[2, 3, 3],[2, 3, 3],[2, 3, 3]]
self.gray_decoder = C3D_DECODER(input_channel=1,model_scope_name='gray_decoder', bn_tag = False)
self.gray_decoder.decoder_channel_num = [64, self.gray_decoder.input_channel]
self.gray_decoder.decoder_stride_num = [[2, 2, 2],[2, 2, 2]]
self.mid_model = Attention_Convert_Model( input_channel = 3,model_scope_name = 'net',s_size=4, attention_uints = 32, attention_hops = 16)
self.batch_size = 1
self.video_imgs_num = 4
self.img_size_h = None
self.img_size_w = None
self.encoder_lr = 1e-3
self.decoder_lr = 1e-4
self.autoencoder_lr = 1e-3
self.selected_gpu_num = 0
self.build_model_adn_loss_opt()
self.root_path = '/home/room304/TB/TB/TensorFlow_Saver/ANORMLY/Split/'
self.optical_save_path = self.root_path + 'MODEL_OPTICAL/'
self.gray_save_path = self.root_path + 'MODEL_GRAY/'
self.mid_stage_save_path = self.root_path + 'MODEL_D/'
self.summaries_dir = self.root_path + 'SUMMARY/'
self.optical_img_save_path = self.root_path + 'RESULT/MODEL_OPTICAL/'
self.gray_img_save_path = self.root_path + 'RESULT/MODEL_GRAY/'
self.mid_stage_img_save_path = self.root_path + 'RESULT/MODEL_MID_STAGE/'
self.full_datat_set_path = self.root_path + 'RESULT/Data_Set_UCSD_Path/'
self.full_ucsd_datatset_path = self.root_path + 'RESULT/FULL_Data_Set/UCSD_Path/'
self.full_shanghai_datatset_path = self.root_path + 'RESULT/FULL_Data_Set/Shanghai/'
tmp_dir_list = []
tmp_dir_list.append(self.optical_save_path)
tmp_dir_list.append(self.gray_save_path)
tmp_dir_list.append(self.mid_stage_save_path)
tmp_dir_list.append(self.summaries_dir)
tmp_dir_list.append(self.optical_img_save_path)
tmp_dir_list.append(self.gray_img_save_path)
tmp_dir_list.append(self.mid_stage_img_save_path)
tmp_dir_list.append(self.full_datat_set_path)
tmp_dir_list.append(self.full_ucsd_datatset_path)
tmp_dir_list.append(self.full_shanghai_datatset_path)
mk_dirs(tmp_dir_list)
return
def __init__(self):
self.img_channel = 1
self.optical_encoder = C3D_ENCODER(
input_channel=2,
model_scope_name='optical_flow_encoder',
bn_tag=False,
relu_tag=True)
self.optical_encoder.encoder_channel_num = [64, 16]
self.optical_encoder.encoder_stride_num = [[2, 2, 2], [2, 2, 2]]
self.optical_decoder = C3D_DECODER(
input_channel=2,
model_scope_name='optical_flow_decoder',
bn_tag=False,
relu_tag=True)
self.optical_decoder.not_last_activation = True
self.optical_decoder.decoder_channel_num = [
64, self.optical_decoder.input_channel
]
self.optical_decoder.decoder_stride_num = [[2, 2, 2], [2, 2, 2]]
self.gray_encoder = C3D_ENCODER(input_channel=1,
model_scope_name='gray_encoder',
bn_tag=False,
relu_tag=True)
self.gray_encoder.encoder_channel_num = [64, 32]
self.gray_encoder.encoder_stride_num = [[2, 2, 2], [2, 2, 2]]
self.gray_decoder = C3D_DECODER(input_channel=1,
model_scope_name='gray_decoder',
bn_tag=False,
relu_tag=True)
self.gray_decoder.decoder_channel_num = [
64, self.gray_decoder.input_channel
]
self.gray_decoder.decoder_stride_num = [[2, 2, 2], [2, 2, 2]]
self.mid_model = Attention_Model(input_channel=512,
model_scope_name='vn4_concate_model',
attention_uints=512,
attention_hops=256)
self.batch_size = 1
self.video_imgs_num = 4
self.img_size_h = 224
self.img_size_w = 224
self.encoder_lr = 1e-3
self.decoder_lr = 1e-4
self.autoencoder_lr = 1e-3
self.selected_gpu_num = 0
self.build_model_adn_loss_opt()
self.root_path = '/home/room304/TB/TB/TensorFlow_Saver/ANORMLY/Attention_test_attention_without_pretrain/'
self.optical_save_path = self.root_path + 'MODEL_OPTICAL/'
self.gray_save_path = self.root_path + 'MODEL_GRAY/'
self.mid_stage_save_path = self.root_path + 'MODEL_D/'
self.summaries_dir = self.root_path + 'SUMMARY/'
self.optical_img_save_path = self.root_path + 'RESULT/MODEL_OPTICAL/'
self.gray_img_save_path = self.root_path + 'RESULT/MODEL_GRAY/'
self.mid_stage_img_save_path = self.root_path + 'RESULT/MODEL_MID_STAGE/'
self.full_datat_set_path = self.root_path + 'RESULT/Data_Set_UCSD_Path/'
self.full_ucsd_datatset_path = self.root_path + 'RESULT/FULL_Data_Set/UCSD_Path/'
self.full_shanghai_datatset_path = self.root_path + 'RESULT/FULL_Data_Set/Shanghai/'
tmp_dir_list = []
tmp_dir_list.append(self.optical_save_path)
tmp_dir_list.append(self.gray_save_path)
tmp_dir_list.append(self.mid_stage_save_path)
tmp_dir_list.append(self.summaries_dir)
tmp_dir_list.append(self.optical_img_save_path)
tmp_dir_list.append(self.gray_img_save_path)
tmp_dir_list.append(self.mid_stage_img_save_path)
tmp_dir_list.append(self.full_datat_set_path)
tmp_dir_list.append(self.full_ucsd_datatset_path)
tmp_dir_list.append(self.full_shanghai_datatset_path)
mk_dirs(tmp_dir_list)
return
def __init__(self):
self.img_channel = 2
self.gray_encoder = C3D_ENCODER(input_channel=1,
model_scope_name='gray_encoder',
bn_tag=False)
self.gray_encoder.encoder_channel_num = [32, 64]
self.gray_encoder.encoder_stride_num = [[2, 2, 2], [2, 2, 2]]
self.gray_decoder = C3D_DECODER(input_channel=1,
model_scope_name='gray_decoder',
bn_tag=False)
self.gray_decoder.decoder_channel_num = [
32, self.gray_decoder.input_channel
]
self.gray_decoder.decoder_stride_num = [[2, 2, 2], [2, 2, 2]]
self.discriminator_model = gan_model(input_channel=3,
model_scope_name='discriminator',
s_size=4,
xt_num=64,
attention_uints=512,
attention_hops=256,
bn_tag=False,
attention_tag=False,
dense_tag=False,
not_last_activation=True)
self.discriminator_model.encoder_channel_num = [32, 32, 32]
self.discriminator_model.encoder_stride_num = [[1, 1], [1, 1], [1, 1]]
self.batch_size = 2
self.video_imgs_num = 4
self.img_size_h = 256
self.img_size_w = 256
self.encoder_lr = 1e-3
self.decoder_lr = 1e-4
self.autoencoder_lr = 1e-3
self.selected_gpu_num = 0
self.build_model_adn_loss_opt()
self.root_path = '/home/room304/TB/TB/TensorFlow_Saver/ANORMLY/GAN_T1/'
self.optical_save_path = self.root_path + 'MODEL_OPTICAL/'
self.gray_save_path = self.root_path + 'MODEL_GRAY/'
self.discriminator_save_path = self.root_path + 'MODEL_DISCRIMINATOR/'
self.mid_stage_save_path = self.root_path + 'MODEL_D/'
self.summaries_dir = self.root_path + 'SUMMARY/'
self.optical_img_save_path = self.root_path + 'RESULT/MODEL_OPTICAL/'
self.gray_img_save_path = self.root_path + 'RESULT/MODEL_GRAY/'
self.mid_stage_img_save_path = self.root_path + 'RESULT/MODEL_MID_STAGE/'
self.full_datat_set_path = self.root_path + 'RESULT/Data_Set_UCSD_Path/'
self.full_ucsd_datatset_path = self.root_path + 'RESULT/FULL_Data_Set/UCSD_Path/'
self.full_shanghai_datatset_path = self.root_path + 'RESULT/FULL_Data_Set/Shanghai/'
tmp_dir_list = []
tmp_dir_list.append(self.optical_save_path)
tmp_dir_list.append(self.gray_save_path)
tmp_dir_list.append(self.mid_stage_save_path)
tmp_dir_list.append(self.summaries_dir)
tmp_dir_list.append(self.optical_img_save_path)
tmp_dir_list.append(self.gray_img_save_path)
tmp_dir_list.append(self.mid_stage_img_save_path)
tmp_dir_list.append(self.full_datat_set_path)
tmp_dir_list.append(self.full_ucsd_datatset_path)
tmp_dir_list.append(self.full_shanghai_datatset_path)
mk_dirs(tmp_dir_list)
return