from __future__ import print_function from dotdict import DotDict hp = DotDict() # Training hyper parameters hp.train_epoch_size = 30000 hp.eval_epoch_size = 3000 hp.num_epoch = 20 hp.learning_rate = 0.04 hp.momentum = 0.9 hp.bn_mom = 0.9 hp.workspace = 512 hp.loss_type = "warpctc" # ["warpctc" "ctc"] hp.batch_size = 1024 hp.num_classes = 5990 # 0 as blank, 1~xxxx as labels hp.img_width = 280 hp.img_height = 32 # LSTM hyper parameters hp.num_hidden = 100 hp.num_lstm_layer = 2 hp.seq_length = 35 hp.num_label = 10 hp.dropout = 0.5
from pointcnn import PointCNN, get_indices, get_xforms, augment, custom_metric, get_loss_sym from dotdict import DotDict import h5py import collections import data_utils ########################### Settings ############################### setting = DotDict() setting.num_class = 10 setting.sample_num = 160 setting.batch_size = 32 setting.num_epochs = 2048 setting.jitter = 0.01 setting.jitter_val = 0.01 setting.rotation_range = [0, math.pi / 18, 0, 'g'] setting.rotation_range_val = [0, 0, 0, 'u'] setting.order = 'rxyz' setting.scaling_range = [0.05, 0.05, 0.05, 'g'] setting.scaling_range_val = [0, 0, 0, 'u'] x = 2