diff --git a/code/conversion/setup.conf b/code/conversion/setup.conf index 0361197..d152668 100644 --- a/code/conversion/setup.conf +++ b/code/conversion/setup.conf @@ -4,23 +4,23 @@ train{ fileprefix_list = [ broken_bullet_50k, # more input models can be added here ] - d_in = 3 - plot_frequency = 5000 + d_in = 3 # 输入数据的维度。在3D点云数据中,通常为3(x、y、z坐标) + plot_frequency = 5000 # 每5000次迭代绘制一次点云 checkpoint_frequency = 5000 status_frequency = 100 weight_decay = 0 learning_rate_schedule = [{ - "Type" : "Step", + "Type" : "Step", # 学习率调度类型。"Step"表示在指定迭代次数后将学习率乘以因子 "Initial" : 0.005, "Interval" : 2000, "Factor" : 0.5 }] - network_class = model.network.NHRepNet + network_class = model.network.NHRepNet # 网络类型。NHRepNet是neural halfspace representation network的缩写 } plot{ - resolution = 128 - mc_value = 0.0 + resolution = 128 # 体素网格的分辨率。128表示体素网格的每个维度有128个单元格 + mc_value = 0.0 # 体素网格的体素值。0.0表示体素网格的体素值为0 is_uniform_grid = True verbose = False save_html = False @@ -29,20 +29,20 @@ plot{ } network{ inputs{ - dims_sdf = [256, 256, 256] - skip_in = [] - geometric_init= True - radius_init = 1 - beta=100 + dims_sdf = [256, 256, 256] # 体素网格的维度。[256, 256, 256]表示体素网格的每个维度有256个单元格 + skip_in = [] # 跳过输入的索引。[]表示不跳过任何输入 + geometric_init= True # 几何初始化。True表示使用几何初始化 + radius_init = 1 # 半径初始化。1表示半径初始化为1 + beta=100 # beta值。100表示beta值为100 } sampler{ - sampler_type = NormalPerPoint + sampler_type = NormalPerPoint # 采样器类型。NormalPerPoint表示每个点都使用正态分布采样 properties{ - global_sigma = 1.8 + global_sigma = 1.8 # 全局sigma值。1.8表示全局sigma值为1.8 } } loss{ - lambda = 1 - normals_lambda = 1 + lambda = 1 # 损失函数中的lambda值。1表示lambda值为1 + normals_lambda = 1 # 损失函数中的normals_lambda值。1表示normals_lambda值为1 } }