From a6a775fc172b7c02a0563b175c61b7d1ba25cab4 Mon Sep 17 00:00:00 2001 From: tu184044109 <43280278+tu184044109@users.noreply.github.com> Date: Sat, 9 Jul 2022 22:04:53 -0700 Subject: [PATCH] add v2vnet yaml file --- v2xvit/hypes_yaml/point_pillar_v2vnet.yaml | 137 +++++++++++++++++++++ 1 file changed, 137 insertions(+) create mode 100644 v2xvit/hypes_yaml/point_pillar_v2vnet.yaml diff --git a/v2xvit/hypes_yaml/point_pillar_v2vnet.yaml b/v2xvit/hypes_yaml/point_pillar_v2vnet.yaml new file mode 100644 index 0000000..d346e44 --- /dev/null +++ b/v2xvit/hypes_yaml/point_pillar_v2vnet.yaml @@ -0,0 +1,137 @@ +name: point_pillar_v2vney +#root_dir: '/home/runshengxu/project/Cooperative_perception/opencood/tmp' +#root_dir: '/home/ucla_cav/data/train' +#validate_dir: '/home/ucla_cav/data/validate' +root_dir: '/home/hao/code/mobility/data/train' +validate_dir: '/home/hao/code/mobility/data/validate' +wild_setting: + async: true + async_overhead: 100 + seed: 20 + loc_err: true + xyz_std: 0.2 + ryp_std: 0.2 + data_size: 1.06 # Mb!! + transmission_speed: 27 # Mbps!! + backbone_delay: 10 # ms + +yaml_parser: "load_point_pillar_params" +train_params: + batch_size: &batch_size 4 + epoches: 60 + eval_freq: 1 + save_freq: 1 + max_cav: &max_cav 5 + +fusion: + core_method: 'FeatureFusionDataset' # LateFusionDataset, EarlyFusionDataset, IntermediateFusionDataset, FeatureFusionDataset supported + args: [] + +# preprocess-related +preprocess: + # options: BasePreprocessor, VoxelPreprocessor, BevPreprocessor + core_method: 'SpVoxelPreprocessor' + args: + voxel_size: &voxel_size [0.4, 0.4, 4] + max_points_per_voxel: 32 + max_voxel_train: 32000 + max_voxel_test: 70000 + # lidar range for each individual cav. + cav_lidar_range: &cav_lidar [-140.8, -38.4, -3, 140.8, 38.4, 1] + +data_augment: + - NAME: random_world_flip + ALONG_AXIS_LIST: [ 'x' ] + + - NAME: random_world_rotation + WORLD_ROT_ANGLE: [ -0.78539816, 0.78539816 ] + + - NAME: random_world_scaling + WORLD_SCALE_RANGE: [ 0.95, 1.05 ] + +# anchor box related +postprocess: + core_method: 'VoxelPostprocessor' # VoxelPostprocessor, BevPostprocessor supported + anchor_args: + cav_lidar_range: *cav_lidar + l: 3.9 + w: 1.6 + h: 1.56 + r: [0, 90] + feature_stride: 4 + num: &achor_num 2 + target_args: + pos_threshold: 0.6 + neg_threshold: 0.45 + score_threshold: 0.20 + order: 'hwl' # hwl or lwh + max_num: 100 # maximum number of objects in a single frame. use this number to make sure different frames has the same dimension in the same batch + nms_thresh: 0.15 + +# model related +model: + core_method: point_pillar_v2vnet + args: + voxel_size: *voxel_size + lidar_range: *cav_lidar + anchor_number: *achor_num + max_cav: *max_cav + compression: 0 # compression rate + backbone_fix: false + + pillar_vfe: + use_norm: true + with_distance: false + use_absolute_xyz: true + num_filters: [64] + point_pillar_scatter: + num_features: 64 + + base_bev_backbone: + layer_nums: [3, 5, 8] + layer_strides: [2, 2, 2] + num_filters: [64, 128, 256] + upsample_strides: [1, 2, 4] + num_upsample_filter: [128, 128, 128] + shrink_header: + kernal_size: [3] + stride: [2] + padding: [1] + dim: [256] + input_dim: 384 # 128 * 3 + + v2vfusion: + use_temporal_encoding: true + voxel_size: *voxel_size + downsample_rate: 4 + num_iteration: 3 + in_channels: 256 + gru_flag: false + agg_operator: "avg" # max or avg + conv_gru: + H: 48 + W: 176 + num_layers: 1 + kernel_size: [[3,3]] + + + # add decoder later + +loss: + core_method: point_pillar_loss + args: + cls_weight: 1.0 + reg: 2.0 + +optimizer: + core_method: Adam + lr: 0.001 + args: + eps: 1e-10 + weight_decay: 1e-4 + +lr_scheduler: + core_method: multistep #step, multistep and Exponential support + gamma: 0.1 + step_size: [15, 50] +