forget to update car.fhd.onestage.config

Author: traveller59

second/configs/car.fhd.onestage.config

@@ -2,7 +2,6 @@ model: {
   second: {
     voxel_generator {
       point_cloud_range : [0, -40, -3, 70.4, 40, 1]
-      # point_cloud_range : [0, -32.0, -3, 52.8, 32.0, 1]
       voxel_size : [0.05, 0.05, 0.1]
       max_number_of_points_per_voxel : 5
     }
@@ -48,31 +47,29 @@ model: {
       classification_weight: 1.0
       localization_weight: 2.0
     }
+    num_point_features: 4 # model's num point feature should be independent of dataset
     # Outputs
     use_sigmoid_score: true
     encode_background_as_zeros: true
     encode_rad_error_by_sin: true
 
     use_direction_classifier: true # this can help for orientation benchmark
     direction_loss_weight: 0.2 # enough.
-    use_aux_classifier: false
+
     # Loss
     pos_class_weight: 1.0
     neg_class_weight: 1.0
 
     loss_norm_type: NormByNumPositives
     # Postprocess
-    post_center_limit_range: [0, -40, -3.0, 70.4, 40, 0.0]
+    post_center_limit_range: [0, -40, -2.2, 70.4, 40, 0.8]
     use_rotate_nms: true
     use_multi_class_nms: false
     nms_pre_max_size: 1000
     nms_post_max_size: 100
-    nms_score_threshold: 0.3
+    nms_score_threshold: 0.3 # 0.4 in submit, but 0.3 can get better hard performance
     nms_iou_threshold: 0.01
 
-    use_bev: false
-    num_point_features: 4
-    without_reflectivity: false
     box_coder: {
       ground_box3d_coder: {
         linear_dim: false
@@ -83,7 +80,7 @@ model: {
       anchor_generators: {
         anchor_generator_range: {
           sizes: [1.6, 3.9, 1.56] # wlh
-          anchor_ranges: [0, -40.0, -1.0, 70.4, 40.0, -1.0] # carefully set z center
+          anchor_ranges: [0, -40.0, -1.00, 70.4, 40.0, -1.00] # carefully set z center
           rotations: [0, 1.57] # DON'T modify this unless you are very familiar with my code.
           matched_threshold : 0.6
           unmatched_threshold : 0.45
@@ -100,91 +97,102 @@ model: {
   }
 }
 
-
 train_input_reader: {
-  max_num_epochs : 160
-  batch_size: 6
-  prefetch_size : 25
-  max_number_of_voxels: 16000
-  shuffle_points: true
-  num_workers: 3
-  groundtruth_localization_noise_std: [1.0, 1.0, 0.5]
-  # groundtruth_rotation_uniform_noise: [-0.3141592654, 0.3141592654]
-  # groundtruth_rotation_uniform_noise: [-1.57, 1.57]
-  groundtruth_rotation_uniform_noise: [-0.78539816, 0.78539816]
-  global_rotation_uniform_noise: [-0.78539816, 0.78539816]
-  global_scaling_uniform_noise: [0.95, 1.05]
-  global_random_rotation_range_per_object: [0, 0] # pi/4 ~ 3pi/4
-  anchor_area_threshold: -1
-  remove_points_after_sample: true
-  groundtruth_points_drop_percentage: 0.0
-  groundtruth_drop_max_keep_points: 15
-  database_sampler {
-    database_info_path: "/media/yy/My Passport/datasets/kitti/kitti_dbinfos_train.pkl"
-    sample_groups {
-      name_to_max_num {
-        key: "Car"
-        value: 15
-      }
-    }
-    database_prep_steps {
-      filter_by_min_num_points {
-        min_num_point_pairs {
+  dataset: {
+    dataset_class_name: "KittiDataset"
+    kitti_info_path: "/media/yy/960evo/datasets/kitti/kitti_infos_train.pkl"
+    kitti_root_path: "/media/yy/960evo/datasets/kitti"
+  }
+
+  batch_size: 8
+  preprocess: {
+    max_number_of_voxels: 17000
+    shuffle_points: true
+    num_workers: 3
+    groundtruth_localization_noise_std: [1.0, 1.0, 0.5]
+    # groundtruth_rotation_uniform_noise: [-0.3141592654, 0.3141592654]
+    # groundtruth_rotation_uniform_noise: [-1.57, 1.57]
+    groundtruth_rotation_uniform_noise: [-0.78539816, 0.78539816]
+    global_rotation_uniform_noise: [-0.78539816, 0.78539816]
+    global_scaling_uniform_noise: [0.95, 1.05]
+    global_random_rotation_range_per_object: [0, 0] # pi/4 ~ 3pi/4
+    global_translate_noise_std: [0, 0, 0]
+    anchor_area_threshold: -1
+    remove_points_after_sample: true
+    groundtruth_points_drop_percentage: 0.0
+    groundtruth_drop_max_keep_points: 15
+    remove_unknown_examples: false
+    remove_environment: false
+    database_sampler {
+      database_info_path: "/media/yy/960evo/datasets/kitti/kitti_dbinfos_train.pkl"
+      sample_groups {
+        name_to_max_num {
           key: "Car"
-          value: 5
+          value: 15
         }
       }
-    }
-    database_prep_steps {
-      filter_by_difficulty {
-        removed_difficulties: [-1]
+      database_prep_steps {
+        filter_by_min_num_points {
+          min_num_point_pairs {
+            key: "Car"
+            value: 5
+          }
+        }
+      }
+      database_prep_steps {
+        filter_by_difficulty {
+          removed_difficulties: [-1]
+        }
       }
+      global_random_rotation_range_per_object: [0, 0]
+      rate: 1.0
     }
-    global_random_rotation_range_per_object: [0, 0]
-    rate: 1.0
   }
-
-  remove_unknown_examples: false
-  remove_environment: false
-  kitti_info_path: "/media/yy/My Passport/datasets/kitti/kitti_infos_train.pkl"
-  kitti_root_path: "/media/yy/My Passport/datasets/kitti"
 }
 
 train_config: {
   optimizer: {
     adam_optimizer: {
       learning_rate: {
         one_cycle: {
-          lr_max: 3e-3
+          lr_max: 2.25e-3
           moms: [0.95, 0.85]
           div_factor: 10.0
           pct_start: 0.4
         }
       }
-      weight_decay: 0.01 # super converge. decrease this when you increase steps.
+      weight_decay: 0.01
     }
     fixed_weight_decay: true
     use_moving_average: false
   }
-  steps: 30950 # 619 * 50, super converge. increase this to achieve slightly better results
-  steps_per_eval: 3095 # 619 * 5
+  # steps: 99040 # 1238 * 120
+  # steps: 49520 # 619 * 80
+  # steps: 30950 # 619 * 80
+  # steps_per_eval: 3095 # 619 * 5
+  steps: 23200 # 464 * 50
+  steps_per_eval: 2320 # 464 * 5
+
   save_checkpoints_secs : 1800 # half hour
   save_summary_steps : 10
-  enable_mixed_precision: false 
+  enable_mixed_precision: false
   loss_scale_factor : 8.0
   clear_metrics_every_epoch: true
 }
 
 eval_input_reader: {
-  batch_size: 6
-  max_num_epochs : 160
-  prefetch_size : 25
-  max_number_of_voxels: 40000
-  shuffle_points: false
-  num_workers: 3
-  anchor_area_threshold: -1
-  remove_environment: false
-  kitti_info_path: "/media/yy/My Passport/datasets/kitti/kitti_infos_val.pkl"
-  # kitti_info_path: "/media/yy/My Passport/datasets/kitti/kitti_infos_test.pkl"
-  kitti_root_path: "/media/yy/My Passport/datasets/kitti"
+  dataset: {
+    dataset_class_name: "KittiDataset"
+    kitti_info_path: "/media/yy/960evo/datasets/kitti/kitti_infos_val.pkl"
+    # kitti_info_path: "/media/yy/960evo/datasets/kitti/kitti_infos_test.pkl"
+    kitti_root_path: "/media/yy/960evo/datasets/kitti"
+  }
+  batch_size: 8
+  preprocess: {
+    max_number_of_voxels: 40000
+    shuffle_points: false
+    num_workers: 3
+    anchor_area_threshold: -1
+    remove_environment: false
+  }
 }