284 lines
6.3 KiB
YAML
284 lines
6.3 KiB
YAML
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# 增强版多任务配置：检测 + 分割（Enhanced Segmentation Head）
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#
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# 改进点：
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# 1. EnhancedBEVSegmentationHead (ASPP + 双注意力 + 深层解码器)
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# 2. Focal Loss修复 (alpha=0.25)
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# 3. Dice Loss混合 (weight=0.5)
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# 4. 类别权重平衡 (stop_line×4, divider×3)
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# 5. Deep supervision
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# 6. 分割损失权重×5
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# 7. 学习率降低(复用权重)
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#
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# 复用: epoch_19.pth (93.7%参数)
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# 预期: mIoU 60-65% (2-3天)
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_base_: ./convfuser.yaml
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# 添加分割头和pipeline
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model:
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# 确保fuser配置正确
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fuser:
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type: ConvFuser
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in_channels: [80, 256]
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out_channels: 256
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heads:
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# object head从convfuser.yaml继承
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# 添加增强版map head
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map:
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type: EnhancedBEVSegmentationHead # ← 使用增强版！
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in_channels: 512
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grid_transform:
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input_scope: [[-54.0, 54.0, 0.75], [-54.0, 54.0, 0.75]]
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output_scope: [[-50, 50, 0.5], [-50, 50, 0.5]]
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classes: ${map_classes}
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loss: focal
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# 类别权重（针对nuScenes不平衡）
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loss_weight:
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drivable_area: 1.0
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ped_crossing: 3.0
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walkway: 1.5
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stop_line: 4.0
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carpark_area: 2.0
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divider: 3.0
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# Focal Loss参数
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focal_alpha: 0.25
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focal_gamma: 2.0
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# Dice Loss配置
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use_dice_loss: true
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dice_weight: 0.5
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# Deep Supervision
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deep_supervision: true
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# Decoder配置
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decoder_channels: [256, 256, 128, 128]
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# 损失权重（分割权重×5）
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loss_scale:
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object: 1.0
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map: 5.0
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# 训练epochs
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max_epochs: 20
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# 优化器（降低学习率）
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optimizer:
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lr: 1.0e-4
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# 修改Collect3D，添加gt_masks_bev
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train_pipeline:
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-
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type: LoadMultiViewImageFromFiles
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to_float32: true
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-
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type: LoadPointsFromFile
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coord_type: LIDAR
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load_dim: ${load_dim}
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use_dim: ${use_dim}
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reduce_beams: ${reduce_beams}
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load_augmented: ${load_augmented}
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-
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type: LoadPointsFromMultiSweeps
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sweeps_num: 9
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load_dim: ${load_dim}
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use_dim: ${use_dim}
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reduce_beams: ${reduce_beams}
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pad_empty_sweeps: true
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remove_close: true
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load_augmented: ${load_augmented}
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-
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type: LoadAnnotations3D
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with_bbox_3d: true
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with_label_3d: true
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with_attr_label: False
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-
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type: ObjectPaste
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stop_epoch: ${gt_paste_stop_epoch}
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db_sampler:
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dataset_root: ${dataset_root}
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info_path: ${dataset_root + "nuscenes_dbinfos_train.pkl"}
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rate: 1.0
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prepare:
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filter_by_difficulty: [-1]
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filter_by_min_points:
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car: 5
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truck: 5
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bus: 5
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trailer: 5
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construction_vehicle: 5
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traffic_cone: 5
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barrier: 5
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motorcycle: 5
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bicycle: 5
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pedestrian: 5
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classes: ${object_classes}
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sample_groups:
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car: 2
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truck: 3
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construction_vehicle: 7
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bus: 4
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trailer: 6
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barrier: 2
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motorcycle: 6
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bicycle: 6
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pedestrian: 2
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traffic_cone: 2
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points_loader:
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type: LoadPointsFromFile
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coord_type: LIDAR
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load_dim: ${load_dim}
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use_dim: ${use_dim}
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reduce_beams: ${reduce_beams}
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-
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type: ImageAug3D
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final_dim: ${image_size}
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resize_lim: ${augment2d.resize[0]}
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bot_pct_lim: [0.0, 0.0]
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rot_lim: ${augment2d.rotate}
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rand_flip: true
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is_train: true
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-
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type: GlobalRotScaleTrans
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resize_lim: ${augment3d.scale}
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rot_lim: ${augment3d.rotate}
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trans_lim: ${augment3d.translate}
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is_train: true
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-
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type: LoadBEVSegmentation
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dataset_root: ${dataset_root}
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xbound: [-50.0, 50.0, 0.5]
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ybound: [-50.0, 50.0, 0.5]
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classes: ${map_classes}
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-
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type: RandomFlip3D
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-
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type: PointsRangeFilter
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point_cloud_range: ${point_cloud_range}
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-
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type: ObjectRangeFilter
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point_cloud_range: ${point_cloud_range}
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-
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type: ObjectNameFilter
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classes: ${object_classes}
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-
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type: ImageNormalize
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mean: [0.485, 0.456, 0.406]
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std: [0.229, 0.224, 0.225]
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-
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type: GridMask
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use_h: true
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use_w: true
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max_epoch: ${max_epochs}
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rotate: 1
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offset: false
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ratio: 0.5
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mode: 1
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prob: ${augment2d.gridmask.prob}
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fixed_prob: ${augment2d.gridmask.fixed_prob}
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-
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type: PointShuffle
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-
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type: DefaultFormatBundle3D
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classes: ${object_classes}
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-
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type: Collect3D
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keys:
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- img
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- points
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- gt_bboxes_3d
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- gt_labels_3d
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- gt_masks_bev
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meta_keys:
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- camera_intrinsics
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- camera2ego
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- lidar2ego
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- lidar2camera
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- camera2lidar
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- lidar2image
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- img_aug_matrix
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- lidar_aug_matrix
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-
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type: GTDepth
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keyframe_only: true
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test_pipeline:
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-
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type: LoadMultiViewImageFromFiles
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to_float32: true
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-
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type: LoadPointsFromFile
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coord_type: LIDAR
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load_dim: ${load_dim}
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use_dim: ${use_dim}
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reduce_beams: ${reduce_beams}
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load_augmented: ${load_augmented}
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-
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type: LoadPointsFromMultiSweeps
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sweeps_num: 9
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load_dim: ${load_dim}
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use_dim: ${use_dim}
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reduce_beams: ${reduce_beams}
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pad_empty_sweeps: true
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remove_close: true
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load_augmented: ${load_augmented}
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-
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type: LoadAnnotations3D
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with_bbox_3d: true
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with_label_3d: true
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with_attr_label: False
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-
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type: ImageAug3D
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final_dim: ${image_size}
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resize_lim: ${augment2d.resize[1]}
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bot_pct_lim: [0.0, 0.0]
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rot_lim: [0.0, 0.0]
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rand_flip: false
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is_train: false
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-
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type: GlobalRotScaleTrans
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resize_lim: [1.0, 1.0]
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rot_lim: [0.0, 0.0]
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trans_lim: 0.0
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is_train: false
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-
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type: LoadBEVSegmentation
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dataset_root: ${dataset_root}
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xbound: [-50.0, 50.0, 0.5]
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ybound: [-50.0, 50.0, 0.5]
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classes: ${map_classes}
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-
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type: PointsRangeFilter
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point_cloud_range: ${point_cloud_range}
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-
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type: ImageNormalize
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mean: [0.485, 0.456, 0.406]
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std: [0.229, 0.224, 0.225]
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-
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type: DefaultFormatBundle3D
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classes: ${object_classes}
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-
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type: Collect3D
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keys:
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- img
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- points
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- gt_bboxes_3d
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- gt_labels_3d
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- gt_masks_bev
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meta_keys:
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- camera_intrinsics
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- camera2ego
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- lidar2ego
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- lidar2camera
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- camera2lidar
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- lidar2image
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- img_aug_matrix
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- lidar_aug_matrix
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-
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type: GTDepth
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keyframe_only: true
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