mirror of
https://github.com/botastic/SoftGroup.git
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72 lines
1.7 KiB
YAML
72 lines
1.7 KiB
YAML
model:
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channels: 32
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num_blocks: 7
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semantic_classes: 13
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instance_classes: 13
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sem2ins_classes: [0, 1]
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semantic_only: False
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ignore_label: -100
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grouping_cfg:
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score_thr: 0.2
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radius: 0.04
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mean_active: 300
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class_numpoint_mean: [1823, 7457, 6189, 7424, 34229, 1724, 5439,
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6016, 39796, 5279, 5092, 12210, 10225]
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npoint_thr: 0.05 # absolute if class_numpoint == -1, relative if class_numpoint != -1
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ignore_classes: [0, 1]
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instance_voxel_cfg:
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scale: 50
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spatial_shape: 20
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train_cfg:
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max_proposal_num: 200
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pos_iou_thr: 0.5
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test_cfg:
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x4_split: True
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cls_score_thr: 0.001
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mask_score_thr: -0.5
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min_npoint: 100
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fixed_modules: ['input_conv', 'unet', 'output_layer', 'semantic_linear', 'offset_linear']
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data:
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train:
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type: 's3dis'
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data_root: 'dataset/s3dis/preprocess'
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prefix: ['Area_1', 'Area_2', 'Area_3', 'Area_4', 'Area_6']
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suffix: '_inst_nostuff.pth'
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repeat: 5
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training: True
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voxel_cfg:
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scale: 50
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spatial_shape: [128, 512]
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max_npoint: 250000
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min_npoint: 5000
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test:
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type: 's3dis'
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data_root: 'dataset/s3dis/preprocess'
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prefix: 'Area_5'
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suffix: '_inst_nostuff.pth'
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training: False
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voxel_cfg:
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scale: 50
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spatial_shape: [128, 512]
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max_npoint: 250000
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min_npoint: 5000
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dataloader:
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train:
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batch_size: 4
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num_workers: 4
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test:
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batch_size: 1
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num_workers: 1
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optimizer:
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type: 'Adam'
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lr: 0.001
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epochs: 30 # actual epochs = 30 * repeat
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step_epoch: 0
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save_freq: 2
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pretrain: 'exp/s3dis/softgroup/softgroup_fold5_s3dis/softgroup_fold5_s3dis-000000030.pth'
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work_dir: 'work_dirs/softgroup_s3dis'
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