1# train ae or vae
2#### a template for pcd encoder
3mode: train
4model:
5 # can be AE, VAE, SeM and DDPM
6 name: ClM
7 # encoder config
8 encoder:
9 name: PointNet
10 in_channel: 3
11 out_channel: 46
12 point_num: 2048
13 building_block: dense
14 # num_neighbors_k: 20
15 local_feature_channels: [64, 64, 128, 256, 512]
16 dense_channels: [1024, 512, 256]
17 activation: lrelu
18 normalization: group
19 classification_losses:
20 - name: CE
21loader:
22 dataset:
23 name: PcdClsDataset
24 data_suffix: .ply
25 cls_label: MedPointS
26 data_path_list:
27 - path/to/datasets/pcd/MedPointS/classification/fold1
28 - path/to/datasets/pcd/MedPointS/classification/fold2
29 - path/to/datasets/pcd/MedPointS/classification/fold3
30 batch_size: 16
31 num_workers: 8
32 shuffle: true
33 data_transforms:
34 - name: Normalize
35 - name: FixedPoints
36 num: 2048
37 - name: ToTensor
38 dtype: float
39 label_transforms:
40 - name: ToOneHot
41 num_classes: 47
42 ignore_background: true
43 - name: ToTensor
44 dtype: float
45val_loader:
46 dataset:
47 name: PcdClsDataset
48 data_suffix: .ply
49 cls_label: MedPointS
50 data_path_list:
51 - path/to/datasets/pcd/MedPointS/classification/fold4
52 batch_size: 32
53 num_workers: 8
54 shuffle: true
55 data_transforms:
56 - name: Normalize
57 - name: FixedPoints
58 num: 2048
59 - name: ToTensor
60 dtype: float
61 label_transforms:
62 - name: ToOneHot
63 num_classes: 47
64 ignore_background: true
65 - name: ToTensor
66 dtype: float
67check_point_dir: path/to/flemme-ckp/MedPointS/PointNet/PointNet_CLS
68### parameter for optimizer
69optimizer:
70 name: Adam
71 lr: 0.0001
72 weight_decay: 0.00000001
73evaluation_metrics:
74 cls:
75 - name: ACC
76score_metric:
77 name: ACC
78### scheduler for learning rate
79lr_scheduler:
80 name: LinearLR
81 start_factor: 1.0
82 end_factor: 0.01
83max_epoch: 100
84write_after_iters: 20
85save_after_epochs: 1