stgcn.py

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model = dict(
    type='STGCNRunner',
    backbone=dict(
        type='STGCN',
        in_channels = 3,
        graph_args = dict(layout = 'coco', strategy='spatial'),
        edge_importance_weighting = True,
        dropout=0.5,
    ),
    head=dict(
        type='STGCNHead',
        in_channels = 256,
        num_class = 17
    ),
    device='cuda:0'
)
 
loss = dict(
    CrossEntropyLoss = dict(
        weight = 1.0,
        weights = [1.0],
        pred_keys = ['scores'],
        gt_keys = ['label']
    )
)
 
data_loader = dict(
    type = 'ActionDatasetLoader',
    train_data_folder = '/media/safemotion/HDD5/pjm_test/action_2023_pkl_2',
    test_data_folder = '/media/safemotion/HDD5/pjm_test/action_2023_pkl_2',
    use_normalize = True,
)
 
train = dict(
    num_workers = 8,
    init_lr = 0.01,
    batch_size = 16,
    epochs = 10,
    optimizer = 'SGD',
    optimizer_args = dict(momentum=0.9, nesterov=True, weight_decay=0.0001),
    adjust_lr_epoch = [50, 100, 150, 200],
    adjust_lr_rate = [0.1]*4,    
    val_interval = 1,
    
    pretrained = '/media/safemotion/HDD5/pjm_test/action_train_test/9.pth',
    save_root = '/media/safemotion/HDD5/pjm_test/action_train_test',
 
)
 
test = dict(
    model_path = '',
    save_root = '',
)