_base_ = '../yolov8/yolov8_x_mask-refine_syncbn_fast_8xb16-500e_coco.py'

# -----data related-----
data_root = '/data/si/darwin/si/'  # Root path of data
class_list = ('02','03')

persistent_workers = True

train_dataloader = dict(
    batch_size=8,
    num_workers=16,
    dataset=dict(
        data_root=data_root,
        ann_file='/data/si/darwin/hdworker/train_balance.json',
        data_prefix=dict(img='construction_signalman/images/'),
        metainfo=dict(classes=class_list)))

val_dataloader = dict(
    batch_size=8,
    num_workers=16,
    dataset=dict(
        data_root=data_root,
        ann_file='/data/si/darwin/hdworker/test_balance.json',
        data_prefix=dict(img='construction_signalman/images/'),
        metainfo=dict(classes=class_list)))

test_dataloader = val_dataloader

model = dict(
    # 固定整个 backbone 权重，不进行训练
    bbox_head=dict(
        head_module=dict(num_classes=2)),
    train_cfg=dict(
            assigner=dict(
                num_classes=2)))

val_evaluator = dict(
    ann_file='/data/si/darwin/hdworker/test_balance.json')
test_evaluator = dict(
    ann_file='/data/si/darwin/hdworker/test_balance.json')

find_unused_parameters=True

load_from = '/data/si/DLenc/mmyolo/pretrained/yolov8_x_mask-refine_syncbn_fast_8xb16-500e_coco_20230217_120411-079ca8d1.pth'