
_base_ = [
    '../_base_/models/faster_rcnn_r50_fpn_aitod.py',
    '../_base_/datasets/aitod_detection.py',
    '../_base_/schedules/schedule_1x.py', 
    '../_base_/default_runtime.py'
]

model = dict(
    roi_head=dict(
        bbox_head=dict(
            num_classes=8)),
    # model training and testing settings
    train_cfg=dict(
        rpn=dict(
            assigner=dict(
                gpu_assign_thr=1024)),
        rpn_proposal=dict(
            nms_pre=3000,
            max_per_img=3000,
            nms=dict(type='nms', iou_threshold=0.7),
            min_bbox_size=0),
        rcnn=dict(
            assigner=dict(
                gpu_assign_thr=1024))),
    test_cfg=dict(
        rpn=dict(
            nms_pre=3000,
            max_per_img=3000,
            nms=dict(type='nms', iou_threshold=0.7),
            min_bbox_size=0),
        rcnn=dict(
            score_thr=0.05,
            nms=dict(type='nms', iou_threshold=0.5),
            max_per_img=3000)
        # soft-nms is also supported for rcnn testing
        # e.g., nms=dict(type='soft_nms', iou_threshold=0.5, min_score=0.05)
    ))


# optimizer
optimizer = dict(type='SGD', lr=0.01, momentum=0.9, weight_decay=0.0001)
# learning policy
checkpoint_config = dict(interval=4)
