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from mmengine import read_base | |
from seg.models.detectors import Mask2formerVideoMinVIS | |
with read_base(): | |
from .datasets.vipseg import * | |
from .models.m2_convl_300q import * | |
model.update( | |
data_preprocessor=data_preprocessor, | |
type=Mask2formerVideoMinVIS, | |
clip_size=2, | |
clip_size_small=3, | |
whole_clip_thr=0, | |
small_clip_thr=15, | |
overlap=0, | |
panoptic_head=dict( | |
ov_classifier_name=f'{ov_model_name}_{ov_datasets_name}', | |
num_things_classes=num_things_classes, | |
num_stuff_classes=num_stuff_classes, | |
), | |
panoptic_fusion_head=dict( | |
num_things_classes=num_things_classes, | |
num_stuff_classes=num_stuff_classes, | |
), | |
test_cfg=dict( | |
panoptic_on=True, | |
semantic_on=False, | |
instance_on=False, | |
), | |
) | |
val_evaluator = dict( | |
type=VIPSegMetric, | |
metric=['VPQ@1', 'VPQ@2', 'VPQ@4', 'VPQ@6'], | |
format_only=True, | |
) | |
test_evaluator = val_evaluator | |