How to make a dataset for video instance segmentation model？ about dvis

[SuppurNewer]

DATASETS:
DATASET_NEED_MAP: [True, False, ]
DATASET_TYPE: ['image_instance', 'video_instance', ]
DATASET_TYPE_TEST: ['video_instance', ]
DATASET_RATIO: [1.0, 0.75]
TRAIN: ("coco2ytvis2019_train", "mydata_train")
TEST: ("mydata_val",)

[zhang-tao-whu]

Hello, thanks for your attention. Please refer to here for the annotation format of YTVIS. The format of instance annotation is basically the same as COCO, but the difference is that bboxes and segmentations are lists of length T, which include the annotations of the object in all frames, with None used as a placeholder for frames where the object does not appear.

[zhang-tao-whu]

If you want to train on the COCO dataset and your own dataset jointly, and if the categories in your dataset are inconsistent with those in YTVIS19, you will need to implement a category mapping to convert the COCO annotations to your dataset. Please refer to here