28 lines
889 B
YAML
28 lines
889 B
YAML
_BASE_: "../Base-RCNN-FPN.yaml"
|
|
MODEL:
|
|
# WEIGHTS: "detectron2://ImageNetPretrained/MSRA/R-50.pkl"
|
|
# For better, more stable performance initialize from COCO
|
|
WEIGHTS: "detectron2://COCO-InstanceSegmentation/mask_rcnn_R_50_FPN_3x/137849600/model_final_f10217.pkl"
|
|
MASK_ON: True
|
|
ROI_HEADS:
|
|
NUM_CLASSES: 8
|
|
# This is similar to the setting used in Mask R-CNN paper, Appendix A
|
|
# But there are some differences, e.g., we did not initialize the output
|
|
# layer using the corresponding classes from COCO
|
|
INPUT:
|
|
MIN_SIZE_TRAIN: (800, 832, 864, 896, 928, 960, 992, 1024)
|
|
MIN_SIZE_TRAIN_SAMPLING: "choice"
|
|
MIN_SIZE_TEST: 1024
|
|
MAX_SIZE_TRAIN: 2048
|
|
MAX_SIZE_TEST: 2048
|
|
DATASETS:
|
|
TRAIN: ("cityscapes_fine_instance_seg_train",)
|
|
TEST: ("cityscapes_fine_instance_seg_val",)
|
|
SOLVER:
|
|
BASE_LR: 0.01
|
|
STEPS: (18000,)
|
|
MAX_ITER: 24000
|
|
IMS_PER_BATCH: 8
|
|
TEST:
|
|
EVAL_PERIOD: 8000
|