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| # Copyright (c) Facebook, Inc. and its affiliates. | |
| # Copyright (c) Meta Platforms, Inc. All Rights Reserved | |
| from detectron2.config import CfgNode as CN | |
| def add_mask_former_default_config(cfg): | |
| # data config | |
| # select the dataset mapper | |
| cfg.INPUT.DATASET_MAPPER_NAME = "mask_former_semantic" | |
| # Color augmentation | |
| cfg.INPUT.COLOR_AUG_SSD = False | |
| # We retry random cropping until no single category in semantic segmentation GT occupies more | |
| # than `SINGLE_CATEGORY_MAX_AREA` part of the crop. | |
| cfg.INPUT.CROP.SINGLE_CATEGORY_MAX_AREA = 1.0 | |
| # Pad image and segmentation GT in dataset mapper. | |
| cfg.INPUT.SIZE_DIVISIBILITY = -1 | |
| # solver config | |
| # test batch size | |
| cfg.SOLVER.TEST_IMS_PER_BATCH = 1 | |
| # weight decay on embedding | |
| cfg.SOLVER.WEIGHT_DECAY_EMBED = 0.0 | |
| # optimizer | |
| cfg.SOLVER.OPTIMIZER = "ADAMW" | |
| cfg.SOLVER.BACKBONE_MULTIPLIER = 0.1 | |
| # mask_former model config | |
| cfg.MODEL.MASK_FORMER = CN() | |
| # loss | |
| cfg.MODEL.MASK_FORMER.DEEP_SUPERVISION = True | |
| cfg.MODEL.MASK_FORMER.NO_OBJECT_WEIGHT = 0.1 | |
| cfg.MODEL.MASK_FORMER.DICE_WEIGHT = 1.0 | |
| cfg.MODEL.MASK_FORMER.MASK_WEIGHT = 20.0 | |
| # transformer config | |
| cfg.MODEL.MASK_FORMER.NHEADS = 8 | |
| cfg.MODEL.MASK_FORMER.DROPOUT = 0.1 | |
| cfg.MODEL.MASK_FORMER.DIM_FEEDFORWARD = 2048 | |
| cfg.MODEL.MASK_FORMER.ENC_LAYERS = 0 | |
| cfg.MODEL.MASK_FORMER.DEC_LAYERS = 6 | |
| cfg.MODEL.MASK_FORMER.PRE_NORM = False | |
| cfg.MODEL.MASK_FORMER.HIDDEN_DIM = 256 | |
| cfg.MODEL.MASK_FORMER.NUM_OBJECT_QUERIES = 100 | |
| cfg.MODEL.MASK_FORMER.TRANSFORMER_IN_FEATURE = "res5" | |
| cfg.MODEL.MASK_FORMER.ENFORCE_INPUT_PROJ = False | |
| # mask_former inference config | |
| cfg.MODEL.MASK_FORMER.TEST = CN() | |
| cfg.MODEL.MASK_FORMER.TEST.PANOPTIC_ON = False | |
| cfg.MODEL.MASK_FORMER.TEST.OBJECT_MASK_THRESHOLD = 0.0 | |
| cfg.MODEL.MASK_FORMER.TEST.OVERLAP_THRESHOLD = 0.0 | |
| cfg.MODEL.MASK_FORMER.TEST.SEM_SEG_POSTPROCESSING_BEFORE_INFERENCE = False | |
| # Sometimes `backbone.size_divisibility` is set to 0 for some backbone (e.g. ResNet) | |
| # you can use this config to override | |
| cfg.MODEL.MASK_FORMER.SIZE_DIVISIBILITY = 32 | |
| # pixel decoder config | |
| cfg.MODEL.SEM_SEG_HEAD.MASK_DIM = 256 | |
| # adding transformer in pixel decoder | |
| cfg.MODEL.SEM_SEG_HEAD.TRANSFORMER_ENC_LAYERS = 0 | |
| # pixel decoder | |
| cfg.MODEL.SEM_SEG_HEAD.PIXEL_DECODER_NAME = "BasePixelDecoder" | |
| # swin transformer backbone | |
| cfg.MODEL.SWIN = CN() | |
| cfg.MODEL.SWIN.PRETRAIN_IMG_SIZE = 224 | |
| cfg.MODEL.SWIN.PATCH_SIZE = 4 | |
| cfg.MODEL.SWIN.EMBED_DIM = 96 | |
| cfg.MODEL.SWIN.DEPTHS = [2, 2, 6, 2] | |
| cfg.MODEL.SWIN.NUM_HEADS = [3, 6, 12, 24] | |
| cfg.MODEL.SWIN.WINDOW_SIZE = 7 | |
| cfg.MODEL.SWIN.MLP_RATIO = 4.0 | |
| cfg.MODEL.SWIN.QKV_BIAS = True | |
| cfg.MODEL.SWIN.QK_SCALE = None | |
| cfg.MODEL.SWIN.NORM_INDICES = None | |
| cfg.MODEL.SWIN.PROJECTION = False | |
| cfg.MODEL.SWIN.PROJECT_DIM = 256 | |
| cfg.MODEL.SWIN.DROP_RATE = 0.0 | |
| cfg.MODEL.SWIN.ATTN_DROP_RATE = 0.0 | |
| cfg.MODEL.SWIN.DROP_PATH_RATE = 0.3 | |
| cfg.MODEL.SWIN.APE = False | |
| cfg.MODEL.SWIN.PATCH_NORM = True | |
| cfg.MODEL.SWIN.OUT_FEATURES = ["res2", "res3", "res4", "res5"] | |
| def add_our_config(cfg): | |
| cfg.TEST.SLIDING_WINDOW = False | |
| cfg.TEST.SLIDING_TILE_SIZE = 224 | |
| cfg.TEST.SLIDING_OVERLAP = 2 / 3.0 | |
| # whether to use dense crf | |
| cfg.TEST.DENSE_CRF = False | |
| cfg.DATASETS.SAMPLE_PER_CLASS = -1 | |
| cfg.DATASETS.SAMPLE_SEED = 0 | |
| # embedding head | |
| cfg.MODEL.SEM_SEG_HEAD.EMBEDDING_DIM = 512 | |
| cfg.MODEL.SEM_SEG_HEAD.EMBED_HIDDEN_DIM = 1024 | |
| cfg.MODEL.SEM_SEG_HEAD.EMBED_LAYERS = 2 | |
| # clip_adapter | |
| cfg.MODEL.CLIP_ADAPTER = CN() | |
| cfg.MODEL.CLIP_ADAPTER.TEXT_TEMPLATES = "vild" | |
| # for predefined | |
| cfg.MODEL.CLIP_ADAPTER.PREDEFINED_PROMPT_TEMPLATES = ["a photo of a {}."] | |
| # for learnable prompt | |
| cfg.MODEL.CLIP_ADAPTER.PROMPT_CHECKPOINT = "" | |
| cfg.MODEL.CLIP_ADAPTER.CLIP_MODEL_NAME = "ViT-B/16" | |
| cfg.MODEL.CLIP_ADAPTER.MASK_FILL = "mean" | |
| cfg.MODEL.CLIP_ADAPTER.MASK_EXPAND_RATIO = 1.0 | |
| cfg.MODEL.CLIP_ADAPTER.MASK_THR = 0.4 | |
| cfg.MODEL.CLIP_ADAPTER.MASK_MATTING = False | |
| cfg.MODEL.CLIP_ADAPTER.REGION_RESIZED = True | |
| cfg.MODEL.CLIP_ADAPTER.CLIP_ENSEMBLE = True | |
| cfg.MODEL.CLIP_ADAPTER.CLIP_ENSEMBLE_WEIGHT = 0.7 | |
| # for mask prompt | |
| cfg.MODEL.CLIP_ADAPTER.MASK_PROMPT_DEPTH = 3 | |
| cfg.MODEL.CLIP_ADAPTER.MASK_PROMPT_FWD = False | |
| # wandb | |
| cfg.WANDB = CN() | |
| cfg.WANDB.PROJECT = "open_vocab_seg" | |
| cfg.WANDB.NAME = None | |
| def add_ovseg_config(cfg): | |
| """ | |
| Add config for open_vocab_seg. | |
| """ | |
| add_mask_former_default_config(cfg) | |
| add_our_config(cfg) | |