readme

configs/data/base.py

+"""
+The data config will be the last one merged into the main config.
+Setups in data configs will override all existed setups!
+"""
+
+from yacs.config import CfgNode as CN
+_CN = CN()
+_CN.DATASET = CN()
+_CN.TRAINER = CN()
+
+# training data config
+_CN.DATASET.TRAIN_DATA_ROOT = None
+_CN.DATASET.TRAIN_POSE_ROOT = None
+_CN.DATASET.TRAIN_NPZ_ROOT = None
+_CN.DATASET.TRAIN_LIST_PATH = None
+_CN.DATASET.TRAIN_INTRINSIC_PATH = None
+# validation set config
+_CN.DATASET.VAL_DATA_ROOT = None
+_CN.DATASET.VAL_POSE_ROOT = None
+_CN.DATASET.VAL_NPZ_ROOT = None
+_CN.DATASET.VAL_LIST_PATH = None
+_CN.DATASET.VAL_INTRINSIC_PATH = None
+
+# testing data config
+_CN.DATASET.TEST_DATA_ROOT = None
+_CN.DATASET.TEST_POSE_ROOT = None
+_CN.DATASET.TEST_NPZ_ROOT = None
+_CN.DATASET.TEST_LIST_PATH = None
+_CN.DATASET.TEST_INTRINSIC_PATH = None
+
+# dataset config
+_CN.DATASET.MIN_OVERLAP_SCORE_TRAIN = 0.4
+_CN.DATASET.MIN_OVERLAP_SCORE_TEST = 0.0  # for both test and val
+
+cfg = _CN

configs/data/debug/.gitignore

+*
+*/
+!.gitignore

configs/data/megadepth_test_1500.py

+from configs.data.base import cfg
+
+TEST_BASE_PATH = "assets/megadepth_test_1500_scene_info"
+
+cfg.DATASET.TEST_DATA_SOURCE = "MegaDepth"
+cfg.DATASET.TEST_DATA_ROOT = "data/megadepth/test"
+cfg.DATASET.TEST_NPZ_ROOT = f"{TEST_BASE_PATH}"
+cfg.DATASET.TEST_LIST_PATH = f"{TEST_BASE_PATH}/megadepth_test_1500.txt"
+
+cfg.DATASET.MGDPT_IMG_RESIZE = 840
+cfg.DATASET.MIN_OVERLAP_SCORE_TEST = 0.0

configs/data/megadepth_trainval_640.py

+from configs.data.base import cfg
+
+
+TRAIN_BASE_PATH = "data/megadepth/index"
+cfg.DATASET.TRAINVAL_DATA_SOURCE = "MegaDepth"
+cfg.DATASET.TRAIN_DATA_ROOT = "data/megadepth/train"
+cfg.DATASET.TRAIN_NPZ_ROOT = f"{TRAIN_BASE_PATH}/scene_info_0.1_0.7"
+cfg.DATASET.TRAIN_LIST_PATH = f"{TRAIN_BASE_PATH}/trainvaltest_list/train_list.txt"
+cfg.DATASET.MIN_OVERLAP_SCORE_TRAIN = 0.0
+
+TEST_BASE_PATH = "data/megadepth/index"
+cfg.DATASET.TEST_DATA_SOURCE = "MegaDepth"
+cfg.DATASET.VAL_DATA_ROOT = cfg.DATASET.TEST_DATA_ROOT = "data/megadepth/test"
+cfg.DATASET.VAL_NPZ_ROOT = cfg.DATASET.TEST_NPZ_ROOT = f"{TEST_BASE_PATH}/scene_info_val_1500"
+cfg.DATASET.VAL_LIST_PATH = cfg.DATASET.TEST_LIST_PATH = f"{TEST_BASE_PATH}/trainvaltest_list/val_list.txt"
+cfg.DATASET.MIN_OVERLAP_SCORE_TEST = 0.0   # for both test and val
+
+# 368 scenes in total for MegaDepth
+# (with difficulty balanced (further split each scene to 3 sub-scenes))
+cfg.TRAINER.N_SAMPLES_PER_SUBSET = 100
+
+cfg.DATASET.MGDPT_IMG_RESIZE = 640  # for training on 11GB mem GPUs

configs/data/megadepth_trainval_840.py

+from configs.data.base import cfg
+
+
+TRAIN_BASE_PATH = "data/megadepth/index"
+cfg.DATASET.TRAINVAL_DATA_SOURCE = "MegaDepth"
+cfg.DATASET.TRAIN_DATA_ROOT = "data/megadepth/train"
+cfg.DATASET.TRAIN_NPZ_ROOT = f"{TRAIN_BASE_PATH}/scene_info_0.1_0.7"
+cfg.DATASET.TRAIN_LIST_PATH = f"{TRAIN_BASE_PATH}/trainvaltest_list/train_list.txt"
+cfg.DATASET.MIN_OVERLAP_SCORE_TRAIN = 0.0
+
+TEST_BASE_PATH = "data/megadepth/index"
+cfg.DATASET.TEST_DATA_SOURCE = "MegaDepth"
+cfg.DATASET.VAL_DATA_ROOT = cfg.DATASET.TEST_DATA_ROOT = "data/megadepth/test"
+cfg.DATASET.VAL_NPZ_ROOT = cfg.DATASET.TEST_NPZ_ROOT = f"{TEST_BASE_PATH}/scene_info_val_1500"
+cfg.DATASET.VAL_LIST_PATH = cfg.DATASET.TEST_LIST_PATH = f"{TEST_BASE_PATH}/trainvaltest_list/val_list.txt"
+cfg.DATASET.MIN_OVERLAP_SCORE_TEST = 0.0   # for both test and val
+
+# 368 scenes in total for MegaDepth
+# (with difficulty balanced (further split each scene to 3 sub-scenes))
+cfg.TRAINER.N_SAMPLES_PER_SUBSET = 100
+
+cfg.DATASET.MGDPT_IMG_RESIZE = 840  # for training on 32GB meme GPUs

configs/data/scannet_test_1500.py

+from configs.data.base import cfg
+
+TEST_BASE_PATH = "assets/scannet_test_1500"
+
+cfg.DATASET.TEST_DATA_SOURCE = "ScanNet"
+cfg.DATASET.TEST_DATA_ROOT = "data/scannet/test"
+cfg.DATASET.TEST_NPZ_ROOT = f"{TEST_BASE_PATH}"
+cfg.DATASET.TEST_LIST_PATH = f"{TEST_BASE_PATH}/scannet_test.txt"
+cfg.DATASET.TEST_INTRINSIC_PATH = f"{TEST_BASE_PATH}/intrinsics.npz"
+
+cfg.DATASET.MIN_OVERLAP_SCORE_TEST = 0.0

configs/data/scannet_trainval.py

+from configs.data.base import cfg
+
+
+TRAIN_BASE_PATH = "data/scannet/index"
+cfg.DATASET.TRAINVAL_DATA_SOURCE = "ScanNet"
+cfg.DATASET.TRAIN_DATA_ROOT = "data/scannet/train"
+cfg.DATASET.TRAIN_NPZ_ROOT = f"{TRAIN_BASE_PATH}/scene_data/train"
+cfg.DATASET.TRAIN_LIST_PATH = f"{TRAIN_BASE_PATH}/scene_data/train_list/scannet_all.txt"
+cfg.DATASET.TRAIN_INTRINSIC_PATH = f"{TRAIN_BASE_PATH}/intrinsics.npz"
+
+TEST_BASE_PATH = "assets/scannet_test_1500"
+cfg.DATASET.TEST_DATA_SOURCE = "ScanNet"
+cfg.DATASET.VAL_DATA_ROOT = cfg.DATASET.TEST_DATA_ROOT = "data/scannet/test"
+cfg.DATASET.VAL_NPZ_ROOT = cfg.DATASET.TEST_NPZ_ROOT = TEST_BASE_PATH
+cfg.DATASET.VAL_LIST_PATH = cfg.DATASET.TEST_LIST_PATH = f"{TEST_BASE_PATH}/scannet_test.txt"
+cfg.DATASET.VAL_INTRINSIC_PATH = cfg.DATASET.TEST_INTRINSIC_PATH = f"{TEST_BASE_PATH}/intrinsics.npz"
+cfg.DATASET.MIN_OVERLAP_SCORE_TEST = 0.0   # for both test and val

configs/loftr/indoor/buggy_pos_enc/loftr_ds.py

+from src.config.default import _CN as cfg
+
+cfg.LOFTR.COARSE.TEMP_BUG_FIX = False
+cfg.LOFTR.MATCH_COARSE.MATCH_TYPE = 'dual_softmax'
+
+cfg.TRAINER.MSLR_MILESTONES = [3, 6, 9, 12, 17, 20, 23, 26, 29]

configs/loftr/indoor/buggy_pos_enc/loftr_ds_dense.py

+from src.config.default import _CN as cfg
+
+cfg.LOFTR.COARSE.TEMP_BUG_FIX = False
+cfg.LOFTR.MATCH_COARSE.MATCH_TYPE = 'dual_softmax'
+
+cfg.LOFTR.MATCH_COARSE.SPARSE_SPVS = False
+
+cfg.TRAINER.MSLR_MILESTONES = [3, 6, 9, 12, 17, 20, 23, 26, 29]

configs/loftr/indoor/buggy_pos_enc/loftr_ot.py

+from src.config.default import _CN as cfg
+
+cfg.LOFTR.COARSE.TEMP_BUG_FIX = False
+cfg.LOFTR.MATCH_COARSE.MATCH_TYPE = 'sinkhorn'
+
+cfg.TRAINER.MSLR_MILESTONES = [3, 6, 9, 12, 17, 20, 23, 26, 29]

configs/loftr/indoor/buggy_pos_enc/loftr_ot_dense.py

+from src.config.default import _CN as cfg
+
+cfg.LOFTR.COARSE.TEMP_BUG_FIX = False
+cfg.LOFTR.MATCH_COARSE.MATCH_TYPE = 'sinkhorn'
+
+cfg.LOFTR.MATCH_COARSE.SPARSE_SPVS = False
+
+cfg.TRAINER.MSLR_MILESTONES = [3, 6, 9, 12, 17, 20, 23, 26, 29]

configs/loftr/indoor/debug/.gitignore

+*
+*/
+!.gitignore

configs/loftr/indoor/loftr_ds.py

+from src.config.default import _CN as cfg
+
+cfg.LOFTR.MATCH_COARSE.MATCH_TYPE = 'dual_softmax'
+
+cfg.TRAINER.MSLR_MILESTONES = [3, 6, 9, 12, 17, 20, 23, 26, 29]

configs/loftr/indoor/loftr_ds_dense.py

+from src.config.default import _CN as cfg
+
+cfg.LOFTR.MATCH_COARSE.MATCH_TYPE = 'dual_softmax'
+
+cfg.LOFTR.MATCH_COARSE.SPARSE_SPVS = False
+
+cfg.TRAINER.MSLR_MILESTONES = [3, 6, 9, 12, 17, 20, 23, 26, 29]

configs/loftr/indoor/loftr_ot.py

+from src.config.default import _CN as cfg
+
+cfg.LOFTR.MATCH_COARSE.MATCH_TYPE = 'sinkhorn'
+
+cfg.TRAINER.MSLR_MILESTONES = [3, 6, 9, 12, 17, 20, 23, 26, 29]

configs/loftr/indoor/loftr_ot_dense.py

+from src.config.default import _CN as cfg
+
+cfg.LOFTR.MATCH_COARSE.MATCH_TYPE = 'sinkhorn'
+
+cfg.LOFTR.MATCH_COARSE.SPARSE_SPVS = False
+
+cfg.TRAINER.MSLR_MILESTONES = [3, 6, 9, 12, 17, 20, 23, 26, 29]

configs/loftr/indoor/scannet/loftr_ds_eval.py

+""" A config only for reproducing the ScanNet evaluation results.
+
+We remove border matches by default, but the originally implemented
+`remove_border()` has a bug, leading to only two sides of
+all borders are actually removed. However, the [bug fix](https://github.com/zju3dv/LoFTR/commit/e9146c8144dea5f3cbdd98b225f3e147a171c216)
+makes the scannet evaluation results worse (auc@10=40.8 => 39.5), which should be
+caused by tiny result fluctuation of few image pairs. This config set `BORDER_RM` to 0
+to be consistent with the results in our paper.
+"""
+
+from src.config.default import _CN as cfg
+
+cfg.LOFTR.COARSE.TEMP_BUG_FIX = False
+cfg.LOFTR.MATCH_COARSE.MATCH_TYPE = 'dual_softmax'
+
+cfg.LOFTR.MATCH_COARSE.BORDER_RM = 0

configs/loftr/indoor/scannet/loftr_ds_eval_new.py

+""" A config only for reproducing the ScanNet evaluation results.
+
+We remove border matches by default, but the originally implemented
+`remove_border()` has a bug, leading to only two sides of
+all borders are actually removed. However, the [bug fix](https://github.com/zju3dv/LoFTR/commit/e9146c8144dea5f3cbdd98b225f3e147a171c216)
+makes the scannet evaluation results worse (auc@10=40.8 => 39.5), which should be
+caused by tiny result fluctuation of few image pairs. This config set `BORDER_RM` to 0
+to be consistent with the results in our paper.
+
+Update: This config is for testing the re-trained model with the pos-enc bug fixed.
+"""
+
+from src.config.default import _CN as cfg
+
+cfg.LOFTR.COARSE.TEMP_BUG_FIX = True
+cfg.LOFTR.MATCH_COARSE.MATCH_TYPE = 'dual_softmax'
+
+cfg.LOFTR.MATCH_COARSE.BORDER_RM = 0

configs/loftr/outdoor/buggy_pos_enc/loftr_ds.py

+from src.config.default import _CN as cfg
+
+cfg.LOFTR.COARSE.TEMP_BUG_FIX = False
+cfg.LOFTR.MATCH_COARSE.MATCH_TYPE = 'dual_softmax'
+
+cfg.TRAINER.CANONICAL_LR = 8e-3
+cfg.TRAINER.WARMUP_STEP = 1875  # 3 epochs
+cfg.TRAINER.WARMUP_RATIO = 0.1
+cfg.TRAINER.MSLR_MILESTONES = [8, 12, 16, 20, 24]
+
+# pose estimation
+cfg.TRAINER.RANSAC_PIXEL_THR = 0.5
+
+cfg.TRAINER.OPTIMIZER = "adamw"
+cfg.TRAINER.ADAMW_DECAY = 0.1
+cfg.LOFTR.MATCH_COARSE.TRAIN_COARSE_PERCENT = 0.3

configs/loftr/outdoor/buggy_pos_enc/loftr_ds_dense.py

+from src.config.default import _CN as cfg
+
+cfg.LOFTR.COARSE.TEMP_BUG_FIX = False
+cfg.LOFTR.MATCH_COARSE.MATCH_TYPE = 'dual_softmax'
+cfg.LOFTR.MATCH_COARSE.SPARSE_SPVS = False
+
+cfg.TRAINER.CANONICAL_LR = 8e-3
+cfg.TRAINER.WARMUP_STEP = 1875  # 3 epochs
+cfg.TRAINER.WARMUP_RATIO = 0.1
+cfg.TRAINER.MSLR_MILESTONES = [8, 12, 16, 20, 24]
+
+# pose estimation
+cfg.TRAINER.RANSAC_PIXEL_THR = 0.5
+
+cfg.TRAINER.OPTIMIZER = "adamw"
+cfg.TRAINER.ADAMW_DECAY = 0.1
+cfg.LOFTR.MATCH_COARSE.TRAIN_COARSE_PERCENT = 0.3