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proj_e2e_GOT_unconstrained_v2.yaml
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#accept supervised or unsupervised data in a batch
META_ARC: "hdn_r50_l234_pot"
BACKBONE_HOMO:
TYPE: "resnet34"
KWARGS:
used_layers: [4] # in deep-homo default use only the last layer
TRAIN_LAYERS: ['layer2', 'layer3', 'layer4']
TRAIN_EPOCH: 0
LAYERS_LR: 0.1
IF_PRETRAINED: True # False
BACKBONE:
TYPE: "resnet50"
KWARGS:
used_layers: [2, 3, 4]
PRETRAINED: 'pretrained_models/resnet50.model'
TRAIN_LAYERS: ['layer2', 'layer3', 'layer4']
TRAIN_EPOCH: 40
LAYERS_LR: 0.1
IF_PRETRAINED: False #True
ADJUST:
ADJUST: True
TYPE: "AdjustAllLayer"
KWARGS:
in_channels: [512, 1024, 2048]
out_channels: [256, 256, 256]
BAN:
BAN: True
TYPE: 'MultiBAN'
KWARGS:
in_channels: [256, 256, 256]
cls_out_channels: 2 # if use sigmoid cls, cls_out_channel = 1 else 2
weighted: True
BAN_LP:
BAN: True
TYPE: 'MultiCircBAN'
KWARGS:
in_channels: [256, 256, 256]
cls_out_channels: 2 # if use sigmoid cls, cls_out_channel = 1 else 2
weighted: True
POINT:
STRIDE: 8
STRIDE_LP: 8
TRACK:
TYPE: 'hdnTrackerHomoProje2e'
WINDOW_INFLUENCE: 0.1632532824922313 # POT 0.1632532824922313
PENALTY_K: 0.08513642556896711 # VOT2018
LR: 0.44418184746462425 # VOT2018
BASE_SC_FAC: 2.0 #search sscale factor
SCALE_SCORE_THRESH: 0.5 #over this value, we need to enlarge the region of search
EXEMPLAR_SIZE: 127
INSTANCE_SIZE: 255
BASE_SIZE: 8
CONTEXT_AMOUNT: 0.5 #0.0 the larger value the larger patch range
TRAIN:
OBJ: 'ALL' # 'ALL', 'SIM', 'HOMO', 'LP', we have simplified the procedure, and there is only ALL option
MODEL_TYPE: 'E2E'
PRINT_FREQ: 30
WEIGHTED_MAP_LP: False
EPOCH: 30 #30 best
START_EPOCH: 0 # 0 or resume checkpoint
BATCH_SIZE: 32 #1
HOMO_START_LR: 0.0002
BASE_LR: 0.0002 #0.0003 0.00005 0.0002
OUTPUT_SIZE_LP: 13
CLS_WEIGHT: 1.0
LOC_WEIGHT: 1.0
FEATURE_DIS_WEIGHT: 0.005 #orign: 1.0
# RESUME: 'experiments/tracker_homo_config/snapshot/xxx.pth'
# RESUME: 'experiments/hdn_r50_l234/snapshot/pot_occ_top_k_e4.pth' # simi
# RESUME: 'model/model_vot.pth' # hdn
NUM_WORKERS: 2
DISTRIBUTED: True
LR:
TYPE: 'log'
KWARGS:
start_lr: 0.0012
end_lr: 0.000002
LR_WARMUP:
# WARMUP: False
TYPE: 'step'
EPOCH: 1 #1
KWARGS:
start_lr: 0.001
end_lr: 0.002
step: 1
SAVE_LOGS: False
LOG_GRADS: False
DATASET:
# POT_E2E:
# SUPERVISED_FRAME_RANGE: 0
# UNSUPERVISED_FRAME_RANGE: 3
NAMES:
- 'GOT10K_E2E'
- 'GOT10K_E2E_UNSUP'
# - 'POT_E2E'
# - 'POT_E2E_UNSUP'
# - 'POT'
- 'COCO14'
#
VAL_NAMES:
- 'GOT_HOMO_VAL'
TYPE: 'unconstrained_v2_dataset' #'simi_aug_homo_dataset semi_supervised_dataset_debug
VIDEOS_PER_EPOCH: 100000
TEMPLATE:
SHIFT: 0 #4
SCALE: 1.05
BLUR: 0.02 #0.1
FLIP: 0.0
ROTATION: 0.05
COLOR: 0.8
DISTORTION: 0.0
AFFINE_A: 0.0
AFFINE_C: 0.0
AFFINE_D: 0.0
UNSUPERVISED:
SHIFT: 5 #4
SCALE: 1.05
BLUR: 0.02 #0.1
FLIP: 0.0
ROTATION: 0.05 #0.01 0.8 0.4 0.0
COLOR: 0.8
DISTORTION: 0.0
AFFINE_A: 0.0
AFFINE_C: 0.0
AFFINE_D: 0.0
IMG_COMP_ALPHA: 1.0
IMG_COMP_BETA: 0.0
IMG_COMP_GAMMA: 0.0
SEARCH:
SHIFT: 32
SCALE: 1.38
BLUR: 0.02
FLIP: 0.0
COLOR: 0.8
ROTATION: 0.65
DISTORTION: 0.0015
AFFINE_A: 0.1
AFFINE_C: 0.15
AFFINE_D: 0.0
UNSUPERVISED:
SHIFT: 32
SCALE: 1.28
BLUR: 0.02
FLIP: 0.0
COLOR: 0.8
ROTATION: 0.7
DISTORTION: 0.0
AFFINE_A: 0.0
AFFINE_C: 0.0
AFFINE_D: 0.0
IMG_COMP_ALPHA: 1.0
IMG_COMP_BETA: 0.0
IMG_COMP_GAMMA: 0.0
OCC: 0.3
NEG: 0.2
GRAY: 0.0
LIGHT: 0.06
DARK: 0.06