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r50_deformable_detr_motip_dancetrack.yaml
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r50_deformable_detr_motip_dancetrack.yaml
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SUPER_CONFIG_PATH:
MODE: # "train" or "eval" or "submit", for the main.py script.
# System config, like CPU/GPU
NUM_CPU_PER_GPU: # number of CPU per GPU
NUM_WORKERS: 6
DEVICE: cuda
AVAILABLE_GPUS: 0,1,2,3,4,5,6,7
# Git version:
GIT_VERSION: # you should input the git version here, if you are using wandb to log your experiments.
# Datasets:
DATASETS: [DanceTrack] # for joint training, there may be multiple datasets, like: [CrowdHuman, MOT17]
DATASET_SPLITS: [train] # and corresponding splits, like: [train, val]
DATA_ROOT: ./datasets/ # datasets root
# Sampling settings:
SAMPLE_STEPS: [0]
SAMPLE_LENGTHS: [40]
SAMPLE_MODES: [random_interval]
SAMPLE_INTERVALS: [4]
# Data augmentation setting:
AUG_RESIZE_SCALES: [480, 512, 544, 576, 608, 640, 672, 704, 736, 768, 800]
AUG_MAX_SIZE: 1333
AUG_RANDOM_RESIZE: [400, 500, 600]
AUG_RANDOM_CROP_MIN: 384
AUG_RANDOM_CROP_MAX: 600
AUG_OVERFLOW_BBOX: False
AUG_REVERSE_CLIP: 0.0
AUG_RANDOM_SHIFT_MAX_RATIO: 0.06 # Only for static images
# Model settings:
NUM_ID_VOCABULARY: 50
NUM_CLASSES: 1
MAX_TEMPORAL_LENGTH: 40
ID_LOSS_WEIGHT: 1
ID_LOSS_GPU_AVERAGE: True
ID_DECODER_LAYERS: 6
SEQ_HIDDEN_DIM: 256
SEQ_DIM_FEEDFORWARD: 512
SEQ_NUM_HEADS: 8
# Backbone:
BACKBONE: resnet50
DILATION: False
# About DETR-Framework
DETR_NUM_QUERIES: 300
DETR_NUM_FEATURE_LEVELS: 4
DETR_AUX_LOSS: True
DETR_WITH_BOX_REFINE: True
DETR_TWO_STAGE: False
DETR_MASKS: False
DETR_HIDDEN_DIM: 256
DETR_PE: sine
DETR_ENC_LAYERS: 6
DETR_DEC_LAYERS: 6
DETR_NUM_HEADS: 8
DETR_DIM_FEEDFORWARD: 1024
DETR_DROPOUT: 0.0
DETR_DEC_N_POINTS: 4
DETR_ENC_N_POINTS: 4
DETR_CLS_LOSS_COEF: 2.0
DETR_BBOX_LOSS_COEF: 5.0
DETR_GIOU_LOSS_COEF: 2.0
DETR_FOCAL_ALPHA: 0.25
DETR_PRETRAIN: ./pretrains/r50_deformable_detr_coco_dancetrack.pth
DETR_FRAMEWORK: Deformable-DETR
# Training Setting:
TRAIN_STAGE: joint
SEED: 42
USE_DISTRIBUTED: False
DETR_NUM_TRAIN_FRAMES: 4
# Below two parameters are for memory optimized DETR training:
DETR_CHECKPOINT_FRAMES: 5
SEQ_DECODER_CHECKPOINT: False
# Training Augmentation:
TRAJ_DROP_RATIO: 0.5
TRAJ_SWITCH_RATIO: 0.3
# Training Scheduler:
EPOCHS: 14
LR: 1.0e-4
LR_BACKBONE_NAMES: [backbone.0]
LR_BACKBONE_SCALE: 0.1
LR_LINEAR_PROJ_NAMES: [reference_points, sampling_offsets]
LR_LINEAR_PROJ_SCALE: 0.05
LR_WARMUP_EPOCHS: 1
WEIGHT_DECAY: 0.0005
CLIP_MAX_NORM: 0.1
SCHEDULER_TYPE: MultiStep
SCHEDULER_MILESTONES: [8, 12]
SCHEDULER_GAMMA: 0.1
BATCH_SIZE: 1
ACCUMULATE_STEPS: 2
RESUME_MODEL:
RESUME_OPTIMIZER: True
RESUME_SCHEDULER: True
RESUME_STATES: True
# Inference:
INFERENCE_MODEL:
INFERENCE_ONLY_DETR: False
INFERENCE_DATASET: DanceTrack
INFERENCE_SPLIT: val
INFERENCE_CONFIG_PATH: # mostly, you don't need to set this parameter. See submit_engine.py L34 for more details.
INFERENCE_GROUP:
INFERENCE_MAX_SIZE: 1333
INFERENCE_ENSEMBLE: 0
# Thresholds:
ID_THRESH: 0.2
DET_THRESH: 0.3
NEWBORN_THRESH: 0.6
AREA_THRESH: 100
# Outputs:
OUTPUTS_DIR:
OUTPUTS_PER_STEP: 100
SAVE_CHECKPOINT_PER_EPOCH: 1
USE_TENSORBOARD: True
USE_WANDB: True
PROJECT_NAME: MOTIP
EXP_NAME: r50_deformable_detr_motip_dancetrack
EXP_GROUP: default
EXP_OWNER:
# Settings which are used to reduce the memory usage of DETR criterion.
# Too many objects (such as CrowdHuman) may cause OOM error.
MEMORY_OPTIMIZED_DETR_CRITERION: False
AUTO_MEMORY_OPTIMIZED_DETR_CRITERION: False
CHECKPOINT_DETR_CRITERION: False