Why your test scale is larger than 600?

[Yorionice1]

Thanks for your working. I found the test scale is 800, which is larger than it in other papers in this field.

[yujheli]

Yes, we do not revise the default test scale. I think the performance can be improved if the test scale is fixed.

[Yorionice1]

Thanks for your reply. But I still can't get the accuracy reported in your paper (50.9), my result is around 45.2 on 4 GPUs with IMG_PER_BATCH_LABEL: 8, IMG_PER_BATCH_UNLABEL: 8, BASE_LR: 0.04. Rest of the settings are same as original config file uploaded by you.

[Yorionice1]

MODEL:

META_ARCHITECTURE: "DAobjTwoStagePseudoLabGeneralizedRCNN" BACKBONE: NAME: "build_vgg_backbone" MASK_ON: False RESNETS: DEPTH: 101 PROPOSAL_GENERATOR: NAME: "PseudoLabRPN"

RPN: IN_FEATURES: ["vgg4"] ROI_HEADS: NAME: "StandardROIHeadsPseudoLab" LOSS: "CrossEntropy" # variant: "CrossEntropy" NUM_CLASSES: 8 IN_FEATURES: ["vgg4"] ROI_BOX_HEAD: NAME: "FastRCNNConvFCHead" NUM_FC: 2 POOLER_RESOLUTION: 7 SOLVER: LR_SCHEDULER_NAME: "WarmupTwoStageMultiStepLR" STEPS: (60000, 80000, 90000, 360000) FACTOR_LIST: (1, 1, 1, 1, 1) MAX_ITER: 100000 IMG_PER_BATCH_LABEL: 8 IMG_PER_BATCH_UNLABEL: 8 BASE_LR: 0.04 DATALOADER: SUP_PERCENT: 100.0 DATASETS: CROSS_DATASET: True TRAIN_LABEL: ("cityscapes_train",) TRAIN_UNLABEL: ("cityscapes_foggy_train",) TEST: ("cityscapes_foggy_val",) SEMISUPNET: Trainer: "ateacher" BBOX_THRESHOLD: 0.8 TEACHER_UPDATE_ITER: 1 BURN_UP_STEP: 20000 EMA_KEEP_RATE: 0.9996 UNSUP_LOSS_WEIGHT: 1.0 SUP_LOSS_WEIGHT: 0.5 DIS_TYPE: "vgg4" #["concate","p2","multi"] TEST: EVAL_PERIOD: 1000

[09/30 02:19:46] detectron2 INFO: Running with full config: CUDNN_BENCHMARK: false DATALOADER: ASPECT_RATIO_GROUPING: true FILTER_EMPTY_ANNOTATIONS: true NUM_WORKERS: 4 RANDOM_DATA_SEED: 0 RANDOM_DATA_SEED_PATH: dataseed/COCO_supervision.txt REPEAT_THRESHOLD: 0.0 SAMPLER_TRAIN: TrainingSampler SUP_PERCENT: 100.0 DATASETS: CROSS_DATASET: true PRECOMPUTED_PROPOSAL_TOPK_TEST: 1000 PRECOMPUTED_PROPOSAL_TOPK_TRAIN: 2000 PROPOSAL_FILES_TEST: [] PROPOSAL_FILES_TRAIN: [] TEST:

• cityscapes_foggy_val TRAIN:
• coco_2017_train TRAIN_LABEL:
• cityscapes_train TRAIN_UNLABEL:
• cityscapes_foggy_train EMAMODEL: SUP_CONSIST: true GLOBAL: HACK: 1.0 INPUT: CROP: ENABLED: false SIZE:
  • 0.9
  • 0.9 TYPE: relative_range FORMAT: BGR MASK_FORMAT: polygon MAX_SIZE_TEST: 1333 MAX_SIZE_TRAIN: 1333 MIN_SIZE_TEST: 800 MIN_SIZE_TRAIN:
• 600 MIN_SIZE_TRAIN_SAMPLING: choice RANDOM_FLIP: horizontal MODEL: ANCHOR_GENERATOR: ANGLES:
  • • -90
    • 0
    • 90 ASPECT_RATIOS:
  • • 0.5
    • 1.0
    • 2.0 NAME: DefaultAnchorGenerator OFFSET: 0.0 SIZES:
  • • 32
    • 64
    • 128
    • 256
    • 512 BACKBONE: FREEZE_AT: 2 NAME: build_vgg_backbone DEVICE: cuda FPN: FUSE_TYPE: sum IN_FEATURES: [] NORM: '' OUT_CHANNELS: 256 KEYPOINT_ON: false LOAD_PROPOSALS: false MASK_ON: false META_ARCHITECTURE: DAobjTwoStagePseudoLabGeneralizedRCNN PANOPTIC_FPN: COMBINE: ENABLED: true INSTANCES_CONFIDENCE_THRESH: 0.5 OVERLAP_THRESH: 0.5 STUFF_AREA_LIMIT: 4096 INSTANCE_LOSS_WEIGHT: 1.0 PIXEL_MEAN:
• 103.53
• 116.28
• 123.675 PIXEL_STD:
• 1.0
• 1.0
• 1.0 PROPOSAL_GENERATOR: MIN_SIZE: 0 NAME: PseudoLabRPN RESNETS: DEFORM_MODULATED: false DEFORM_NUM_GROUPS: 1 DEFORM_ON_PER_STAGE:
  • false
  • false
  • false
  • false DEPTH: 101 NORM: FrozenBN NUM_GROUPS: 1 OUT_FEATURES:
  • res4 RES2_OUT_CHANNELS: 256 RES5_DILATION: 1 STEM_OUT_CHANNELS: 64 STRIDE_IN_1X1: true WIDTH_PER_GROUP: 64 RETINANET: BBOX_REG_LOSS_TYPE: smooth_l1 BBOX_REG_WEIGHTS:
  • 1.0
  • 1.0
  • 1.0
  • 1.0 FOCAL_LOSS_ALPHA: 0.25 FOCAL_LOSS_GAMMA: 2.0 IN_FEATURES:
  • p3
  • p4
  • p5
  • p6
  • p7 IOU_LABELS:
  • 0
  • -1
  • 1 IOU_THRESHOLDS:
  • 0.4
  • 0.5 NMS_THRESH_TEST: 0.5 NORM: '' NUM_CLASSES: 80 NUM_CONVS: 4 PRIOR_PROB: 0.01 SCORE_THRESH_TEST: 0.05 SMOOTH_L1_LOSS_BETA: 0.1 TOPK_CANDIDATES_TEST: 1000 ROI_BOX_CASCADE_HEAD: BBOX_REG_WEIGHTS:
  • • 10.0
    • 10.0
    • 5.0
    • 5.0
  • • 20.0
    • 20.0
    • 10.0
    • 10.0
  • • 30.0
    • 30.0
    • 15.0
    • 15.0 IOUS:
  • 0.5
  • 0.6
  • 0.7 ROI_BOX_HEAD: BBOX_REG_LOSS_TYPE: smooth_l1 BBOX_REG_LOSS_WEIGHT: 1.0 BBOX_REG_WEIGHTS:
  • 10.0
  • 10.0
  • 5.0
  • 5.0 CLS_AGNOSTIC_BBOX_REG: false CONV_DIM: 256 FC_DIM: 1024 NAME: FastRCNNConvFCHead NORM: '' NUM_CONV: 0 NUM_FC: 2 POOLER_RESOLUTION: 7 POOLER_SAMPLING_RATIO: 0 POOLER_TYPE: ROIAlignV2 SMOOTH_L1_BETA: 0.0 TRAIN_ON_PRED_BOXES: false ROI_HEADS: BATCH_SIZE_PER_IMAGE: 512 IN_FEATURES:
  • vgg4 IOU_LABELS:
  • 0
  • 1 IOU_THRESHOLDS:
  • 0.5 LOSS: CrossEntropy NAME: StandardROIHeadsPseudoLab NMS_THRESH_TEST: 0.5 NUM_CLASSES: 8 POSITIVE_FRACTION: 0.25 PROPOSAL_APPEND_GT: true SCORE_THRESH_TEST: 0.05 ROI_KEYPOINT_HEAD: CONV_DIMS:
  • 512
  • 512
  • 512
  • 512
  • 512
  • 512
  • 512
  • 512 LOSS_WEIGHT: 1.0 MIN_KEYPOINTS_PER_IMAGE: 1 NAME: KRCNNConvDeconvUpsampleHead NORMALIZE_LOSS_BY_VISIBLE_KEYPOINTS: true NUM_KEYPOINTS: 17 POOLER_RESOLUTION: 14 POOLER_SAMPLING_RATIO: 0 POOLER_TYPE: ROIAlignV2 ROI_MASK_HEAD: CLS_AGNOSTIC_MASK: false CONV_DIM: 256 NAME: MaskRCNNConvUpsampleHead NORM: '' NUM_CONV: 0 POOLER_RESOLUTION: 14 POOLER_SAMPLING_RATIO: 0 POOLER_TYPE: ROIAlignV2 RPN: BATCH_SIZE_PER_IMAGE: 256 BBOX_REG_LOSS_TYPE: smooth_l1 BBOX_REG_LOSS_WEIGHT: 1.0 BBOX_REG_WEIGHTS:
  • 1.0
  • 1.0
  • 1.0
  • 1.0 BOUNDARY_THRESH: -1 CONV_DIMS:
  • -1 HEAD_NAME: StandardRPNHead IN_FEATURES:
  • vgg4 IOU_LABELS:
  • 0
  • -1
  • 1 IOU_THRESHOLDS:
  • 0.3
  • 0.7 LOSS: CrossEntropy LOSS_WEIGHT: 1.0 NMS_THRESH: 0.7 POSITIVE_FRACTION: 0.5 POST_NMS_TOPK_TEST: 1000 POST_NMS_TOPK_TRAIN: 2000 PRE_NMS_TOPK_TEST: 6000 PRE_NMS_TOPK_TRAIN: 12000 SMOOTH_L1_BETA: 0.0 UNSUP_LOSS_WEIGHT: 1.0 SEM_SEG_HEAD: COMMON_STRIDE: 4 CONVS_DIM: 128 IGNORE_VALUE: 255 IN_FEATURES:
  • p2
  • p3
  • p4
  • p5 LOSS_WEIGHT: 1.0 NAME: SemSegFPNHead NORM: GN NUM_CLASSES: 54 WEIGHTS: '' OUTPUT_DIR: output/exp_city SEED: -1 SEMISUPNET: BBOX_THRESHOLD: 0.8 BURN_UP_STEP: 20000 DIS_LOSS_WEIGHT: 0.1 DIS_TYPE: vgg4 EMA_KEEP_RATE: 0.9996 LOSS_WEIGHT_TYPE: standard MLP_DIM: 128 PSEUDO_BBOX_SAMPLE: thresholding SUP_LOSS_WEIGHT: 0.5 TEACHER_UPDATE_ITER: 1 Trainer: ateacher UNSUP_LOSS_WEIGHT: 1.0 SOLVER: AMP: ENABLED: false BASE_LR: 0.04 BIAS_LR_FACTOR: 1.0 CHECKPOINT_PERIOD: 5000 CLIP_GRADIENTS: CLIP_TYPE: value CLIP_VALUE: 1.0 ENABLED: false NORM_TYPE: 2.0 FACTOR_LIST:
• 1
• 1
• 1
• 1
• 1 GAMMA: 0.1 IMG_PER_BATCH_LABEL: 8 IMG_PER_BATCH_UNLABEL: 8 IMS_PER_BATCH: 16 LR_SCHEDULER_NAME: WarmupTwoStageMultiStepLR MAX_ITER: 100000 MOMENTUM: 0.9 NESTEROV: false REFERENCE_WORLD_SIZE: 0 STEPS:
• 60000
• 80000
• 90000
• 360000 WARMUP_FACTOR: 0.001 WARMUP_ITERS: 1000 WARMUP_METHOD: linear WEIGHT_DECAY: 0.0001 WEIGHT_DECAY_BIAS: 0.0001 WEIGHT_DECAY_NORM: 0.0 TEST: AUG: ENABLED: false FLIP: true MAX_SIZE: 4000 MIN_SIZES:
  • 400
  • 500
  • 600
  • 700
  • 800
  • 900
  • 1000
  • 1100
  • 1200 DETECTIONS_PER_IMAGE: 100 EVALUATOR: COCOeval EVAL_PERIOD: 1000 EXPECTED_RESULTS: [] KEYPOINT_OKS_SIGMAS: [] PRECISE_BN: ENABLED: false NUM_ITER: 200 VAL_LOSS: true VERSION: 2 VIS_PERIOD: 0