"CUDNN_BENCHMARK: false\nDATALOADER:\n ASPECT_RATIO_GROUPING: true\n FILTER_EMPTY_ANNOTATIONS:\ \ true\n NUM_WORKERS: 4\n REPEAT_SQRT: true\n REPEAT_THRESHOLD: 0.0\n SAMPLER_TRAIN:\ \ TrainingSampler\nDATASETS:\n PRECOMPUTED_PROPOSAL_TOPK_TEST: 1000\n PRECOMPUTED_PROPOSAL_TOPK_TRAIN:\ \ 2000\n PROPOSAL_FILES_TEST: []\n PROPOSAL_FILES_TRAIN: []\n TEST:\n - coco_2017_val\n\ \ TRAIN:\n - coco_2017_train\nFLOAT32_PRECISION: ''\nGLOBAL:\n HACK: 1.0\nINPUT:\n\ \ CROP:\n ENABLED: false\n SIZE:\n - 0.9\n - 0.9\n TYPE: relative_range\n\ \ FORMAT: BGR\n MASK_FORMAT: polygon\n MAX_SIZE_TEST: 1333\n MAX_SIZE_TRAIN:\ \ 1333\n MIN_SIZE_TEST: 800\n MIN_SIZE_TRAIN:\n - 640\n - 672\n - 704\n -\ \ 736\n - 768\n - 800\n MIN_SIZE_TRAIN_SAMPLING: choice\n RANDOM_FLIP: horizontal\n\ MODEL:\n ANCHOR_GENERATOR:\n ANGLES:\n - - -90\n - 0\n - 90\n \ \ ASPECT_RATIOS:\n - - 0.5\n - 1.0\n - 2.0\n NAME: DefaultAnchorGenerator\n\ \ OFFSET: 0.0\n SIZES:\n - - 32\n - - 64\n - - 128\n - - 256\n\ \ - - 512\n BACKBONE:\n FREEZE_AT: 2\n NAME: build_resnet_fpn_backbone\n\ \ DEVICE: cuda\n FPN:\n FUSE_TYPE: sum\n IN_FEATURES:\n - res2\n -\ \ res3\n - res4\n - res5\n NORM: ''\n OUT_CHANNELS: 256\n KEYPOINT_ON:\ \ false\n LOAD_PROPOSALS: false\n MASK_ON: false\n META_ARCHITECTURE: GeneralizedRCNN\n\ \ PANOPTIC_FPN:\n COMBINE:\n ENABLED: true\n INSTANCES_CONFIDENCE_THRESH:\ \ 0.5\n OVERLAP_THRESH: 0.5\n STUFF_AREA_LIMIT: 4096\n INSTANCE_LOSS_WEIGHT:\ \ 1.0\n PIXEL_MEAN:\n - 103.53\n - 116.28\n - 123.675\n PIXEL_STD:\n - 1.0\n\ \ - 1.0\n - 1.0\n PROPOSAL_GENERATOR:\n MIN_SIZE: 0\n NAME: RPN\n RESNETS:\n\ \ DEFORM_MODULATED: false\n DEFORM_NUM_GROUPS: 1\n DEFORM_ON_PER_STAGE:\n\ \ - false\n - false\n - false\n - false\n DEPTH: 50\n NORM: FrozenBN\n\ \ NUM_GROUPS: 1\n OUT_FEATURES:\n - res2\n - res3\n - res4\n -\ \ res5\n RES2_OUT_CHANNELS: 256\n RES5_DILATION: 1\n STEM_OUT_CHANNELS:\ \ 64\n STRIDE_IN_1X1: true\n WIDTH_PER_GROUP: 64\n RETINANET:\n BBOX_REG_LOSS_TYPE:\ \ smooth_l1\n BBOX_REG_WEIGHTS: &id002\n - 1.0\n - 1.0\n - 1.0\n \ \ - 1.0\n FOCAL_LOSS_ALPHA: 0.25\n FOCAL_LOSS_GAMMA: 2.0\n IN_FEATURES:\n\ \ - p3\n - p4\n - p5\n - p6\n - p7\n IOU_LABELS:\n - 0\n \ \ - -1\n - 1\n IOU_THRESHOLDS:\n - 0.4\n - 0.5\n NMS_THRESH_TEST:\ \ 0.5\n NORM: ''\n NUM_CLASSES: 80\n NUM_CONVS: 4\n PRIOR_PROB: 0.01\n\ \ SCORE_THRESH_TEST: 0.05\n SMOOTH_L1_LOSS_BETA: 0.1\n TOPK_CANDIDATES_TEST:\ \ 1000\n ROI_BOX_CASCADE_HEAD:\n BBOX_REG_WEIGHTS:\n - &id001\n - 10.0\n\ \ - 10.0\n - 5.0\n - 5.0\n - - 20.0\n - 20.0\n - 10.0\n\ \ - 10.0\n - - 30.0\n - 30.0\n - 15.0\n - 15.0\n IOUS:\n\ \ - 0.5\n - 0.6\n - 0.7\n ROI_BOX_HEAD:\n BBOX_REG_LOSS_TYPE: smooth_l1\n\ \ BBOX_REG_LOSS_WEIGHT: 1.0\n BBOX_REG_WEIGHTS: *id001\n CLS_AGNOSTIC_BBOX_REG:\ \ false\n CONV_DIM: 256\n FC_DIM: 1024\n FED_LOSS_FREQ_WEIGHT_POWER: 0.5\n\ \ FED_LOSS_NUM_CLASSES: 50\n NAME: FastRCNNConvFCHead\n NORM: ''\n NUM_CONV:\ \ 0\n NUM_FC: 2\n POOLER_RESOLUTION: 7\n POOLER_SAMPLING_RATIO: 0\n \ \ POOLER_TYPE: ROIAlignV2\n SMOOTH_L1_BETA: 0.0\n TRAIN_ON_PRED_BOXES: false\n\ \ USE_FED_LOSS: false\n USE_SIGMOID_CE: false\n ROI_HEADS:\n BATCH_SIZE_PER_IMAGE:\ \ 512\n IN_FEATURES:\n - p2\n - p3\n - p4\n - p5\n IOU_LABELS:\n\ \ - 0\n - 1\n IOU_THRESHOLDS:\n - 0.5\n NAME: StandardROIHeads\n\ \ NMS_THRESH_TEST: 0.5\n NUM_CLASSES: 3\n POSITIVE_FRACTION: 0.25\n \ \ PROPOSAL_APPEND_GT: true\n SCORE_THRESH_TEST: 0.7\n ROI_KEYPOINT_HEAD:\n \ \ CONV_DIMS:\n - 512\n - 512\n - 512\n - 512\n - 512\n - 512\n\ \ - 512\n - 512\n LOSS_WEIGHT: 1.0\n MIN_KEYPOINTS_PER_IMAGE: 1\n \ \ NAME: KRCNNConvDeconvUpsampleHead\n NORMALIZE_LOSS_BY_VISIBLE_KEYPOINTS: true\n\ \ NUM_KEYPOINTS: 17\n POOLER_RESOLUTION: 14\n POOLER_SAMPLING_RATIO: 0\n\ \ POOLER_TYPE: ROIAlignV2\n ROI_MASK_HEAD:\n CLS_AGNOSTIC_MASK: false\n \ \ CONV_DIM: 256\n NAME: MaskRCNNConvUpsampleHead\n NORM: ''\n NUM_CONV:\ \ 4\n POOLER_RESOLUTION: 14\n POOLER_SAMPLING_RATIO: 0\n POOLER_TYPE: ROIAlignV2\n\ \ RPN:\n BATCH_SIZE_PER_IMAGE: 256\n BBOX_REG_LOSS_TYPE: smooth_l1\n BBOX_REG_LOSS_WEIGHT:\ \ 1.0\n BBOX_REG_WEIGHTS: *id002\n BOUNDARY_THRESH: -1\n CONV_DIMS:\n \ \ - -1\n HEAD_NAME: StandardRPNHead\n IN_FEATURES:\n - p2\n - p3\n\ \ - p4\n - p5\n - p6\n IOU_LABELS:\n - 0\n - -1\n - 1\n \ \ IOU_THRESHOLDS:\n - 0.3\n - 0.7\n LOSS_WEIGHT: 1.0\n NMS_THRESH: 0.7\n\ \ POSITIVE_FRACTION: 0.5\n POST_NMS_TOPK_TEST: 1000\n POST_NMS_TOPK_TRAIN:\ \ 1000\n PRE_NMS_TOPK_TEST: 1000\n PRE_NMS_TOPK_TRAIN: 2000\n SMOOTH_L1_BETA:\ \ 0.0\n SEM_SEG_HEAD:\n COMMON_STRIDE: 4\n CONVS_DIM: 128\n IGNORE_VALUE:\ \ 255\n IN_FEATURES:\n - p2\n - p3\n - p4\n - p5\n LOSS_WEIGHT:\ \ 1.0\n NAME: SemSegFPNHead\n NORM: GN\n NUM_CLASSES: 54\n WEIGHTS: /kaggle/working/output/model_final.pth\n\ OUTPUT_DIR: ./output\nSEED: -1\nSOLVER:\n AMP:\n ENABLED: false\n BASE_LR:\ \ 0.02\n BASE_LR_END: 0.0\n BIAS_LR_FACTOR: 1.0\n CHECKPOINT_PERIOD: 5000\n \ \ CLIP_GRADIENTS:\n CLIP_TYPE: value\n CLIP_VALUE: 1.0\n ENABLED: false\n\ \ NORM_TYPE: 2.0\n GAMMA: 0.1\n IMS_PER_BATCH: 16\n LR_SCHEDULER_NAME: WarmupMultiStepLR\n\ \ MAX_ITER: 270000\n MOMENTUM: 0.9\n NESTEROV: false\n NUM_DECAYS: 3\n REFERENCE_WORLD_SIZE:\ \ 0\n RESCALE_INTERVAL: false\n STEPS:\n - 210000\n - 250000\n WARMUP_FACTOR:\ \ 0.001\n WARMUP_ITERS: 1000\n WARMUP_METHOD: linear\n WEIGHT_DECAY: 0.0001\n\ \ WEIGHT_DECAY_BIAS: null\n WEIGHT_DECAY_NORM: 0.0\nTEST:\n AUG:\n ENABLED:\ \ false\n FLIP: true\n MAX_SIZE: 4000\n MIN_SIZES:\n - 400\n - 500\n\ \ - 600\n - 700\n - 800\n - 900\n - 1000\n - 1100\n - 1200\n\ \ DETECTIONS_PER_IMAGE: 100\n EVAL_PERIOD: 0\n EXPECTED_RESULTS: []\n KEYPOINT_OKS_SIGMAS:\ \ []\n PRECISE_BN:\n ENABLED: false\n NUM_ITER: 200\nVERSION: 2\nVIS_PERIOD:\ \ 0\n"