search

tianzhi0549 / FCOS

FCOS: Fully Convolutional One-Stage Object Detection (ICCV'19)
https://arxiv.org/abs/1904.01355
Other
3.27k stars 629 forks source link

Use the data of the last 40 categories of the COCO dataset to train the model of 80 categories #294

Open chenaifang opened 4 years ago

chenaifang commented 4 years ago

@tianzhi0549 Hello, I'm doing something about incremental learning At present, I have removed the labels of the first 40 categories of the COCO dataset and only used the data of the last 40 categories to train the whole model But my training result is that the first 40 categories are accurate, and the last 40 categories are all 0, Is there something in the code that changes the category of the box to start at 1?

The result is:

Maximum f-measures for classes:
[0.0, 0.0, 0.0, 0.0005740105676817332, 0.004240057384235276, 0.003351580828957659, 0.0058365758754863805, 0.0, 0.0016975046681378374, 0.0, 0.0, 0.0005377789728421619, 0.0, 0.0, 0.0077833991215878135, 0.016303900310158374, 0.005934718100890208, 0.020163533419189646, 0.003124147677964841, 0.023236277190912827, 0.0049321090424977445, 0.014010968536695497, 0.0025194205332773464, 0.0, 0.0, 0.0, 0.0, 0.005831257972423009, 0.007957559681697613, 0.0, 0.0, 0.0018049145244050226, 0.0, 0.0020767473521471256, 0.0005956813104988831, 0.0, 0.05400540054005401, 0.001370301009455077, 0.0, 0.009353741496598641, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]
Score thresholds for classes (used in demos for visualization purposes):
[0.739753007888794, 0.7549595236778259, 0.6479933261871338, 0.22768962383270264, 0.19447387754917145, 0.287908673286438, 0.3628227114677429, 0.4966130554676056, 0.22188042104244232, 0.6412631273269653, 0.4416590631008148, 0.3477969169616699, 0.4622531831264496, 0.6484530568122864, 0.2043519765138626, 0.26480832695961, 0.5569340586662292, 0.21177774667739868, 0.19535374641418457, 0.18984755873680115, 0.17053937911987305, 0.16538876295089722, 0.18358872830867767, 0.8271213173866272, 0.7856563925743103, 0.5274842381477356, 0.6363959312438965, 0.28237074613571167, 0.2814313471317291, 0.7677108645439148, 0.0, 0.20111560821533203, 0.604306161403656, 0.18206530809402466, 0.2856121063232422, 0.6664050817489624, 0.3740610182285309, 0.21397672593593597, 0.2665221691131592, 0.29126012325286865, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]
2020-08-07 10:36:44,874 fcos_core_s80.inference INFO: OrderedDict([('bbox', OrderedDict([('AP', 0.00023310340961515017), ('AP50', 0.00039320463674013715), ('AP75', 0.0002367099235623245), ('APs', 0.0003922088417932285), ('APm', 0.0003971098755152556), ('APl', 0.00028796008626458567)]))])
chenaifang commented 4 years ago

@tianzhi0549 I've already solved the above problem. but i have a new question

I'm just training with the last 40 categories 80 total categories, the knowledge of the first 40 categories can't be forgotten that fast, so what's causing the map value of the first 40 categories to be 0?

`2020-08-07 18:22:19,012 fcos_core_s80 INFO: Using 1 GPUs 2020-08-07 18:22:19,012 fcos_core_s80 INFO: DATALOADER: ASPECT_RATIO_GROUPING: True NUM_WORKERS: 4 SIZE_DIVISIBILITY: 32 DATASETS: TEST: ('coco_2017_val',) TRAIN: ('coco_2017_train',) INPUT: MAX_SIZE_TEST: 1333 MAX_SIZE_TRAIN: 1333 MIN_SIZE_RANGE_TRAIN: (-1, -1) MIN_SIZE_TEST: 800 MIN_SIZE_TRAIN: (800,) PIXEL_MEAN: [102.9801, 115.9465, 122.7717] PIXEL_STD: [1.0, 1.0, 1.0] TO_BGR255: True MODEL: BACKBONE: CONV_BODY: R-50-FPN-RETINANET FREEZE_CONV_BODY_AT: 2 USE_GN: False CLS_AGNOSTIC_BBOX_REG: False DEVICE: cuda FBNET: ARCH: default ARCH_DEF: BN_TYPE: bn DET_HEAD_BLOCKS: [] DET_HEAD_LAST_SCALE: 1.0 DET_HEAD_STRIDE: 0 DW_CONV_SKIP_BN: True DW_CONV_SKIP_RELU: True KPTS_HEAD_BLOCKS: [] KPTS_HEAD_LAST_SCALE: 0.0 KPTS_HEAD_STRIDE: 0 MASK_HEAD_BLOCKS: [] MASK_HEAD_LAST_SCALE: 0.0 MASK_HEAD_STRIDE: 0 RPN_BN_TYPE: RPN_HEAD_BLOCKS: 0 SCALE_FACTOR: 1.0 WIDTH_DIVISOR: 1 FCOS: CENTERNESS_ON_REG: True CENTER_SAMPLING_RADIUS: 1.5 FPN_STRIDES: [8, 16, 32, 64, 128] INFERENCE_TH: 0.05 IOU_LOSS_TYPE: giou LOSS_ALPHA: 0.25 LOSS_GAMMA: 2.0 NMS_TH: 0.6 NORM_REG_TARGETS: True NUM_CLASSES: 81 NUM_CONVS: 4 PRE_NMS_TOP_N: 1000 PRIOR_PROB: 0.01 USE_DCN_IN_TOWER: False FCOS_ON: True FPN: USE_GN: False USE_RELU: False GROUP_NORM: DIM_PER_GP: -1 EPSILON: 1e-05 NUM_GROUPS: 32 KEYPOINT_ON: False MASK_ON: False META_ARCHITECTURE: GeneralizedRCNN RESNETS: BACKBONE_OUT_CHANNELS: 256 DEFORMABLE_GROUPS: 1 NUM_GROUPS: 1 RES2_OUT_CHANNELS: 256 RES5_DILATION: 1 STAGE_WITH_DCN: (False, False, False, False) STEM_FUNC: StemWithFixedBatchNorm STEM_OUT_CHANNELS: 64 STRIDE_IN_1X1: True TRANS_FUNC: BottleneckWithFixedBatchNorm WIDTH_PER_GROUP: 64 WITH_MODULATED_DCN: False RETINANET: ANCHOR_SIZES: (32, 64, 128, 256, 512) ANCHOR_STRIDES: (8, 16, 32, 64, 128) ASPECT_RATIOS: (0.5, 1.0, 2.0) BBOX_REG_BETA: 0.11 BBOX_REG_WEIGHT: 4.0 BG_IOU_THRESHOLD: 0.4 FG_IOU_THRESHOLD: 0.5 INFERENCE_TH: 0.05 LOSS_ALPHA: 0.25 LOSS_GAMMA: 2.0 NMS_TH: 0.4 NUM_CLASSES: 81 NUM_CONVS: 4 OCTAVE: 2.0 PRE_NMS_TOP_N: 1000 PRIOR_PROB: 0.01 SCALES_PER_OCTAVE: 3 STRADDLE_THRESH: 0 USE_C5: False RETINANET_ON: False ROI_BOX_HEAD: CONV_HEAD_DIM: 256 DILATION: 1 FEATURE_EXTRACTOR: ResNet50Conv5ROIFeatureExtractor MLP_HEAD_DIM: 1024 NUM_CLASSES: 81 NUM_STACKED_CONVS: 4 POOLER_RESOLUTION: 14 POOLER_SAMPLING_RATIO: 0 POOLER_SCALES: (0.0625,) PREDICTOR: FastRCNNPredictor USE_GN: False ROI_HEADS: BATCH_SIZE_PER_IMAGE: 512 BBOX_REG_WEIGHTS: (10.0, 10.0, 5.0, 5.0) BG_IOU_THRESHOLD: 0.5 DETECTIONS_PER_IMG: 100 FG_IOU_THRESHOLD: 0.5 NMS: 0.5 POSITIVE_FRACTION: 0.25 SCORE_THRESH: 0.05 USE_FPN: False ROI_KEYPOINT_HEAD: CONV_LAYERS: (512, 512, 512, 512, 512, 512, 512, 512) FEATURE_EXTRACTOR: KeypointRCNNFeatureExtractor MLP_HEAD_DIM: 1024 NUM_CLASSES: 81 POOLER_RESOLUTION: 14 POOLER_SAMPLING_RATIO: 0 POOLER_SCALES: (0.0625,) PREDICTOR: KeypointRCNNPredictor RESOLUTION: 14 SHARE_BOX_FEATURE_EXTRACTOR: True ROI_MASK_HEAD: CONV_LAYERS: (256, 256, 256, 256) DILATION: 1 FEATURE_EXTRACTOR: ResNet50Conv5ROIFeatureExtractor MLP_HEAD_DIM: 1024 POOLER_RESOLUTION: 14 POOLER_SAMPLING_RATIO: 0 POOLER_SCALES: (0.0625,) POSTPROCESS_MASKS: False POSTPROCESS_MASKS_THRESHOLD: 0.5 PREDICTOR: MaskRCNNC4Predictor RESOLUTION: 14 SHARE_BOX_FEATURE_EXTRACTOR: True USE_GN: False RPN: ANCHOR_SIZES: (32, 64, 128, 256, 512) ANCHOR_STRIDE: (16,) ASPECT_RATIOS: (0.5, 1.0, 2.0) BATCH_SIZE_PER_IMAGE: 256 BG_IOU_THRESHOLD: 0.3 FG_IOU_THRESHOLD: 0.7 FPN_POST_NMS_TOP_N_TEST: 2000 FPN_POST_NMS_TOP_N_TRAIN: 2000 MIN_SIZE: 0 NMS_THRESH: 0.7 POSITIVE_FRACTION: 0.5 POST_NMS_TOP_N_TEST: 1000 POST_NMS_TOP_N_TRAIN: 2000 PRE_NMS_TOP_N_TEST: 6000 PRE_NMS_TOP_N_TRAIN: 12000 RPN_HEAD: SingleConvRPNHead STRADDLE_THRESH: 0 USE_FPN: False RPN_ONLY: True USE_SYNCBN: False WEIGHT: /mnt/FCOS/training_dir/fcos_imprv_R_50_FPN_s80/model_0020000.pth OUTPUT_DIR: /mnt/FCOS/training_dir/FCOS_imprv20000 PATHS_CATALOG: /mnt/FCOS/fcos_core_s80/config/paths_catalog.py SOLVER: BASE_LR: 0.01 BIAS_LR_FACTOR: 2 CHECKPOINT_PERIOD: 2500 DCONV_OFFSETS_LR_FACTOR: 1.0 GAMMA: 0.1 IMS_PER_BATCH: 4 MAX_ITER: 150000 MOMENTUM: 0.9 STEPS: (60000, 80000) WARMUP_FACTOR: 0.3333333333333333 WARMUP_ITERS: 500 WARMUP_METHOD: constant WEIGHT_DECAY: 0.0001 WEIGHT_DECAY_BIAS: 0 TEST: BBOX_AUG: ENABLED: False H_FLIP: False MAX_SIZE: 4000 SCALES: () SCALE_H_FLIP: False DETECTIONS_PER_IMG: 100 EXPECTED_RESULTS: [] EXPECTED_RESULTS_SIGMA_TOL: 4 IMS_PER_BATCH: 8 2020-08-07 18:22:19,013 fcos_core_s80 INFO: Collecting env info (might take some time) 2020-08-07 18:22:22,518 fcos_core_s80 INFO: PyTorch version: 1.3.1 Is debug build: No CUDA used to build PyTorch: 10.1.243

OS: Ubuntu 18.04.3 LTS GCC version: (Ubuntu 7.5.0-3ubuntu1~18.04) 7.5.0 CMake version: version 3.10.2

Python version: 3.7 Is CUDA available: Yes CUDA runtime version: 10.0.130 GPU models and configuration: GPU 0: GeForce RTX 2080 Ti GPU 1: GeForce RTX 2080 Ti

Nvidia driver version: 440.64 cuDNN version: /usr/lib/x86_64-linux-gnu/libcudnn.so.7.6.5

Versions of relevant libraries: [pip] numpy==1.18.1 [pip] torch==1.3.1 [pip] torchvision==0.4.2 [conda] Could not collect Pillow (6.1.0) 2020-08-07 18:22:30,471 fcos_core_s80.utils.checkpoint INFO: Loading checkpoint from /mnt/FCOS/training_dir/fcos_imprv_R_50_FPN_s80/model_0020000.pth 2020-08-07 18:22:33,428 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer1.0.bn1.bias loaded from backbone.body.layer1.0.bn1.bias of shape (64,) 2020-08-07 18:22:33,428 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer1.0.bn1.running_mean loaded from backbone.body.layer1.0.bn1.running_mean of shape (64,) 2020-08-07 18:22:33,428 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer1.0.bn1.running_var loaded from backbone.body.layer1.0.bn1.running_var of shape (64,) 2020-08-07 18:22:33,428 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer1.0.bn1.weight loaded from backbone.body.layer1.0.bn1.weight of shape (64,) 2020-08-07 18:22:33,428 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer1.0.bn2.bias loaded from backbone.body.layer1.0.bn2.bias of shape (64,) 2020-08-07 18:22:33,428 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer1.0.bn2.running_mean loaded from backbone.body.layer1.0.bn2.running_mean of shape (64,) 2020-08-07 18:22:33,429 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer1.0.bn2.running_var loaded from backbone.body.layer1.0.bn2.running_var of shape (64,) 2020-08-07 18:22:33,429 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer1.0.bn2.weight loaded from backbone.body.layer1.0.bn2.weight of shape (64,) 2020-08-07 18:22:33,429 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer1.0.bn3.bias loaded from backbone.body.layer1.0.bn3.bias of shape (256,) 2020-08-07 18:22:33,429 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer1.0.bn3.running_mean loaded from backbone.body.layer1.0.bn3.running_mean of shape (256,) 2020-08-07 18:22:33,429 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer1.0.bn3.running_var loaded from backbone.body.layer1.0.bn3.running_var of shape (256,) 2020-08-07 18:22:33,429 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer1.0.bn3.weight loaded from backbone.body.layer1.0.bn3.weight of shape (256,) 2020-08-07 18:22:33,429 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer1.0.conv1.weight loaded from backbone.body.layer1.0.conv1.weight of shape (64, 64, 1, 1) 2020-08-07 18:22:33,429 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer1.0.conv2.weight loaded from backbone.body.layer1.0.conv2.weight of shape (64, 64, 3, 3) 2020-08-07 18:22:33,429 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer1.0.conv3.weight loaded from backbone.body.layer1.0.conv3.weight of shape (256, 64, 1, 1) 2020-08-07 18:22:33,430 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer1.0.downsample.0.weight loaded from backbone.body.layer1.0.downsample.0.weight of shape (256, 64, 1, 1) 2020-08-07 18:22:33,430 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer1.0.downsample.1.bias loaded from backbone.body.layer1.0.downsample.1.bias of shape (256,) 2020-08-07 18:22:33,430 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer1.0.downsample.1.running_mean loaded from backbone.body.layer1.0.downsample.1.running_mean of shape (256,) 2020-08-07 18:22:33,430 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer1.0.downsample.1.running_var loaded from backbone.body.layer1.0.downsample.1.running_var of shape (256,) 2020-08-07 18:22:33,430 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer1.0.downsample.1.weight loaded from backbone.body.layer1.0.downsample.1.weight of shape (256,) 2020-08-07 18:22:33,430 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer1.1.bn1.bias loaded from backbone.body.layer1.1.bn1.bias of shape (64,) 2020-08-07 18:22:33,430 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer1.1.bn1.running_mean loaded from backbone.body.layer1.1.bn1.running_mean of shape (64,) 2020-08-07 18:22:33,430 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer1.1.bn1.running_var loaded from backbone.body.layer1.1.bn1.running_var of shape (64,) 2020-08-07 18:22:33,430 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer1.1.bn1.weight loaded from backbone.body.layer1.1.bn1.weight of shape (64,) 2020-08-07 18:22:33,430 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer1.1.bn2.bias loaded from backbone.body.layer1.1.bn2.bias of shape (64,) 2020-08-07 18:22:33,431 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer1.1.bn2.running_mean loaded from backbone.body.layer1.1.bn2.running_mean of shape (64,) 2020-08-07 18:22:33,431 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer1.1.bn2.running_var loaded from backbone.body.layer1.1.bn2.running_var of shape (64,) 2020-08-07 18:22:33,431 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer1.1.bn2.weight loaded from backbone.body.layer1.1.bn2.weight of shape (64,) 2020-08-07 18:22:33,431 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer1.1.bn3.bias loaded from backbone.body.layer1.1.bn3.bias of shape (256,) 2020-08-07 18:22:33,431 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer1.1.bn3.running_mean loaded from backbone.body.layer1.1.bn3.running_mean of shape (256,) 2020-08-07 18:22:33,431 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer1.1.bn3.running_var loaded from backbone.body.layer1.1.bn3.running_var of shape (256,) 2020-08-07 18:22:33,431 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer1.1.bn3.weight loaded from backbone.body.layer1.1.bn3.weight of shape (256,) 2020-08-07 18:22:33,431 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer1.1.conv1.weight loaded from backbone.body.layer1.1.conv1.weight of shape (64, 256, 1, 1) 2020-08-07 18:22:33,431 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer1.1.conv2.weight loaded from backbone.body.layer1.1.conv2.weight of shape (64, 64, 3, 3) 2020-08-07 18:22:33,431 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer1.1.conv3.weight loaded from backbone.body.layer1.1.conv3.weight of shape (256, 64, 1, 1) 2020-08-07 18:22:33,432 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer1.2.bn1.bias loaded from backbone.body.layer1.2.bn1.bias of shape (64,) 2020-08-07 18:22:33,432 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer1.2.bn1.running_mean loaded from backbone.body.layer1.2.bn1.running_mean of shape (64,) 2020-08-07 18:22:33,432 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer1.2.bn1.running_var loaded from backbone.body.layer1.2.bn1.running_var of shape (64,) 2020-08-07 18:22:33,432 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer1.2.bn1.weight loaded from backbone.body.layer1.2.bn1.weight of shape (64,) 2020-08-07 18:22:33,432 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer1.2.bn2.bias loaded from backbone.body.layer1.2.bn2.bias of shape (64,) 2020-08-07 18:22:33,432 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer1.2.bn2.running_mean loaded from backbone.body.layer1.2.bn2.running_mean of shape (64,) 2020-08-07 18:22:33,432 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer1.2.bn2.running_var loaded from backbone.body.layer1.2.bn2.running_var of shape (64,) 2020-08-07 18:22:33,432 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer1.2.bn2.weight loaded from backbone.body.layer1.2.bn2.weight of shape (64,) 2020-08-07 18:22:33,432 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer1.2.bn3.bias loaded from backbone.body.layer1.2.bn3.bias of shape (256,) 2020-08-07 18:22:33,432 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer1.2.bn3.running_mean loaded from backbone.body.layer1.2.bn3.running_mean of shape (256,) 2020-08-07 18:22:33,433 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer1.2.bn3.running_var loaded from backbone.body.layer1.2.bn3.running_var of shape (256,) 2020-08-07 18:22:33,433 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer1.2.bn3.weight loaded from backbone.body.layer1.2.bn3.weight of shape (256,) 2020-08-07 18:22:33,433 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer1.2.conv1.weight loaded from backbone.body.layer1.2.conv1.weight of shape (64, 256, 1, 1) 2020-08-07 18:22:33,433 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer1.2.conv2.weight loaded from backbone.body.layer1.2.conv2.weight of shape (64, 64, 3, 3) 2020-08-07 18:22:33,433 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer1.2.conv3.weight loaded from backbone.body.layer1.2.conv3.weight of shape (256, 64, 1, 1) 2020-08-07 18:22:33,433 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer2.0.bn1.bias loaded from backbone.body.layer2.0.bn1.bias of shape (128,) 2020-08-07 18:22:33,433 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer2.0.bn1.running_mean loaded from backbone.body.layer2.0.bn1.running_mean of shape (128,) 2020-08-07 18:22:33,433 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer2.0.bn1.running_var loaded from backbone.body.layer2.0.bn1.running_var of shape (128,) 2020-08-07 18:22:33,433 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer2.0.bn1.weight loaded from backbone.body.layer2.0.bn1.weight of shape (128,) 2020-08-07 18:22:33,434 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer2.0.bn2.bias loaded from backbone.body.layer2.0.bn2.bias of shape (128,) 2020-08-07 18:22:33,434 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer2.0.bn2.running_mean loaded from backbone.body.layer2.0.bn2.running_mean of shape (128,) 2020-08-07 18:22:33,434 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer2.0.bn2.running_var loaded from backbone.body.layer2.0.bn2.running_var of shape (128,) 2020-08-07 18:22:33,434 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer2.0.bn2.weight loaded from backbone.body.layer2.0.bn2.weight of shape (128,) 2020-08-07 18:22:33,434 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer2.0.bn3.bias loaded from backbone.body.layer2.0.bn3.bias of shape (512,) 2020-08-07 18:22:33,434 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer2.0.bn3.running_mean loaded from backbone.body.layer2.0.bn3.running_mean of shape (512,) 2020-08-07 18:22:33,434 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer2.0.bn3.running_var loaded from backbone.body.layer2.0.bn3.running_var of shape (512,) 2020-08-07 18:22:33,434 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer2.0.bn3.weight loaded from backbone.body.layer2.0.bn3.weight of shape (512,) 2020-08-07 18:22:33,434 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer2.0.conv1.weight loaded from backbone.body.layer2.0.conv1.weight of shape (128, 256, 1, 1) 2020-08-07 18:22:33,434 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer2.0.conv2.weight loaded from backbone.body.layer2.0.conv2.weight of shape (128, 128, 3, 3) 2020-08-07 18:22:33,435 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer2.0.conv3.weight loaded from backbone.body.layer2.0.conv3.weight of shape (512, 128, 1, 1) 2020-08-07 18:22:33,435 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer2.0.downsample.0.weight loaded from backbone.body.layer2.0.downsample.0.weight of shape (512, 256, 1, 1) 2020-08-07 18:22:33,435 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer2.0.downsample.1.bias loaded from backbone.body.layer2.0.downsample.1.bias of shape (512,) 2020-08-07 18:22:33,435 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer2.0.downsample.1.running_mean loaded from backbone.body.layer2.0.downsample.1.running_mean of shape (512,) 2020-08-07 18:22:33,435 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer2.0.downsample.1.running_var loaded from backbone.body.layer2.0.downsample.1.running_var of shape (512,) 2020-08-07 18:22:33,435 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer2.0.downsample.1.weight loaded from backbone.body.layer2.0.downsample.1.weight of shape (512,) 2020-08-07 18:22:33,435 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer2.1.bn1.bias loaded from backbone.body.layer2.1.bn1.bias of shape (128,) 2020-08-07 18:22:33,435 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer2.1.bn1.running_mean loaded from backbone.body.layer2.1.bn1.running_mean of shape (128,) 2020-08-07 18:22:33,435 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer2.1.bn1.running_var loaded from backbone.body.layer2.1.bn1.running_var of shape (128,) 2020-08-07 18:22:33,435 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer2.1.bn1.weight loaded from backbone.body.layer2.1.bn1.weight of shape (128,) 2020-08-07 18:22:33,436 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer2.1.bn2.bias loaded from backbone.body.layer2.1.bn2.bias of shape (128,) 2020-08-07 18:22:33,436 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer2.1.bn2.running_mean loaded from backbone.body.layer2.1.bn2.running_mean of shape (128,) 2020-08-07 18:22:33,436 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer2.1.bn2.running_var loaded from backbone.body.layer2.1.bn2.running_var of shape (128,) 2020-08-07 18:22:33,436 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer2.1.bn2.weight loaded from backbone.body.layer2.1.bn2.weight of shape (128,) 2020-08-07 18:22:33,436 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer2.1.bn3.bias loaded from backbone.body.layer2.1.bn3.bias of shape (512,) 2020-08-07 18:22:33,436 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer2.1.bn3.running_mean loaded from backbone.body.layer2.1.bn3.running_mean of shape (512,) 2020-08-07 18:22:33,436 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer2.1.bn3.running_var loaded from backbone.body.layer2.1.bn3.running_var of shape (512,) 2020-08-07 18:22:33,436 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer2.1.bn3.weight loaded from backbone.body.layer2.1.bn3.weight of shape (512,) 2020-08-07 18:22:33,436 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer2.1.conv1.weight loaded from backbone.body.layer2.1.conv1.weight of shape (128, 512, 1, 1) 2020-08-07 18:22:33,436 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer2.1.conv2.weight loaded from backbone.body.layer2.1.conv2.weight of shape (128, 128, 3, 3) 2020-08-07 18:22:33,437 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer2.1.conv3.weight loaded from backbone.body.layer2.1.conv3.weight of shape (512, 128, 1, 1) 2020-08-07 18:22:33,437 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer2.2.bn1.bias loaded from backbone.body.layer2.2.bn1.bias of shape (128,) 2020-08-07 18:22:33,437 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer2.2.bn1.running_mean loaded from backbone.body.layer2.2.bn1.running_mean of shape (128,) 2020-08-07 18:22:33,437 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer2.2.bn1.running_var loaded from backbone.body.layer2.2.bn1.running_var of shape (128,) 2020-08-07 18:22:33,437 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer2.2.bn1.weight loaded from backbone.body.layer2.2.bn1.weight of shape (128,) 2020-08-07 18:22:33,437 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer2.2.bn2.bias loaded from backbone.body.layer2.2.bn2.bias of shape (128,) 2020-08-07 18:22:33,437 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer2.2.bn2.running_mean loaded from backbone.body.layer2.2.bn2.running_mean of shape (128,) 2020-08-07 18:22:33,437 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer2.2.bn2.running_var loaded from backbone.body.layer2.2.bn2.running_var of shape (128,) 2020-08-07 18:22:33,437 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer2.2.bn2.weight loaded from backbone.body.layer2.2.bn2.weight of shape (128,) 2020-08-07 18:22:33,437 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer2.2.bn3.bias loaded from backbone.body.layer2.2.bn3.bias of shape (512,) 2020-08-07 18:22:33,438 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer2.2.bn3.running_mean loaded from backbone.body.layer2.2.bn3.running_mean of shape (512,) 2020-08-07 18:22:33,438 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer2.2.bn3.running_var loaded from backbone.body.layer2.2.bn3.running_var of shape (512,) 2020-08-07 18:22:33,438 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer2.2.bn3.weight loaded from backbone.body.layer2.2.bn3.weight of shape (512,) 2020-08-07 18:22:33,438 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer2.2.conv1.weight loaded from backbone.body.layer2.2.conv1.weight of shape (128, 512, 1, 1) 2020-08-07 18:22:33,438 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer2.2.conv2.weight loaded from backbone.body.layer2.2.conv2.weight of shape (128, 128, 3, 3) 2020-08-07 18:22:33,438 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer2.2.conv3.weight loaded from backbone.body.layer2.2.conv3.weight of shape (512, 128, 1, 1) 2020-08-07 18:22:33,438 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer2.3.bn1.bias loaded from backbone.body.layer2.3.bn1.bias of shape (128,) 2020-08-07 18:22:33,438 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer2.3.bn1.running_mean loaded from backbone.body.layer2.3.bn1.running_mean of shape (128,) 2020-08-07 18:22:33,438 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer2.3.bn1.running_var loaded from backbone.body.layer2.3.bn1.running_var of shape (128,) 2020-08-07 18:22:33,439 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer2.3.bn1.weight loaded from backbone.body.layer2.3.bn1.weight of shape (128,) 2020-08-07 18:22:33,439 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer2.3.bn2.bias loaded from backbone.body.layer2.3.bn2.bias of shape (128,) 2020-08-07 18:22:33,439 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer2.3.bn2.running_mean loaded from backbone.body.layer2.3.bn2.running_mean of shape (128,) 2020-08-07 18:22:33,439 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer2.3.bn2.running_var loaded from backbone.body.layer2.3.bn2.running_var of shape (128,) 2020-08-07 18:22:33,439 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer2.3.bn2.weight loaded from backbone.body.layer2.3.bn2.weight of shape (128,) 2020-08-07 18:22:33,439 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer2.3.bn3.bias loaded from backbone.body.layer2.3.bn3.bias of shape (512,) 2020-08-07 18:22:33,439 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer2.3.bn3.running_mean loaded from backbone.body.layer2.3.bn3.running_mean of shape (512,) 2020-08-07 18:22:33,439 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer2.3.bn3.running_var loaded from backbone.body.layer2.3.bn3.running_var of shape (512,) 2020-08-07 18:22:33,439 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer2.3.bn3.weight loaded from backbone.body.layer2.3.bn3.weight of shape (512,) 2020-08-07 18:22:33,439 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer2.3.conv1.weight loaded from backbone.body.layer2.3.conv1.weight of shape (128, 512, 1, 1) 2020-08-07 18:22:33,440 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer2.3.conv2.weight loaded from backbone.body.layer2.3.conv2.weight of shape (128, 128, 3, 3) 2020-08-07 18:22:33,440 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer2.3.conv3.weight loaded from backbone.body.layer2.3.conv3.weight of shape (512, 128, 1, 1) 2020-08-07 18:22:33,440 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.0.bn1.bias loaded from backbone.body.layer3.0.bn1.bias of shape (256,) 2020-08-07 18:22:33,440 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.0.bn1.running_mean loaded from backbone.body.layer3.0.bn1.running_mean of shape (256,) 2020-08-07 18:22:33,440 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.0.bn1.running_var loaded from backbone.body.layer3.0.bn1.running_var of shape (256,) 2020-08-07 18:22:33,440 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.0.bn1.weight loaded from backbone.body.layer3.0.bn1.weight of shape (256,) 2020-08-07 18:22:33,440 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.0.bn2.bias loaded from backbone.body.layer3.0.bn2.bias of shape (256,) 2020-08-07 18:22:33,440 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.0.bn2.running_mean loaded from backbone.body.layer3.0.bn2.running_mean of shape (256,) 2020-08-07 18:22:33,440 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.0.bn2.running_var loaded from backbone.body.layer3.0.bn2.running_var of shape (256,) 2020-08-07 18:22:33,440 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.0.bn2.weight loaded from backbone.body.layer3.0.bn2.weight of shape (256,) 2020-08-07 18:22:33,440 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.0.bn3.bias loaded from backbone.body.layer3.0.bn3.bias of shape (1024,) 2020-08-07 18:22:33,441 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.0.bn3.running_mean loaded from backbone.body.layer3.0.bn3.running_mean of shape (1024,) 2020-08-07 18:22:33,441 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.0.bn3.running_var loaded from backbone.body.layer3.0.bn3.running_var of shape (1024,) 2020-08-07 18:22:33,441 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.0.bn3.weight loaded from backbone.body.layer3.0.bn3.weight of shape (1024,) 2020-08-07 18:22:33,441 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.0.conv1.weight loaded from backbone.body.layer3.0.conv1.weight of shape (256, 512, 1, 1) 2020-08-07 18:22:33,441 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.0.conv2.weight loaded from backbone.body.layer3.0.conv2.weight of shape (256, 256, 3, 3) 2020-08-07 18:22:33,441 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.0.conv3.weight loaded from backbone.body.layer3.0.conv3.weight of shape (1024, 256, 1, 1) 2020-08-07 18:22:33,441 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.0.downsample.0.weight loaded from backbone.body.layer3.0.downsample.0.weight of shape (1024, 512, 1, 1) 2020-08-07 18:22:33,441 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.0.downsample.1.bias loaded from backbone.body.layer3.0.downsample.1.bias of shape (1024,) 2020-08-07 18:22:33,441 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.0.downsample.1.running_mean loaded from backbone.body.layer3.0.downsample.1.running_mean of shape (1024,) 2020-08-07 18:22:33,441 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.0.downsample.1.running_var loaded from backbone.body.layer3.0.downsample.1.running_var of shape (1024,) 2020-08-07 18:22:33,441 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.0.downsample.1.weight loaded from backbone.body.layer3.0.downsample.1.weight of shape (1024,) 2020-08-07 18:22:33,442 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.1.bn1.bias loaded from backbone.body.layer3.1.bn1.bias of shape (256,) 2020-08-07 18:22:33,442 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.1.bn1.running_mean loaded from backbone.body.layer3.1.bn1.running_mean of shape (256,) 2020-08-07 18:22:33,442 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.1.bn1.running_var loaded from backbone.body.layer3.1.bn1.running_var of shape (256,) 2020-08-07 18:22:33,442 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.1.bn1.weight loaded from backbone.body.layer3.1.bn1.weight of shape (256,) 2020-08-07 18:22:33,442 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.1.bn2.bias loaded from backbone.body.layer3.1.bn2.bias of shape (256,) 2020-08-07 18:22:33,442 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.1.bn2.running_mean loaded from backbone.body.layer3.1.bn2.running_mean of shape (256,) 2020-08-07 18:22:33,442 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.1.bn2.running_var loaded from backbone.body.layer3.1.bn2.running_var of shape (256,) 2020-08-07 18:22:33,442 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.1.bn2.weight loaded from backbone.body.layer3.1.bn2.weight of shape (256,) 2020-08-07 18:22:33,442 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.1.bn3.bias loaded from backbone.body.layer3.1.bn3.bias of shape (1024,) 2020-08-07 18:22:33,442 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.1.bn3.running_mean loaded from backbone.body.layer3.1.bn3.running_mean of shape (1024,) 2020-08-07 18:22:33,442 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.1.bn3.running_var loaded from backbone.body.layer3.1.bn3.running_var of shape (1024,) 2020-08-07 18:22:33,443 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.1.bn3.weight loaded from backbone.body.layer3.1.bn3.weight of shape (1024,) 2020-08-07 18:22:33,443 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.1.conv1.weight loaded from backbone.body.layer3.1.conv1.weight of shape (256, 1024, 1, 1) 2020-08-07 18:22:33,443 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.1.conv2.weight loaded from backbone.body.layer3.1.conv2.weight of shape (256, 256, 3, 3) 2020-08-07 18:22:33,443 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.1.conv3.weight loaded from backbone.body.layer3.1.conv3.weight of shape (1024, 256, 1, 1) 2020-08-07 18:22:33,443 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.2.bn1.bias loaded from backbone.body.layer3.2.bn1.bias of shape (256,) 2020-08-07 18:22:33,443 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.2.bn1.running_mean loaded from backbone.body.layer3.2.bn1.running_mean of shape (256,) 2020-08-07 18:22:33,443 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.2.bn1.running_var loaded from backbone.body.layer3.2.bn1.running_var of shape (256,) 2020-08-07 18:22:33,443 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.2.bn1.weight loaded from backbone.body.layer3.2.bn1.weight of shape (256,) 2020-08-07 18:22:33,443 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.2.bn2.bias loaded from backbone.body.layer3.2.bn2.bias of shape (256,) 2020-08-07 18:22:33,443 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.2.bn2.running_mean loaded from backbone.body.layer3.2.bn2.running_mean of shape (256,) 2020-08-07 18:22:33,444 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.2.bn2.running_var loaded from backbone.body.layer3.2.bn2.running_var of shape (256,) 2020-08-07 18:22:33,444 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.2.bn2.weight loaded from backbone.body.layer3.2.bn2.weight of shape (256,) 2020-08-07 18:22:33,444 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.2.bn3.bias loaded from backbone.body.layer3.2.bn3.bias of shape (1024,) 2020-08-07 18:22:33,444 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.2.bn3.running_mean loaded from backbone.body.layer3.2.bn3.running_mean of shape (1024,) 2020-08-07 18:22:33,444 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.2.bn3.running_var loaded from backbone.body.layer3.2.bn3.running_var of shape (1024,) 2020-08-07 18:22:33,444 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.2.bn3.weight loaded from backbone.body.layer3.2.bn3.weight of shape (1024,) 2020-08-07 18:22:33,444 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.2.conv1.weight loaded from backbone.body.layer3.2.conv1.weight of shape (256, 1024, 1, 1) 2020-08-07 18:22:33,444 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.2.conv2.weight loaded from backbone.body.layer3.2.conv2.weight of shape (256, 256, 3, 3) 2020-08-07 18:22:33,444 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.2.conv3.weight loaded from backbone.body.layer3.2.conv3.weight of shape (1024, 256, 1, 1) 2020-08-07 18:22:33,444 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.3.bn1.bias loaded from backbone.body.layer3.3.bn1.bias of shape (256,) 2020-08-07 18:22:33,445 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.3.bn1.running_mean loaded from backbone.body.layer3.3.bn1.running_mean of shape (256,) 2020-08-07 18:22:33,445 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.3.bn1.running_var loaded from backbone.body.layer3.3.bn1.running_var of shape (256,) 2020-08-07 18:22:33,445 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.3.bn1.weight loaded from backbone.body.layer3.3.bn1.weight of shape (256,) 2020-08-07 18:22:33,445 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.3.bn2.bias loaded from backbone.body.layer3.3.bn2.bias of shape (256,) 2020-08-07 18:22:33,445 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.3.bn2.running_mean loaded from backbone.body.layer3.3.bn2.running_mean of shape (256,) 2020-08-07 18:22:33,445 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.3.bn2.running_var loaded from backbone.body.layer3.3.bn2.running_var of shape (256,) 2020-08-07 18:22:33,445 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.3.bn2.weight loaded from backbone.body.layer3.3.bn2.weight of shape (256,) 2020-08-07 18:22:33,445 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.3.bn3.bias loaded from backbone.body.layer3.3.bn3.bias of shape (1024,) 2020-08-07 18:22:33,445 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.3.bn3.running_mean loaded from backbone.body.layer3.3.bn3.running_mean of shape (1024,) 2020-08-07 18:22:33,445 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.3.bn3.running_var loaded from backbone.body.layer3.3.bn3.running_var of shape (1024,) 2020-08-07 18:22:33,445 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.3.bn3.weight loaded from backbone.body.layer3.3.bn3.weight of shape (1024,) 2020-08-07 18:22:33,446 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.3.conv1.weight loaded from backbone.body.layer3.3.conv1.weight of shape (256, 1024, 1, 1) 2020-08-07 18:22:33,446 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.3.conv2.weight loaded from backbone.body.layer3.3.conv2.weight of shape (256, 256, 3, 3) 2020-08-07 18:22:33,446 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.3.conv3.weight loaded from backbone.body.layer3.3.conv3.weight of shape (1024, 256, 1, 1) 2020-08-07 18:22:33,446 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.4.bn1.bias loaded from backbone.body.layer3.4.bn1.bias of shape (256,) 2020-08-07 18:22:33,446 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.4.bn1.running_mean loaded from backbone.body.layer3.4.bn1.running_mean of shape (256,) 2020-08-07 18:22:33,446 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.4.bn1.running_var loaded from backbone.body.layer3.4.bn1.running_var of shape (256,) 2020-08-07 18:22:33,446 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.4.bn1.weight loaded from backbone.body.layer3.4.bn1.weight of shape (256,) 2020-08-07 18:22:33,446 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.4.bn2.bias loaded from backbone.body.layer3.4.bn2.bias of shape (256,) 2020-08-07 18:22:33,446 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.4.bn2.running_mean loaded from backbone.body.layer3.4.bn2.running_mean of shape (256,) 2020-08-07 18:22:33,446 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.4.bn2.running_var loaded from backbone.body.layer3.4.bn2.running_var of shape (256,) 2020-08-07 18:22:33,447 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.4.bn2.weight loaded from backbone.body.layer3.4.bn2.weight of shape (256,) 2020-08-07 18:22:33,447 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.4.bn3.bias loaded from backbone.body.layer3.4.bn3.bias of shape (1024,) 2020-08-07 18:22:33,447 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.4.bn3.running_mean loaded from backbone.body.layer3.4.bn3.running_mean of shape (1024,) 2020-08-07 18:22:33,447 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.4.bn3.running_var loaded from backbone.body.layer3.4.bn3.running_var of shape (1024,) 2020-08-07 18:22:33,447 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.4.bn3.weight loaded from backbone.body.layer3.4.bn3.weight of shape (1024,) 2020-08-07 18:22:33,447 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.4.conv1.weight loaded from backbone.body.layer3.4.conv1.weight of shape (256, 1024, 1, 1) 2020-08-07 18:22:33,447 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.4.conv2.weight loaded from backbone.body.layer3.4.conv2.weight of shape (256, 256, 3, 3) 2020-08-07 18:22:33,447 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.4.conv3.weight loaded from backbone.body.layer3.4.conv3.weight of shape (1024, 256, 1, 1) 2020-08-07 18:22:33,447 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.5.bn1.bias loaded from backbone.body.layer3.5.bn1.bias of shape (256,) 2020-08-07 18:22:33,447 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.5.bn1.running_mean loaded from backbone.body.layer3.5.bn1.running_mean of shape (256,) 2020-08-07 18:22:33,447 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.5.bn1.running_var loaded from backbone.body.layer3.5.bn1.running_var of shape (256,) 2020-08-07 18:22:33,448 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.5.bn1.weight loaded from backbone.body.layer3.5.bn1.weight of shape (256,) 2020-08-07 18:22:33,448 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.5.bn2.bias loaded from backbone.body.layer3.5.bn2.bias of shape (256,) 2020-08-07 18:22:33,448 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.5.bn2.running_mean loaded from backbone.body.layer3.5.bn2.running_mean of shape (256,) 2020-08-07 18:22:33,448 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.5.bn2.running_var loaded from backbone.body.layer3.5.bn2.running_var of shape (256,) 2020-08-07 18:22:33,448 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.5.bn2.weight loaded from backbone.body.layer3.5.bn2.weight of shape (256,) 2020-08-07 18:22:33,448 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.5.bn3.bias loaded from backbone.body.layer3.5.bn3.bias of shape (1024,) 2020-08-07 18:22:33,448 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.5.bn3.running_mean loaded from backbone.body.layer3.5.bn3.running_mean of shape (1024,) 2020-08-07 18:22:33,448 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.5.bn3.running_var loaded from backbone.body.layer3.5.bn3.running_var of shape (1024,) 2020-08-07 18:22:33,448 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.5.bn3.weight loaded from backbone.body.layer3.5.bn3.weight of shape (1024,) 2020-08-07 18:22:33,448 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.5.conv1.weight loaded from backbone.body.layer3.5.conv1.weight of shape (256, 1024, 1, 1) 2020-08-07 18:22:33,449 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.5.conv2.weight loaded from backbone.body.layer3.5.conv2.weight of shape (256, 256, 3, 3) 2020-08-07 18:22:33,449 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer3.5.conv3.weight loaded from backbone.body.layer3.5.conv3.weight of shape (1024, 256, 1, 1) 2020-08-07 18:22:33,449 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer4.0.bn1.bias loaded from backbone.body.layer4.0.bn1.bias of shape (512,) 2020-08-07 18:22:33,449 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer4.0.bn1.running_mean loaded from backbone.body.layer4.0.bn1.running_mean of shape (512,) 2020-08-07 18:22:33,449 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer4.0.bn1.running_var loaded from backbone.body.layer4.0.bn1.running_var of shape (512,) 2020-08-07 18:22:33,449 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer4.0.bn1.weight loaded from backbone.body.layer4.0.bn1.weight of shape (512,) 2020-08-07 18:22:33,449 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer4.0.bn2.bias loaded from backbone.body.layer4.0.bn2.bias of shape (512,) 2020-08-07 18:22:33,449 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer4.0.bn2.running_mean loaded from backbone.body.layer4.0.bn2.running_mean of shape (512,) 2020-08-07 18:22:33,449 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer4.0.bn2.running_var loaded from backbone.body.layer4.0.bn2.running_var of shape (512,) 2020-08-07 18:22:33,449 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer4.0.bn2.weight loaded from backbone.body.layer4.0.bn2.weight of shape (512,) 2020-08-07 18:22:33,449 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer4.0.bn3.bias loaded from backbone.body.layer4.0.bn3.bias of shape (2048,) 2020-08-07 18:22:33,450 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer4.0.bn3.running_mean loaded from backbone.body.layer4.0.bn3.running_mean of shape (2048,) 2020-08-07 18:22:33,450 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer4.0.bn3.running_var loaded from backbone.body.layer4.0.bn3.running_var of shape (2048,) 2020-08-07 18:22:33,450 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer4.0.bn3.weight loaded from backbone.body.layer4.0.bn3.weight of shape (2048,) 2020-08-07 18:22:33,450 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer4.0.conv1.weight loaded from backbone.body.layer4.0.conv1.weight of shape (512, 1024, 1, 1) 2020-08-07 18:22:33,450 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer4.0.conv2.weight loaded from backbone.body.layer4.0.conv2.weight of shape (512, 512, 3, 3) 2020-08-07 18:22:33,450 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer4.0.conv3.weight loaded from backbone.body.layer4.0.conv3.weight of shape (2048, 512, 1, 1) 2020-08-07 18:22:33,450 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer4.0.downsample.0.weight loaded from backbone.body.layer4.0.downsample.0.weight of shape (2048, 1024, 1, 1) 2020-08-07 18:22:33,450 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer4.0.downsample.1.bias loaded from backbone.body.layer4.0.downsample.1.bias of shape (2048,) 2020-08-07 18:22:33,450 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer4.0.downsample.1.running_mean loaded from backbone.body.layer4.0.downsample.1.running_mean of shape (2048,) 2020-08-07 18:22:33,450 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer4.0.downsample.1.running_var loaded from backbone.body.layer4.0.downsample.1.running_var of shape (2048,) 2020-08-07 18:22:33,450 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer4.0.downsample.1.weight loaded from backbone.body.layer4.0.downsample.1.weight of shape (2048,) 2020-08-07 18:22:33,451 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer4.1.bn1.bias loaded from backbone.body.layer4.1.bn1.bias of shape (512,) 2020-08-07 18:22:33,451 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer4.1.bn1.running_mean loaded from backbone.body.layer4.1.bn1.running_mean of shape (512,) 2020-08-07 18:22:33,451 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer4.1.bn1.running_var loaded from backbone.body.layer4.1.bn1.running_var of shape (512,) 2020-08-07 18:22:33,451 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer4.1.bn1.weight loaded from backbone.body.layer4.1.bn1.weight of shape (512,) 2020-08-07 18:22:33,451 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer4.1.bn2.bias loaded from backbone.body.layer4.1.bn2.bias of shape (512,) 2020-08-07 18:22:33,451 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer4.1.bn2.running_mean loaded from backbone.body.layer4.1.bn2.running_mean of shape (512,) 2020-08-07 18:22:33,451 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer4.1.bn2.running_var loaded from backbone.body.layer4.1.bn2.running_var of shape (512,) 2020-08-07 18:22:33,451 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer4.1.bn2.weight loaded from backbone.body.layer4.1.bn2.weight of shape (512,) 2020-08-07 18:22:33,451 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer4.1.bn3.bias loaded from backbone.body.layer4.1.bn3.bias of shape (2048,) 2020-08-07 18:22:33,451 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer4.1.bn3.running_mean loaded from backbone.body.layer4.1.bn3.running_mean of shape (2048,) 2020-08-07 18:22:33,452 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer4.1.bn3.running_var loaded from backbone.body.layer4.1.bn3.running_var of shape (2048,) 2020-08-07 18:22:33,452 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer4.1.bn3.weight loaded from backbone.body.layer4.1.bn3.weight of shape (2048,) 2020-08-07 18:22:33,452 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer4.1.conv1.weight loaded from backbone.body.layer4.1.conv1.weight of shape (512, 2048, 1, 1) 2020-08-07 18:22:33,452 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer4.1.conv2.weight loaded from backbone.body.layer4.1.conv2.weight of shape (512, 512, 3, 3) 2020-08-07 18:22:33,452 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer4.1.conv3.weight loaded from backbone.body.layer4.1.conv3.weight of shape (2048, 512, 1, 1) 2020-08-07 18:22:33,452 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer4.2.bn1.bias loaded from backbone.body.layer4.2.bn1.bias of shape (512,) 2020-08-07 18:22:33,452 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer4.2.bn1.running_mean loaded from backbone.body.layer4.2.bn1.running_mean of shape (512,) 2020-08-07 18:22:33,452 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer4.2.bn1.running_var loaded from backbone.body.layer4.2.bn1.running_var of shape (512,) 2020-08-07 18:22:33,452 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer4.2.bn1.weight loaded from backbone.body.layer4.2.bn1.weight of shape (512,) 2020-08-07 18:22:33,452 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer4.2.bn2.bias loaded from backbone.body.layer4.2.bn2.bias of shape (512,) 2020-08-07 18:22:33,452 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer4.2.bn2.running_mean loaded from backbone.body.layer4.2.bn2.running_mean of shape (512,) 2020-08-07 18:22:33,452 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer4.2.bn2.running_var loaded from backbone.body.layer4.2.bn2.running_var of shape (512,) 2020-08-07 18:22:33,453 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer4.2.bn2.weight loaded from backbone.body.layer4.2.bn2.weight of shape (512,) 2020-08-07 18:22:33,453 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer4.2.bn3.bias loaded from backbone.body.layer4.2.bn3.bias of shape (2048,) 2020-08-07 18:22:33,453 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer4.2.bn3.running_mean loaded from backbone.body.layer4.2.bn3.running_mean of shape (2048,) 2020-08-07 18:22:33,453 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer4.2.bn3.running_var loaded from backbone.body.layer4.2.bn3.running_var of shape (2048,) 2020-08-07 18:22:33,453 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer4.2.bn3.weight loaded from backbone.body.layer4.2.bn3.weight of shape (2048,) 2020-08-07 18:22:33,453 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer4.2.conv1.weight loaded from backbone.body.layer4.2.conv1.weight of shape (512, 2048, 1, 1) 2020-08-07 18:22:33,453 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer4.2.conv2.weight loaded from backbone.body.layer4.2.conv2.weight of shape (512, 512, 3, 3) 2020-08-07 18:22:33,453 fcos_core_s80.utils.model_serialization INFO: backbone.body.layer4.2.conv3.weight loaded from backbone.body.layer4.2.conv3.weight of shape (2048, 512, 1, 1) 2020-08-07 18:22:33,454 fcos_core_s80.utils.model_serialization INFO: backbone.body.stem.bn1.bias loaded from backbone.body.stem.bn1.bias of shape (64,) 2020-08-07 18:22:33,454 fcos_core_s80.utils.model_serialization INFO: backbone.body.stem.bn1.running_mean loaded from backbone.body.stem.bn1.running_mean of shape (64,) 2020-08-07 18:22:33,454 fcos_core_s80.utils.model_serialization INFO: backbone.body.stem.bn1.running_var loaded from backbone.body.stem.bn1.running_var of shape (64,) 2020-08-07 18:22:33,454 fcos_core_s80.utils.model_serialization INFO: backbone.body.stem.bn1.weight loaded from backbone.body.stem.bn1.weight of shape (64,) 2020-08-07 18:22:33,454 fcos_core_s80.utils.model_serialization INFO: backbone.body.stem.conv1.weight loaded from backbone.body.stem.conv1.weight of shape (64, 3, 7, 7) 2020-08-07 18:22:33,454 fcos_core_s80.utils.model_serialization INFO: backbone.fpn.fpn_inner2.bias loaded from backbone.fpn.fpn_inner2.bias of shape (256,) 2020-08-07 18:22:33,454 fcos_core_s80.utils.model_serialization INFO: backbone.fpn.fpn_inner2.weight loaded from backbone.fpn.fpn_inner2.weight of shape (256, 512, 1, 1) 2020-08-07 18:22:33,454 fcos_core_s80.utils.model_serialization INFO: backbone.fpn.fpn_inner3.bias loaded from backbone.fpn.fpn_inner3.bias of shape (256,) 2020-08-07 18:22:33,454 fcos_core_s80.utils.model_serialization INFO: backbone.fpn.fpn_inner3.weight loaded from backbone.fpn.fpn_inner3.weight of shape (256, 1024, 1, 1) 2020-08-07 18:22:33,454 fcos_core_s80.utils.model_serialization INFO: backbone.fpn.fpn_inner4.bias loaded from backbone.fpn.fpn_inner4.bias of shape (256,) 2020-08-07 18:22:33,454 fcos_core_s80.utils.model_serialization INFO: backbone.fpn.fpn_inner4.weight loaded from backbone.fpn.fpn_inner4.weight of shape (256, 2048, 1, 1) 2020-08-07 18:22:33,455 fcos_core_s80.utils.model_serialization INFO: backbone.fpn.fpn_layer2.bias loaded from backbone.fpn.fpn_layer2.bias of shape (256,) 2020-08-07 18:22:33,455 fcos_core_s80.utils.model_serialization INFO: backbone.fpn.fpn_layer2.weight loaded from backbone.fpn.fpn_layer2.weight of shape (256, 256, 3, 3) 2020-08-07 18:22:33,455 fcos_core_s80.utils.model_serialization INFO: backbone.fpn.fpn_layer3.bias loaded from backbone.fpn.fpn_layer3.bias of shape (256,) 2020-08-07 18:22:33,455 fcos_core_s80.utils.model_serialization INFO: backbone.fpn.fpn_layer3.weight loaded from backbone.fpn.fpn_layer3.weight of shape (256, 256, 3, 3) 2020-08-07 18:22:33,455 fcos_core_s80.utils.model_serialization INFO: backbone.fpn.fpn_layer4.bias loaded from backbone.fpn.fpn_layer4.bias of shape (256,) 2020-08-07 18:22:33,455 fcos_core_s80.utils.model_serialization INFO: backbone.fpn.fpn_layer4.weight loaded from backbone.fpn.fpn_layer4.weight of shape (256, 256, 3, 3) 2020-08-07 18:22:33,455 fcos_core_s80.utils.model_serialization INFO: backbone.fpn.top_blocks.p6.bias loaded from backbone.fpn.top_blocks.p6.bias of shape (256,) 2020-08-07 18:22:33,455 fcos_core_s80.utils.model_serialization INFO: backbone.fpn.top_blocks.p6.weight loaded from backbone.fpn.top_blocks.p6.weight of shape (256, 256, 3, 3) 2020-08-07 18:22:33,455 fcos_core_s80.utils.model_serialization INFO: backbone.fpn.top_blocks.p7.bias loaded from backbone.fpn.top_blocks.p7.bias of shape (256,) 2020-08-07 18:22:33,455 fcos_core_s80.utils.model_serialization INFO: backbone.fpn.top_blocks.p7.weight loaded from backbone.fpn.top_blocks.p7.weight of shape (256, 256, 3, 3) 2020-08-07 18:22:33,456 fcos_core_s80.utils.model_serialization INFO: rpn.head.bbox_pred.bias loaded from rpn.head.bbox_pred.bias of shape (4,) 2020-08-07 18:22:33,456 fcos_core_s80.utils.model_serialization INFO: rpn.head.bbox_pred.weight loaded from rpn.head.bbox_pred.weight of shape (4, 256, 3, 3) 2020-08-07 18:22:33,456 fcos_core_s80.utils.model_serialization INFO: rpn.head.bbox_tower.0.bias loaded from rpn.head.bbox_tower.0.bias of shape (256,) 2020-08-07 18:22:33,456 fcos_core_s80.utils.model_serialization INFO: rpn.head.bbox_tower.0.weight loaded from rpn.head.bbox_tower.0.weight of shape (256, 256, 3, 3) 2020-08-07 18:22:33,456 fcos_core_s80.utils.model_serialization INFO: rpn.head.bbox_tower.1.bias loaded from rpn.head.bbox_tower.1.bias of shape (256,) 2020-08-07 18:22:33,456 fcos_core_s80.utils.model_serialization INFO: rpn.head.bbox_tower.1.weight loaded from rpn.head.bbox_tower.1.weight of shape (256,) 2020-08-07 18:22:33,456 fcos_core_s80.utils.model_serialization INFO: rpn.head.bbox_tower.10.bias loaded from rpn.head.bbox_tower.10.bias of shape (256,) 2020-08-07 18:22:33,456 fcos_core_s80.utils.model_serialization INFO: rpn.head.bbox_tower.10.weight loaded from rpn.head.bbox_tower.10.weight of shape (256,) 2020-08-07 18:22:33,456 fcos_core_s80.utils.model_serialization INFO: rpn.head.bbox_tower.3.bias loaded from rpn.head.bbox_tower.3.bias of shape (256,) 2020-08-07 18:22:33,456 fcos_core_s80.utils.model_serialization INFO: rpn.head.bbox_tower.3.weight loaded from rpn.head.bbox_tower.3.weight of shape (256, 256, 3, 3) 2020-08-07 18:22:33,456 fcos_core_s80.utils.model_serialization INFO: rpn.head.bbox_tower.4.bias loaded from rpn.head.bbox_tower.4.bias of shape (256,) 2020-08-07 18:22:33,457 fcos_core_s80.utils.model_serialization INFO: rpn.head.bbox_tower.4.weight loaded from rpn.head.bbox_tower.4.weight of shape (256,) 2020-08-07 18:22:33,457 fcos_core_s80.utils.model_serialization INFO: rpn.head.bbox_tower.6.bias loaded from rpn.head.bbox_tower.6.bias of shape (256,) 2020-08-07 18:22:33,457 fcos_core_s80.utils.model_serialization INFO: rpn.head.bbox_tower.6.weight loaded from rpn.head.bbox_tower.6.weight of shape (256, 256, 3, 3) 2020-08-07 18:22:33,457 fcos_core_s80.utils.model_serialization INFO: rpn.head.bbox_tower.7.bias loaded from rpn.head.bbox_tower.7.bias of shape (256,) 2020-08-07 18:22:33,457 fcos_core_s80.utils.model_serialization INFO: rpn.head.bbox_tower.7.weight loaded from rpn.head.bbox_tower.7.weight of shape (256,) 2020-08-07 18:22:33,457 fcos_core_s80.utils.model_serialization INFO: rpn.head.bbox_tower.9.bias loaded from rpn.head.bbox_tower.9.bias of shape (256,) 2020-08-07 18:22:33,457 fcos_core_s80.utils.model_serialization INFO: rpn.head.bbox_tower.9.weight loaded from rpn.head.bbox_tower.9.weight of shape (256, 256, 3, 3) 2020-08-07 18:22:33,457 fcos_core_s80.utils.model_serialization INFO: rpn.head.centerness.bias loaded from rpn.head.centerness.bias of shape (1,) 2020-08-07 18:22:33,457 fcos_core_s80.utils.model_serialization INFO: rpn.head.centerness.weight loaded from rpn.head.centerness.weight of shape (1, 256, 3, 3) 2020-08-07 18:22:33,457 fcos_core_s80.utils.model_serialization INFO: rpn.head.cls_logits.bias loaded from rpn.head.cls_logits.bias of shape (80,) 2020-08-07 18:22:33,457 fcos_core_s80.utils.model_serialization INFO: rpn.head.cls_logits.weight loaded from rpn.head.cls_logits.weight of shape (80, 256, 3, 3) 2020-08-07 18:22:33,458 fcos_core_s80.utils.model_serialization INFO: rpn.head.cls_tower.0.bias loaded from rpn.head.cls_tower.0.bias of shape (256,) 2020-08-07 18:22:33,458 fcos_core_s80.utils.model_serialization INFO: rpn.head.cls_tower.0.weight loaded from rpn.head.cls_tower.0.weight of shape (256, 256, 3, 3) 2020-08-07 18:22:33,458 fcos_core_s80.utils.model_serialization INFO: rpn.head.cls_tower.1.bias loaded from rpn.head.cls_tower.1.bias of shape (256,) 2020-08-07 18:22:33,458 fcos_core_s80.utils.model_serialization INFO: rpn.head.cls_tower.1.weight loaded from rpn.head.cls_tower.1.weight of shape (256,) 2020-08-07 18:22:33,458 fcos_core_s80.utils.model_serialization INFO: rpn.head.cls_tower.10.bias loaded from rpn.head.cls_tower.10.bias of shape (256,) 2020-08-07 18:22:33,458 fcos_core_s80.utils.model_serialization INFO: rpn.head.cls_tower.10.weight loaded from rpn.head.cls_tower.10.weight of shape (256,) 2020-08-07 18:22:33,458 fcos_core_s80.utils.model_serialization INFO: rpn.head.cls_tower.3.bias loaded from rpn.head.cls_tower.3.bias of shape (256,) 2020-08-07 18:22:33,458 fcos_core_s80.utils.model_serialization INFO: rpn.head.cls_tower.3.weight loaded from rpn.head.cls_tower.3.weight of shape (256, 256, 3, 3) 2020-08-07 18:22:33,458 fcos_core_s80.utils.model_serialization INFO: rpn.head.cls_tower.4.bias loaded from rpn.head.cls_tower.4.bias of shape (256,) 2020-08-07 18:22:33,458 fcos_core_s80.utils.model_serialization INFO: rpn.head.cls_tower.4.weight loaded from rpn.head.cls_tower.4.weight of shape (256,) 2020-08-07 18:22:33,459 fcos_core_s80.utils.model_serialization INFO: rpn.head.cls_tower.6.bias loaded from rpn.head.cls_tower.6.bias of shape (256,) 2020-08-07 18:22:33,459 fcos_core_s80.utils.model_serialization INFO: rpn.head.cls_tower.6.weight loaded from rpn.head.cls_tower.6.weight of shape (256, 256, 3, 3) 2020-08-07 18:22:33,459 fcos_core_s80.utils.model_serialization INFO: rpn.head.cls_tower.7.bias loaded from rpn.head.cls_tower.7.bias of shape (256,) 2020-08-07 18:22:33,459 fcos_core_s80.utils.model_serialization INFO: rpn.head.cls_tower.7.weight loaded from rpn.head.cls_tower.7.weight of shape (256,) 2020-08-07 18:22:33,459 fcos_core_s80.utils.model_serialization INFO: rpn.head.cls_tower.9.bias loaded from rpn.head.cls_tower.9.bias of shape (256,) 2020-08-07 18:22:33,459 fcos_core_s80.utils.model_serialization INFO: rpn.head.cls_tower.9.weight loaded from rpn.head.cls_tower.9.weight of shape (256, 256, 3, 3) 2020-08-07 18:22:33,459 fcos_core_s80.utils.model_serialization INFO: rpn.head.scales.0.scale loaded from rpn.head.scales.0.scale of shape (1,) 2020-08-07 18:22:33,459 fcos_core_s80.utils.model_serialization INFO: rpn.head.scales.1.scale loaded from rpn.head.scales.1.scale of shape (1,) 2020-08-07 18:22:33,459 fcos_core_s80.utils.model_serialization INFO: rpn.head.scales.2.scale loaded from rpn.head.scales.2.scale of shape (1,) 2020-08-07 18:22:33,459 fcos_core_s80.utils.model_serialization INFO: rpn.head.scales.3.scale loaded from rpn.head.scales.3.scale of shape (1,) 2020-08-07 18:22:33,460 fcos_core_s80.utils.model_serialization INFO: rpn.head.scales.4.scale loaded from rpn.head.scales.4.scale of shape (1,) 2020-08-07 18:22:33,903 fcos_core_s80.data.build WARNING: When using more than one image per GPU you may encounter an out-of-memory (OOM) error if your GPU does not have sufficient memory. If this happens, you can reduce SOLVER.IMS_PER_BATCH (for training) or TEST.IMS_PER_BATCH (for inference). For training, you must also adjust the learning rate and schedule length according to the linear scaling rule. See for example: https://github.com/facebookresearch/Detectron/blob/master/configs/getting_started/tutorial_1gpu_e2e_faster_rcnn_R-50-FPN.yaml#L14 loading annotations into memory... Done (t=1.02s) creating index... index created! 2020-08-07 18:22:35,306 fcos_core_s80.inference INFO: Start evaluation on coco_2017_val dataset(5000 images). 2020-08-07 18:34:20,668 fcos_core_s80.inference INFO: Total run time: 0:11:45.361560 (0.1410723120212555 s / img per device, on 1 devices) 2020-08-07 18:34:20,668 fcos_core_s80.inference INFO: Model inference time: 0:00:00 (0.0 s / img per device, on 1 devices) 2020-08-07 18:34:23,146 fcos_core_s80.inference INFO: Preparing results for COCO format 2020-08-07 18:34:23,147 fcos_core_s80.inference INFO: Preparing bbox results 2020-08-07 18:34:25,934 fcos_core_s80.inference INFO: Evaluating predictions Loading and preparing results... DONE (t=4.96s) creating index... index created! Running per image evaluation... Evaluate annotation type bbox DONE (t=1.44s). Accumulating evaluation results... DONE (t=0.19s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000 Running per image evaluation... Evaluate annotation type bbox DONE (t=0.40s). Accumulating evaluation results... DONE (t=0.03s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000 Running per image evaluation... Evaluate annotation type bbox DONE (t=0.51s). Accumulating evaluation results... DONE (t=0.06s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000 Running per image evaluation... Evaluate annotation type bbox DONE (t=0.39s). Accumulating evaluation results... DONE (t=0.03s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000 Running per image evaluation... Evaluate annotation type bbox DONE (t=0.37s). Accumulating evaluation results... DONE (t=0.03s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000 Running per image evaluation... Evaluate annotation type bbox DONE (t=0.39s). Accumulating evaluation results... DONE (t=0.03s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000 Running per image evaluation... Evaluate annotation type bbox DONE (t=0.38s). Accumulating evaluation results... DONE (t=0.03s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000 Running per image evaluation... Evaluate annotation type bbox DONE (t=0.56s). Accumulating evaluation results... DONE (t=0.04s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000 Running per image evaluation... Evaluate annotation type bbox DONE (t=0.38s). Accumulating evaluation results... DONE (t=0.03s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000 Running per image evaluation... Evaluate annotation type bbox DONE (t=0.40s). Accumulating evaluation results... DONE (t=0.03s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000 Running per image evaluation... Evaluate annotation type bbox DONE (t=0.36s). Accumulating evaluation results... DONE (t=0.03s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000 Running per image evaluation... Evaluate annotation type bbox DONE (t=0.35s). Accumulating evaluation results... DONE (t=0.03s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000 Running per image evaluation... Evaluate annotation type bbox DONE (t=0.34s). Accumulating evaluation results... DONE (t=0.03s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000 Running per image evaluation... Evaluate annotation type bbox DONE (t=0.40s). Accumulating evaluation results... DONE (t=0.04s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000 Running per image evaluation... Evaluate annotation type bbox DONE (t=0.37s). Accumulating evaluation results... DONE (t=0.03s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000 Running per image evaluation... Evaluate annotation type bbox DONE (t=0.39s). Accumulating evaluation results... DONE (t=0.04s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000 Running per image evaluation... Evaluate annotation type bbox DONE (t=0.39s). Accumulating evaluation results... DONE (t=0.04s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000 Running per image evaluation... Evaluate annotation type bbox DONE (t=0.50s). Accumulating evaluation results... DONE (t=0.03s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000 Running per image evaluation... Evaluate annotation type bbox DONE (t=0.35s). Accumulating evaluation results... DONE (t=0.03s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000 Running per image evaluation... Evaluate annotation type bbox DONE (t=0.36s). Accumulating evaluation results... DONE (t=0.03s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000 Running per image evaluation... Evaluate annotation type bbox DONE (t=0.36s). Accumulating evaluation results... DONE (t=0.03s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000 Running per image evaluation... Evaluate annotation type bbox DONE (t=0.35s). Accumulating evaluation results... DONE (t=0.03s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000 Running per image evaluation... Evaluate annotation type bbox DONE (t=0.36s). Accumulating evaluation results... DONE (t=0.03s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000 Running per image evaluation... Evaluate annotation type bbox DONE (t=1.00s). Accumulating evaluation results... DONE (t=0.03s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000 Running per image evaluation... Evaluate annotation type bbox DONE (t=0.40s). Accumulating evaluation results... DONE (t=0.04s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000 Running per image evaluation... Evaluate annotation type bbox DONE (t=0.39s). Accumulating evaluation results... DONE (t=0.04s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000 Running per image evaluation... Evaluate annotation type bbox DONE (t=0.59s). Accumulating evaluation results... DONE (t=0.04s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000 Running per image evaluation... Evaluate annotation type bbox DONE (t=0.37s). Accumulating evaluation results... DONE (t=0.03s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000 Running per image evaluation... Evaluate annotation type bbox DONE (t=0.37s). Accumulating evaluation results... DONE (t=0.03s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000 Running per image evaluation... Evaluate annotation type bbox DONE (t=0.35s). Accumulating evaluation results... DONE (t=0.03s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000 Running per image evaluation... Evaluate annotation type bbox DONE (t=0.37s). Accumulating evaluation results... DONE (t=0.03s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000 Running per image evaluation... Evaluate annotation type bbox DONE (t=0.35s). Accumulating evaluation results... DONE (t=0.03s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000 Running per image evaluation... Evaluate annotation type bbox DONE (t=0.39s). Accumulating evaluation results... DONE (t=0.03s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000 Running per image evaluation... Evaluate annotation type bbox DONE (t=0.37s). Accumulating evaluation results... DONE (t=0.03s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000 Running per image evaluation... Evaluate annotation type bbox DONE (t=0.38s). Accumulating evaluation results... DONE (t=0.03s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000 Running per image evaluation... Evaluate annotation type bbox DONE (t=0.37s). Accumulating evaluation results... DONE (t=0.03s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000 Running per image evaluation... Evaluate annotation type bbox DONE (t=0.50s). Accumulating evaluation results... DONE (t=0.03s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000 Running per image evaluation... Evaluate annotation type bbox DONE (t=0.38s). Accumulating evaluation results... DONE (t=0.03s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000 Running per image evaluation... Evaluate annotation type bbox DONE (t=0.38s). Accumulating evaluation results... DONE (t=0.03s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000 Running per image evaluation... Evaluate annotation type bbox DONE (t=0.46s). Accumulating evaluation results... DONE (t=0.05s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000 Running per image evaluation... Evaluate annotation type bbox DONE (t=1.23s). Accumulating evaluation results... DONE (t=0.25s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.249 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.414 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.262 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.150 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.326 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.559 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.159 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.396 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.449 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.289 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.614 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.774 Running per image evaluation... Evaluate annotation type bbox DONE (t=2.17s). Accumulating evaluation results... DONE (t=0.51s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.306 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.435 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.337 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.187 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.425 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.464 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.235 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.497 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.522 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.358 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.655 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.762 Running per image evaluation... Evaluate annotation type bbox DONE (t=0.74s). Accumulating evaluation results... DONE (t=0.13s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.101 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.194 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.101 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.071 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.175 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.086 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.166 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.335 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.346 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.183 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.499 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.464 Running per image evaluation... Evaluate annotation type bbox DONE (t=0.78s). Accumulating evaluation results... DONE (t=0.16s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.038 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.081 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.030 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.040 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.077 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.086 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.094 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.185 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.188 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.120 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.333 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.238 Running per image evaluation... Evaluate annotation type bbox DONE (t=0.73s). Accumulating evaluation results... DONE (t=0.16s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.037 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.077 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.033 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.076 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.109 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.050 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.096 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.206 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.209 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.136 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.371 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.286 Running per image evaluation... Evaluate annotation type bbox DONE (t=1.43s). Accumulating evaluation results... DONE (t=0.31s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.275 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.398 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.317 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.125 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.294 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.423 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.254 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.490 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.501 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.238 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.556 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.710 Running per image evaluation... Evaluate annotation type bbox DONE (t=1.38s). Accumulating evaluation results... DONE (t=0.29s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.096 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.177 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.093 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.068 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.128 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.214 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.084 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.223 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.269 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.107 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.261 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.551 Running per image evaluation... Evaluate annotation type bbox DONE (t=1.01s). Accumulating evaluation results... DONE (t=0.22s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.059 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.081 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.065 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.011 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.118 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.083 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.111 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.272 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.322 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.111 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.444 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.610 Running per image evaluation... Evaluate annotation type bbox DONE (t=0.89s). Accumulating evaluation results... DONE (t=0.21s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.165 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.288 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.158 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.009 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.108 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.240 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.259 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.499 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.505 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.072 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.304 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.701 Running per image evaluation... Evaluate annotation type bbox DONE (t=0.93s). Accumulating evaluation results... DONE (t=0.28s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.206 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.264 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.229 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.038 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.270 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.371 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.134 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.394 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.459 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.164 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.558 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.752 Running per image evaluation... Evaluate annotation type bbox DONE (t=1.45s). Accumulating evaluation results... DONE (t=0.18s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.175 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.313 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.165 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.052 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.195 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.268 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.080 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.339 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.453 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.191 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.472 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.612 Running per image evaluation... Evaluate annotation type bbox DONE (t=1.04s). Accumulating evaluation results... DONE (t=0.12s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.093 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.163 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.091 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.075 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.145 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.079 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.066 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.251 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.325 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.186 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.455 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.432 Running per image evaluation... Evaluate annotation type bbox DONE (t=1.00s). Accumulating evaluation results... DONE (t=0.33s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.083 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.163 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.075 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.029 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.113 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.161 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.184 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.363 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.417 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.111 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.470 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.672 Running per image evaluation... Evaluate annotation type bbox DONE (t=0.98s). Accumulating evaluation results... DONE (t=0.20s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.305 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.438 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.357 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.034 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.290 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.437 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.339 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.535 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.551 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.100 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.503 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.731 Running per image evaluation... Evaluate annotation type bbox DONE (t=3.03s). Accumulating evaluation results... DONE (t=0.60s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.185 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.250 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.208 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.235 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.302 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.277 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.116 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.475 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.633 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.496 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.714 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.846 Running per image evaluation... Evaluate annotation type bbox DONE (t=1.35s). Accumulating evaluation results... DONE (t=0.46s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.154 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.257 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.161 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.085 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.257 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.231 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.201 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.423 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.447 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.184 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.466 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.665 Running per image evaluation... Evaluate annotation type bbox DONE (t=8.03s). Accumulating evaluation results... DONE (t=2.73s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.138 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.236 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.143 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.076 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.165 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.239 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.128 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.344 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.450 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.308 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.504 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.670 Running per image evaluation... Evaluate annotation type bbox DONE (t=1.90s). Accumulating evaluation results... DONE (t=0.64s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.248 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.379 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.258 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.016 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.150 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.293 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.361 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.607 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.617 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.100 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.421 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.700 Running per image evaluation... Evaluate annotation type bbox DONE (t=2.03s). Accumulating evaluation results... DONE (t=0.98s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.101 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.183 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.105 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.096 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.187 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.099 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.204 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.384 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.423 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.232 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.480 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.564 Running per image evaluation... Evaluate annotation type bbox DONE (t=2.14s). Accumulating evaluation results... DONE (t=1.13s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.154 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.246 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.148 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.080 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.167 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.483 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.617 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.631 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.379 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.659 Running per image evaluation... Evaluate annotation type bbox DONE (t=2.87s). Accumulating evaluation results... DONE (t=1.01s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.185 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.295 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.183 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.019 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.064 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.280 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.334 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.457 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.471 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.129 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.318 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.632 Running per image evaluation... Evaluate annotation type bbox DONE (t=1.90s). Accumulating evaluation results... DONE (t=0.59s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.463 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.625 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.516 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.081 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.361 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.539 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.468 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.687 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.711 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.157 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.615 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.778 Running per image evaluation... Evaluate annotation type bbox DONE (t=1.53s). Accumulating evaluation results... DONE (t=0.46s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.395 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.582 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.443 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.062 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.359 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.522 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.440 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.612 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.612 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.213 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.577 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.746 Running per image evaluation... Evaluate annotation type bbox DONE (t=1.40s). Accumulating evaluation results... DONE (t=0.38s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.415 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.574 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.461 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.089 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.234 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.575 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.445 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.598 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.609 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.220 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.475 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.750 Running per image evaluation... Evaluate annotation type bbox DONE (t=0.76s). Accumulating evaluation results... DONE (t=0.17s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.465 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.619 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.582 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.417 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.539 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.472 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.485 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.628 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.628 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.553 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.725 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.600 Running per image evaluation... Evaluate annotation type bbox DONE (t=3.08s). Accumulating evaluation results... DONE (t=0.99s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.152 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.272 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.159 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.161 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.174 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.208 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.202 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.454 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.492 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.426 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.677 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.693 Running per image evaluation... Evaluate annotation type bbox DONE (t=1.06s). Accumulating evaluation results... DONE (t=0.26s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.259 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.437 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.297 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.152 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.300 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.267 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.310 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.477 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.479 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.256 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.463 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.572 Running per image evaluation... Evaluate annotation type bbox DONE (t=2.27s). Accumulating evaluation results... DONE (t=1.00s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.195 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.315 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.205 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.088 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.291 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.397 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.305 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.456 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.465 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.337 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.609 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.675 Running per image evaluation... Evaluate annotation type bbox DONE (t=0.91s). Accumulating evaluation results... DONE (t=0.17s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.328 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.498 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.360 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.003 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.371 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.376 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.475 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.616 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.622 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.150 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.642 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.689 Running per image evaluation... Evaluate annotation type bbox DONE (t=0.94s). Accumulating evaluation results... DONE (t=0.23s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.175 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.287 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.188 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.009 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.124 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.242 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.278 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.406 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.408 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.030 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.322 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.512 Running per image evaluation... Evaluate annotation type bbox DONE (t=0.54s). Accumulating evaluation results... DONE (t=0.09s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.047 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.096 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.011 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.080 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.077 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.063 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.211 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.544 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.544 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.800 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.460 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.500 Running per image evaluation... Evaluate annotation type bbox DONE (t=1.16s). Accumulating evaluation results... DONE (t=0.30s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.240 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.426 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.240 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.109 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.346 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.275 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.300 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.458 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.465 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.230 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.531 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.602 Running per image evaluation... Evaluate annotation type bbox DONE (t=1.03s). Accumulating evaluation results... DONE (t=0.22s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.351 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.500 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.420 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.087 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.434 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.390 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.538 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.539 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.154 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.656 Running per image evaluation... Evaluate annotation type bbox DONE (t=6.11s). Accumulating evaluation results... DONE (t=1.51s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.060 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.140 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.037 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.081 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.076 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.045 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.051 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.174 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.306 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.242 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.476 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.542 Running per image evaluation... Evaluate annotation type bbox DONE (t=2.19s). Accumulating evaluation results... DONE (t=0.67s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.395 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.584 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.435 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.276 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.528 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.495 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.434 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.582 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.590 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.445 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.706 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.719 Running per image evaluation... Evaluate annotation type bbox DONE (t=1.44s). Accumulating evaluation results... DONE (t=0.52s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.221 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.348 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.246 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.166 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.284 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.360 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.238 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.459 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.491 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.338 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.592 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.676 Running per image evaluation... Evaluate annotation type bbox DONE (t=0.91s). Accumulating evaluation results... DONE (t=0.25s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.044 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.092 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.034 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.230 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.056 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.192 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.275 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.275 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.344 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.486 Running per image evaluation... Evaluate annotation type bbox DONE (t=1.34s). Accumulating evaluation results... DONE (t=0.36s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.289 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.511 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.279 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.072 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.234 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.422 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.264 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.492 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.534 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.205 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.478 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.686 Running per image evaluation... Evaluate annotation type bbox DONE (t=0.51s). Accumulating evaluation results... DONE (t=0.08s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.002 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.003 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.002 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.008 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.118 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.118 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.118 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.433 Running per image evaluation... Evaluate annotation type bbox DONE (t=0.78s). Accumulating evaluation results... DONE (t=0.13s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.031 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.059 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.033 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.063 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.073 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.013 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.112 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.202 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.202 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.186 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.217 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.300 Running per image evaluation... Evaluate annotation type bbox DONE (t=72.34s). Accumulating evaluation results... DONE (t=20.61s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.099 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.154 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.106 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.043 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.108 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.136 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.123 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.213 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.228 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.108 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.235 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.308 Maximum f-measures for classes: [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.46258806742174263, 0.4757475083056478, 0.27861227601982463, 0.18807376067693785, 0.19540229885057472, 0.45342895562528013, 0.28386911595866826, 0.18700169122976562, 0.3603154836031549, 0.3802615933412604, 0.3793865464509856, 0.2685185185185185, 0.24509803921568624, 0.5107142857142857, 0.3496985357450474, 0.3080604681024922, 0.31585117165081267, 0.4007579346281383, 0.28400735294117646, 0.35836177474402736, 0.3936515382510457, 0.6305732484076434, 0.5984911986588433, 0.6108094392286221, 0.6222982049090243, 0.3358051420838971, 0.49403341288782826, 0.35968379446640314, 0.5333333333333333, 0.35383064516129037, 0.2485875706214689, 0.46728844713731366, 0.5429704715733804, 0.2649475599184401, 0.6221986473942449, 0.42430096593797656, 0.2126298960831335, 0.5483193277310925, 0.02735562310030395, 0.1931608133086876] Score thresholds for classes (used in demos for visualization purposes): [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.4703640341758728, 0.4727361798286438, 0.38663119077682495, 0.35623297095298767, 0.37722647190093994, 0.38312646746635437, 0.3606594502925873, 0.3987991213798523, 0.44733166694641113, 0.37133318185806274, 0.396053671836853, 0.3247193992137909, 0.5468730926513672, 0.49230754375457764, 0.5655774474143982, 0.41305890679359436, 0.4464961290359497, 0.46184128522872925, 0.4791387915611267, 0.6468421220779419, 0.43104860186576843, 0.6053315997123718, 0.5383934378623962, 0.5869072079658508, 0.5218812823295593, 0.5400450229644775, 0.5463709831237793, 0.5581806302070618, 0.5044541358947754, 0.459420770406723, 0.42476314306259155, 0.48108866810798645, 0.49867093563079834, 0.44977763295173645, 0.6395751237869263, 0.4730090796947479, 0.4202061593532562, 0.5147315263748169, 0.27854931354522705, 0.338283896446228] 2020-08-07 18:38:05,019 fcos_core_s80.inference INFO: OrderedDict([('bbox', OrderedDict([('AP', 0.09850643163693498), ('AP50', 0.15380437648025588), ('AP75', 0.1057837714951089), ('APs', 0.04253907787091786), ('APm', 0.10835336193955489), ('APl', 0.13590968275089071)]))])`