2019-08-09 03:28:47,300 maskrcnn_benchmark INFO: Using 1 GPUs
2019-08-09 03:28:47,300 maskrcnn_benchmark INFO: AMP_VERBOSE: False
DARTS:
ARCH_START_ITER: 5000
LR_A: 0.001
LR_END: 0.0001
TIE_CELL: False
T_MAX: 2500
WD_A: 0.001
DARTS_ON: False
DATALOADER:
ASPECT_RATIO_GROUPING: True
NUM_WORKERS: 4
SIZE_DIVISIBILITY: 32
DATASETS:
TEST: (‘coco_2017_val’,)
TRAIN: (‘coco_2017_train’,)
DTYPE: float32
INPUT:
BRIGHTNESS: 0.0
CONTRAST: 0.0
CROP_PROB_TRAIN: 0.0
CROP_SIZE_TRAIN: -1
HUE: 0.0
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]
SATURATION: 0.0
TO_BGR255: True
VERTICAL_FLIP_PROB_TRAIN: 0.0
IS_LOAD_OPTIMIZER: True
IS_LOAD_SCHEDULER: True
MODEL:
BACKBONE:
CONV_BODY: R-50-FPN-RETINANET
FREEZE_CONV_BODY_AT: 2
CHAR_INST_ON: False
CHAR_ON: 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:
CENTER_SAMPLE: False
FPN_STRIDES: [8, 16, 32, 64, 128]
INFERENCE_TH: 0.05
LOC_LOSS_TYPE: iou
LOSS_ALPHA: 0.25
LOSS_GAMMA: 2.0
NMS_TH: 0.6
NUM_CLASSES: 81
NUM_CONVS: 4
POS_RADIUS: 1.5
PRE_NMS_TOP_N: 1000
PRIOR_PROB: 0.01
SIZES_OF_INTEREST: [64, 128, 256, 512]
USE_BN: False
USE_DEFORMABLE: False
USE_GN: True
USE_LIGHTWEIGHT: False
USE_RELU: True
FCOS_ON: True
FPN:
USE_BN: False
USE_DEFORMABLE: False
USE_GN: False
USE_RELU: False
GROUP_NORM:
DIM_PER_GP: -1
EPSILON: 1e-05
NUM_GROUPS: 32
HEAD:
BBOX_LOSS:
ALPHA: 0.5
BETA: 0.11
GAMMA: 1.5
TYPE: IOULoss
WEIGHT: 1.0
HNASNET:
AFFINE: True
BACKBONE_OUT_CHANNELS: 256
BLOCK_CFG: mn3
FILTER_MULTIPLIER: 16
GENOTYPE:
NUM_BLOCKS: 5
NUM_LAYERS: 12
PRIMITIVES: AutoDeepLab
STRIDE_MULTIPLIER: (1, 2, 4, 8)
TIE_CELL: False
INST_ON: False
KEYPOINT_ON: False
KE_ON: False
MASK_ON: False
META_ARCHITECTURE: GeneralizedRCNN
MSR_ON: False
NECK:
CONV_BODY: none
IN_CHANNELS: 256
NUM_LEVELS: 5
REFINE_LEVEL: 1
REFINE_TYPE: non_local
USE_DEFORMABLE: False
USE_GN: False
ONE_STAGE_HEAD: yolact
PANOPTIC:
CHANNEL_SIZE: 128
HEAD: UPS
LAMBDA_S: 1.0
NUM_CLASSES: 1
PANOPTIC_ON: False
POINTMASK:
CENTER_MASK_THRES: -0.1
MASK_GROUP: (1, 1)
MASK_SIZE: (28, 28)
PREDICTOR: mask
TEACHER_FORCING: False
USE_CONTEXT: False
USE_DEFORMABLE: False
POLYGON_DET: False
RESNETS:
BACKBONE_OUT_CHANNELS: 256
DEFORMABLE_GROUPS: 1
DEFORM_POOLING: False
MAX_DCN_LAYER: 15
NUM_GROUPS: 1
RES2_OUT_CHANNELS: 256
RES5_DILATION: 1
STAGE_WITH_CONTEXT: (False, False, False, False)
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:
CLASS_WEIGHT: 1.0
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_DFPOOL: False
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_INST_HEAD:
PREDICTOR: EmbeddingPredictor
ROI_KEYPOINT_HEAD:
CONV_LAYERS: (512, 512, 512, 512, 512, 512, 512, 512)
FEATURE_EXTRACTOR: KeypointRCNNFeatureExtractor
MLP_HEAD_DIM: 1024
NUM_CLASSES: 17
POOLER_RESOLUTION: 14
POOLER_SAMPLING_RATIO: 0
POOLER_SCALES: (0.0625,)
PREDICTOR: KeypointRCNNPredictor
RESOLUTION: 14
SHARE_BOX_FEATURE_EXTRACTOR: True
ROI_KE_HEAD:
CONV_LAYERS: (256, 256, 256, 256)
FEATURE_EXTRACTOR: ResNet50Conv5ROIFeatureExtractor
KE_WEIGHT: 1.0
MTY_WEIGHT: 1.0
NUM_KES: 10
NUM_MATCHTYPE: 24
POOLER_RESOLUTION: 14
POOLER_SAMPLING_RATIO: 0
POOLER_SCALES: (0.0625,)
POSTPROCESS_KES: False
POSTPROCESS_KES_THRESHOLD: 0.5
PREDICTOR: KERCNNC4Predictor
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_DFPOOL: False
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_PER_BATCH: True
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
WEIGHT: /data/pretrained/pytorch/fcos/FCOS_R_50_FPN_1x.pth
YOLACT:
HEAD_NUM_CONVS: 2
MASKS_PROTO_CROP: False
MASKS_TO_TRAIN: 100
MASK_PROTO_SRC: 0
MASK_TYPE: lincomb
NUM_PROTOS: 32
PRIOR_PROB: 0.01
PROTO_ACTIVATION: sigmoid
PROTO_NUM_CONVS: 4
SHARE_CLS_TOWER: True
OUTPUT_DIR: .
PATHS_CATALOG: /workspace/git/hao-fcos/maskrcnn_benchmark/config/paths_catalog.py
PROCESS:
NMS_THRESH: 0.4
PNMS: False
SOLVER:
BASE_LR: 0.01
BIAS_LR_FACTOR: 2
CHECKPOINT_PERIOD: 2500
GAMMA: 0.1
IMS_PER_BATCH: 16
MAX_ITER: 90000
MOMENTUM: 0.9
ONE_STAGE_MASK_LR_FACTOR: 10.0
STEPS: (60000, 80000)
WARMUP_FACTOR: 0.3333333333333333
WARMUP_ITERS: 500
WARMUP_METHOD: constant
WEIGHT_DECAY: 0.0001
WEIGHT_DECAY_BIAS: 0
SYNCBN: False
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: 1
2019-08-09 03:28:47,301 maskrcnn_benchmark INFO: Collecting env info (might take some time)
2019-08-09 03:28:48,378 maskrcnn_benchmark INFO:
PyTorch version: 1.0.1.post2
Is debug build: No
CUDA used to build PyTorch: 9.0.176

OS: CentOS Linux release 7.6.1810 (Core)
GCC version: (GCC) 5.3.1 20160406 (Red Hat 5.3.1-6)
CMake version: version 3.6.2

Python version: 3.6
Is CUDA available: Yes
CUDA runtime version: 9.0.176
GPU models and configuration: GPU 0: GeForce GTX 1070
Nvidia driver version: 418.56
cuDNN version: Could not collect

Versions of relevant libraries:
[pip] Could not collect
[conda] Could not collect
Pillow (6.0.0)
2019-08-09 03:28:51,679 maskrcnn_benchmark.utils.checkpoint INFO: Loading checkpoint from /data/pretrained/pytorch/fcos/FCOS_R_50_FPN_1x.pth
2019-08-09 03:28:51,751 maskrcnn_benchmark.utils.model_serialization INFO: backbone.body.layer1.0.bn1.bias loaded from backbone.body.layer1.0.bn1.bias of shape (64,)
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2019-08-09 03:28:51,752 maskrcnn_benchmark.utils.model_serialization INFO: backbone.body.layer1.0.bn1.running_var loaded from backbone.body.layer1.0.bn1.running_var of shape (64,)
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2019-08-09 03:28:51,752 maskrcnn_benchmark.utils.model_serialization INFO: backbone.body.layer1.0.bn2.bias loaded from backbone.body.layer1.0.bn2.bias of shape (64,)
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2019-08-09 03:28:51,752 maskrcnn_benchmark.utils.model_serialization INFO: backbone.body.layer1.0.bn2.running_var loaded from backbone.body.layer1.0.bn2.running_var of shape (64,)
2019-08-09 03:28:51,752 maskrcnn_benchmark.utils.model_serialization INFO: backbone.body.layer1.0.bn2.weight loaded from backbone.body.layer1.0.bn2.weight of shape (64,)
2019-08-09 03:28:51,752 maskrcnn_benchmark.utils.model_serialization INFO: backbone.body.layer1.0.bn3.bias loaded from backbone.body.layer1.0.bn3.bias of shape (256,)
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2019-08-09 03:28:51,752 maskrcnn_benchmark.utils.model_serialization INFO: backbone.body.layer1.0.bn3.running_var loaded from backbone.body.layer1.0.bn3.running_var of shape (256,)
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2019-08-09 03:28:51,753 maskrcnn_benchmark.utils.model_serialization INFO: backbone.body.layer1.0.conv3.weight loaded from backbone.body.layer1.0.conv3.weight of shape (256, 64, 1, 1)
2019-08-09 03:28:51,753 maskrcnn_benchmark.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)
2019-08-09 03:28:51,753 maskrcnn_benchmark.utils.model_serialization INFO: backbone.body.layer1.0.downsample.1.bias loaded from backbone.body.layer1.0.downsample.1.bias of shape (256,)
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2019-08-09 03:28:51,753 maskrcnn_benchmark.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,)
2019-08-09 03:28:51,753 maskrcnn_benchmark.utils.model_serialization INFO: backbone.body.layer1.0.downsample.1.weight loaded from backbone.body.layer1.0.downsample.1.weight of shape (256,)
2019-08-09 03:28:51,753 maskrcnn_benchmark.utils.model_serialization INFO: backbone.body.layer1.1.bn1.bias loaded from backbone.body.layer1.1.bn1.bias of shape (64,)
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loading annotations into memory…
Traceback (most recent call last):
File “tools/test_net.py”, line 115, in main() File "tools/test_net.py", line 98, in main data_loaders_val = make_data_loader(cfg, is_train=False, is_distributed=distributed) File "/workspace/git/hao-fcos/maskrcnn_benchmark/data/build.py", line 162, in make_data_loader cfg) File "/workspace/git/hao-fcos/maskrcnn_benchmark/data/build.py", line 50, in build_dataset dataset = factory(**args) File "/workspace/git/hao-fcos/maskrcnn_benchmark/data/datasets/coco.py", line 49, in __init__ super(COCODataset, self).__init__(root, ann_file) File "/home/chenp/.pyenv/versions/3.6.8/lib/python3.6/site-packages/torchvision/datasets/coco.py", line 97, in __init__ self.coco = COCO(annFile) File "/home/chenp/.pyenv/versions/3.6.8/lib/python3.6/site-packages/pycocotools/coco.py", line 84, in __init__ dataset = json.load(open(annotation_file, 'r')) FileNotFoundError: [Errno 2] No such file or directory: 'datasets/coco/annotations/instances_val2017.json'