deep-high-resolution-net.pytorch
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Segmentation fault (core dumped) after main() returned in tools/test.py
I am currently running the following sample script on a Ubuntu 18.04.4 LTS AMD Ryzen 3920x machine with 24 physical cores and 3 GPUs, all detected by pytorch:
python3 tools/test.py --cfg experiments/mpii/hrnet/w32_256x256_adam_lr1e-3.yaml TEST.MODEL_FILE models/pytorch/pose_mpii/pose_hrnet_w32_256x256.pth
I have adjusted the configuration file to test with a batch size of 8 per GPU so it consumes less memory, and here is the output:
=> creating output/mpii/pose_hrnet/w32_256x256_adam_lr1e-3
=> creating log/mpii/pose_hrnet/w32_256x256_adam_lr1e-3_2021-08-24-18-48
Namespace(cfg='experiments/mpii/hrnet/w32_256x256_adam_lr1e-3.yaml', dataDir='', logDir='', modelDir='', opts=['TEST.MODEL_FILE', 'models/pytorch/pose_mpii/pose_hrnet_w32_256x256.pth'], prevModelDir='')
AUTO_RESUME: True
CUDNN:
BENCHMARK: True
DETERMINISTIC: False
ENABLED: True
DATASET:
COLOR_RGB: True
DATASET: mpii
DATA_FORMAT: jpg
FLIP: True
HYBRID_JOINTS_TYPE:
NUM_JOINTS_HALF_BODY: 8
PROB_HALF_BODY: -1.0
ROOT: data/mpii/
ROT_FACTOR: 30
SCALE_FACTOR: 0.25
SELECT_DATA: False
TEST_SET: valid
TRAIN_SET: train
DATA_DIR:
DEBUG:
DEBUG: True
SAVE_BATCH_IMAGES_GT: True
SAVE_BATCH_IMAGES_PRED: True
SAVE_HEATMAPS_GT: True
SAVE_HEATMAPS_PRED: True
GPUS: (0, 1, 2)
LOG_DIR: log
LOSS:
TOPK: 8
USE_DIFFERENT_JOINTS_WEIGHT: False
USE_OHKM: False
USE_TARGET_WEIGHT: True
MODEL:
EXTRA:
FINAL_CONV_KERNEL: 1
PRETRAINED_LAYERS: ['conv1', 'bn1', 'conv2', 'bn2', 'layer1', 'transition1', 'stage2', 'transition2', 'stage3', 'transition3', 'stage4']
STAGE2:
BLOCK: BASIC
FUSE_METHOD: SUM
NUM_BLOCKS: [4, 4]
NUM_BRANCHES: 2
NUM_CHANNELS: [32, 64]
NUM_MODULES: 1
STAGE3:
BLOCK: BASIC
FUSE_METHOD: SUM
NUM_BLOCKS: [4, 4, 4]
NUM_BRANCHES: 3
NUM_CHANNELS: [32, 64, 128]
NUM_MODULES: 4
STAGE4:
BLOCK: BASIC
FUSE_METHOD: SUM
NUM_BLOCKS: [4, 4, 4, 4]
NUM_BRANCHES: 4
NUM_CHANNELS: [32, 64, 128, 256]
NUM_MODULES: 3
HEATMAP_SIZE: [64, 64]
IMAGE_SIZE: [256, 256]
INIT_WEIGHTS: True
NAME: pose_hrnet
NUM_JOINTS: 16
PRETRAINED: models/pytorch/imagenet/hrnet_w32-36af842e.pth
SIGMA: 2
TAG_PER_JOINT: True
TARGET_TYPE: gaussian
OUTPUT_DIR: output
PIN_MEMORY: True
PRINT_FREQ: 100
RANK: 0
TEST:
BATCH_SIZE_PER_GPU: 8
BBOX_THRE: 1.0
COCO_BBOX_FILE:
FLIP_TEST: True
IMAGE_THRE: 0.1
IN_VIS_THRE: 0.0
MODEL_FILE: models/pytorch/pose_mpii/pose_hrnet_w32_256x256.pth
NMS_THRE: 0.6
OKS_THRE: 0.5
POST_PROCESS: True
SHIFT_HEATMAP: True
SOFT_NMS: False
USE_GT_BBOX: False
TRAIN:
BATCH_SIZE_PER_GPU: 8
BEGIN_EPOCH: 0
CHECKPOINT:
END_EPOCH: 210
GAMMA1: 0.99
GAMMA2: 0.0
LR: 0.001
LR_FACTOR: 0.1
LR_STEP: [170, 200]
MOMENTUM: 0.9
NESTEROV: False
OPTIMIZER: adam
RESUME: False
SHUFFLE: True
WD: 0.0001
WORKERS: 24
=> loading model from models/pytorch/pose_mpii/pose_hrnet_w32_256x256.pth
/home/aaron/anaconda3/envs/pytorch_env/lib/python3.8/site-packages/json_tricks/nonp.py:221: JsonTricksDeprecation: `json_tricks.load(s)` stripped some comments, but `ignore_comments` was not passed; in the next major release, the behaviour when `ignore_comments` is not passed will change; it is recommended to explicitly pass `ignore_comments=True` if you want to strip comments; see https://github.com/mverleg/pyjson_tricks/issues/74
warnings.warn('`json_tricks.load(s)` stripped some comments, but `ignore_comments` was '
=> load 2958 samples
Test: [0/124] Time 5.269 (5.269) Loss 0.0003 (0.0003) Accuracy 0.959 (0.959)
Test: [100/124] Time 0.362 (0.451) Loss 0.0004 (0.0004) Accuracy 0.880 (0.914)
| Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mean | [email protected] |
|---|---|---|---|---|---|---|---|---|---|
| pose_hrnet | 97.101 | 95.941 | 90.336 | 86.449 | 89.095 | 87.084 | 83.278 | 90.330 | 37.702 |
Segmentation fault (core dumped)
As per the change in title, the Segmentation fault (core dumped) statement was printed after the validate() function has finished running, for both the coco and mpii dataset.
did you solve this problem?
@WaiTsun-Yeung can you share the dependencies versions that you installed to run the test script please. Thanks