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View Code? Open in Web Editor NEWCode for CVPR 2021 paper: Anchor-Free Person Search
License: Apache License 2.0
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baodijun chaoso tragedyn lynn294555 hxl1990 xrosliang firmamentqj jaybdub dangweili cvlinks aureliuspatiens charleschen24 waterbearbee songbaihust jie311 zhangleilei0125 opentld judgepazair cv-ip dongryeolee djever23 liviust alvahan kiwiap xixirupan feboreigns zqx951102 vaibhavsundharam polivares dufolk aj1143208 chaiyanchong peterzsalignps's Issues
Visualization of deformable conv
Hello, I wonder how to visualize the offset of deformable conv? Could you offer a demo code?
Confused about the 'regress_ranges' in fcos_reid_head.py
Thank you for your nice work!
I'm confused about the 'regress_ranges' in fcos_reid_head.py. It is set as ((-1, INF), (-2, -1), (-2, -1), (-2, -1), (-2, -1)). In other words, although the output contains {P3, P4, P5, P6, P6, P7}, the others have no effect except P3? Is it the same as 'regress_ranges = ((-1, INF),)'? Are there any other settings related to the design of learning features only from P3?
I really can't figure this out. Thanks for your answers!
error when installing mmcv
Thanks for your error report and we appreciate it a lot.
Checklist
- I have searched related issues but cannot get the expected help.
- The bug has not been fixed in the latest version.
Describe the bug
A clear and concise description of what the bug is.
Reproduction
- What command or script did you run?
pip install mmcv-full==1.1.5 -f https://download.openmmlab.com/mmcv/dist/cu101/torch1.7.0/index.html
- Did you make any modifications on the code or config? Did you understand what you have modified?
- What dataset did you use?
Environment
Ubuntu 20.04.1
GeForce GTX 1080 Ti
nvidia driver: 460.56
pytorch: 1.7.0
cuda: 10.1
cudnn: 7.6.5
gcc version: 7.5.0
g++ version 7.5.0
Error traceback
If applicable, paste the error trackback here.
Building wheel for mmcv-full (setup.py) ... error
ERROR: Command errored out with exit status 1:
command: /home/ajay/anaconda3/envs/AlignPS/bin/python -u -c 'import sys, setuptools, tokenize; sys.argv[0] = '"'"'/tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/setup.py'"'"'; __file__='"'"'/tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/setup.py'"'"';f=getattr(tokenize, '"'"'open'"'"', open)(__file__);code=f.read().replace('"'"'\r\n'"'"', '"'"'\n'"'"');f.close();exec(compile(code, __file__, '"'"'exec'"'"'))' bdist_wheel -d /tmp/pip-wheel-2hoh9h7m
cwd: /tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/
Complete output (414 lines):
running bdist_wheel
running build
running build_py
creating build
creating build/lib.linux-x86_64-3.7
creating build/lib.linux-x86_64-3.7/mmcv
copying mmcv/version.py -> build/lib.linux-x86_64-3.7/mmcv
copying mmcv/__init__.py -> build/lib.linux-x86_64-3.7/mmcv
creating build/lib.linux-x86_64-3.7/mmcv/ops
copying mmcv/ops/roi_pool.py -> build/lib.linux-x86_64-3.7/mmcv/ops
copying mmcv/ops/cc_attention.py -> build/lib.linux-x86_64-3.7/mmcv/ops
copying mmcv/ops/deprecated_wrappers.py -> build/lib.linux-x86_64-3.7/mmcv/ops
copying mmcv/ops/focal_loss.py -> build/lib.linux-x86_64-3.7/mmcv/ops
copying mmcv/ops/sync_bn.py -> build/lib.linux-x86_64-3.7/mmcv/ops
copying mmcv/ops/carafe.py -> build/lib.linux-x86_64-3.7/mmcv/ops
copying mmcv/ops/saconv.py -> build/lib.linux-x86_64-3.7/mmcv/ops
copying mmcv/ops/roi_align.py -> build/lib.linux-x86_64-3.7/mmcv/ops
copying mmcv/ops/merge_cells.py -> build/lib.linux-x86_64-3.7/mmcv/ops
copying mmcv/ops/deform_conv.py -> build/lib.linux-x86_64-3.7/mmcv/ops
copying mmcv/ops/__init__.py -> build/lib.linux-x86_64-3.7/mmcv/ops
copying mmcv/ops/bbox.py -> build/lib.linux-x86_64-3.7/mmcv/ops
copying mmcv/ops/tin_shift.py -> build/lib.linux-x86_64-3.7/mmcv/ops
copying mmcv/ops/nms.py -> build/lib.linux-x86_64-3.7/mmcv/ops
copying mmcv/ops/psa_mask.py -> build/lib.linux-x86_64-3.7/mmcv/ops
copying mmcv/ops/deform_roi_pool.py -> build/lib.linux-x86_64-3.7/mmcv/ops
copying mmcv/ops/masked_conv.py -> build/lib.linux-x86_64-3.7/mmcv/ops
copying mmcv/ops/point_sample.py -> build/lib.linux-x86_64-3.7/mmcv/ops
copying mmcv/ops/corner_pool.py -> build/lib.linux-x86_64-3.7/mmcv/ops
copying mmcv/ops/modulated_deform_conv.py -> build/lib.linux-x86_64-3.7/mmcv/ops
copying mmcv/ops/info.py -> build/lib.linux-x86_64-3.7/mmcv/ops
creating build/lib.linux-x86_64-3.7/mmcv/fileio
copying mmcv/fileio/__init__.py -> build/lib.linux-x86_64-3.7/mmcv/fileio
copying mmcv/fileio/parse.py -> build/lib.linux-x86_64-3.7/mmcv/fileio
copying mmcv/fileio/io.py -> build/lib.linux-x86_64-3.7/mmcv/fileio
copying mmcv/fileio/file_client.py -> build/lib.linux-x86_64-3.7/mmcv/fileio
creating build/lib.linux-x86_64-3.7/mmcv/runner
copying mmcv/runner/log_buffer.py -> build/lib.linux-x86_64-3.7/mmcv/runner
copying mmcv/runner/dist_utils.py -> build/lib.linux-x86_64-3.7/mmcv/runner
copying mmcv/runner/iter_based_runner.py -> build/lib.linux-x86_64-3.7/mmcv/runner
copying mmcv/runner/__init__.py -> build/lib.linux-x86_64-3.7/mmcv/runner
copying mmcv/runner/epoch_based_runner.py -> build/lib.linux-x86_64-3.7/mmcv/runner
copying mmcv/runner/priority.py -> build/lib.linux-x86_64-3.7/mmcv/runner
copying mmcv/runner/utils.py -> build/lib.linux-x86_64-3.7/mmcv/runner
copying mmcv/runner/builder.py -> build/lib.linux-x86_64-3.7/mmcv/runner
copying mmcv/runner/checkpoint.py -> build/lib.linux-x86_64-3.7/mmcv/runner
copying mmcv/runner/fp16_utils.py -> build/lib.linux-x86_64-3.7/mmcv/runner
copying mmcv/runner/base_runner.py -> build/lib.linux-x86_64-3.7/mmcv/runner
creating build/lib.linux-x86_64-3.7/mmcv/image
copying mmcv/image/geometric.py -> build/lib.linux-x86_64-3.7/mmcv/image
copying mmcv/image/colorspace.py -> build/lib.linux-x86_64-3.7/mmcv/image
copying mmcv/image/photometric.py -> build/lib.linux-x86_64-3.7/mmcv/image
copying mmcv/image/__init__.py -> build/lib.linux-x86_64-3.7/mmcv/image
copying mmcv/image/io.py -> build/lib.linux-x86_64-3.7/mmcv/image
copying mmcv/image/misc.py -> build/lib.linux-x86_64-3.7/mmcv/image
creating build/lib.linux-x86_64-3.7/mmcv/utils
copying mmcv/utils/config.py -> build/lib.linux-x86_64-3.7/mmcv/utils
copying mmcv/utils/version_utils.py -> build/lib.linux-x86_64-3.7/mmcv/utils
copying mmcv/utils/__init__.py -> build/lib.linux-x86_64-3.7/mmcv/utils
copying mmcv/utils/timer.py -> build/lib.linux-x86_64-3.7/mmcv/utils
copying mmcv/utils/logging.py -> build/lib.linux-x86_64-3.7/mmcv/utils
copying mmcv/utils/env.py -> build/lib.linux-x86_64-3.7/mmcv/utils
copying mmcv/utils/progressbar.py -> build/lib.linux-x86_64-3.7/mmcv/utils
copying mmcv/utils/ext_loader.py -> build/lib.linux-x86_64-3.7/mmcv/utils
copying mmcv/utils/path.py -> build/lib.linux-x86_64-3.7/mmcv/utils
copying mmcv/utils/parrots_wrapper.py -> build/lib.linux-x86_64-3.7/mmcv/utils
copying mmcv/utils/misc.py -> build/lib.linux-x86_64-3.7/mmcv/utils
copying mmcv/utils/registry.py -> build/lib.linux-x86_64-3.7/mmcv/utils
creating build/lib.linux-x86_64-3.7/mmcv/parallel
copying mmcv/parallel/data_parallel.py -> build/lib.linux-x86_64-3.7/mmcv/parallel
copying mmcv/parallel/data_container.py -> build/lib.linux-x86_64-3.7/mmcv/parallel
copying mmcv/parallel/_functions.py -> build/lib.linux-x86_64-3.7/mmcv/parallel
copying mmcv/parallel/__init__.py -> build/lib.linux-x86_64-3.7/mmcv/parallel
copying mmcv/parallel/collate.py -> build/lib.linux-x86_64-3.7/mmcv/parallel
copying mmcv/parallel/distributed_deprecated.py -> build/lib.linux-x86_64-3.7/mmcv/parallel
copying mmcv/parallel/distributed.py -> build/lib.linux-x86_64-3.7/mmcv/parallel
copying mmcv/parallel/utils.py -> build/lib.linux-x86_64-3.7/mmcv/parallel
copying mmcv/parallel/registry.py -> build/lib.linux-x86_64-3.7/mmcv/parallel
copying mmcv/parallel/scatter_gather.py -> build/lib.linux-x86_64-3.7/mmcv/parallel
creating build/lib.linux-x86_64-3.7/mmcv/cnn
copying mmcv/cnn/resnet.py -> build/lib.linux-x86_64-3.7/mmcv/cnn
copying mmcv/cnn/vgg.py -> build/lib.linux-x86_64-3.7/mmcv/cnn
copying mmcv/cnn/__init__.py -> build/lib.linux-x86_64-3.7/mmcv/cnn
copying mmcv/cnn/alexnet.py -> build/lib.linux-x86_64-3.7/mmcv/cnn
creating build/lib.linux-x86_64-3.7/mmcv/video
copying mmcv/video/processing.py -> build/lib.linux-x86_64-3.7/mmcv/video
copying mmcv/video/__init__.py -> build/lib.linux-x86_64-3.7/mmcv/video
copying mmcv/video/io.py -> build/lib.linux-x86_64-3.7/mmcv/video
copying mmcv/video/optflow.py -> build/lib.linux-x86_64-3.7/mmcv/video
creating build/lib.linux-x86_64-3.7/mmcv/visualization
copying mmcv/visualization/image.py -> build/lib.linux-x86_64-3.7/mmcv/visualization
copying mmcv/visualization/__init__.py -> build/lib.linux-x86_64-3.7/mmcv/visualization
copying mmcv/visualization/color.py -> build/lib.linux-x86_64-3.7/mmcv/visualization
copying mmcv/visualization/optflow.py -> build/lib.linux-x86_64-3.7/mmcv/visualization
creating build/lib.linux-x86_64-3.7/mmcv/arraymisc
copying mmcv/arraymisc/__init__.py -> build/lib.linux-x86_64-3.7/mmcv/arraymisc
copying mmcv/arraymisc/quantization.py -> build/lib.linux-x86_64-3.7/mmcv/arraymisc
creating build/lib.linux-x86_64-3.7/mmcv/onnx
copying mmcv/onnx/__init__.py -> build/lib.linux-x86_64-3.7/mmcv/onnx
copying mmcv/onnx/symbolic.py -> build/lib.linux-x86_64-3.7/mmcv/onnx
creating build/lib.linux-x86_64-3.7/mmcv/fileio/handlers
copying mmcv/fileio/handlers/yaml_handler.py -> build/lib.linux-x86_64-3.7/mmcv/fileio/handlers
copying mmcv/fileio/handlers/base.py -> build/lib.linux-x86_64-3.7/mmcv/fileio/handlers
copying mmcv/fileio/handlers/json_handler.py -> build/lib.linux-x86_64-3.7/mmcv/fileio/handlers
copying mmcv/fileio/handlers/__init__.py -> build/lib.linux-x86_64-3.7/mmcv/fileio/handlers
copying mmcv/fileio/handlers/pickle_handler.py -> build/lib.linux-x86_64-3.7/mmcv/fileio/handlers
creating build/lib.linux-x86_64-3.7/mmcv/runner/hooks
copying mmcv/runner/hooks/iter_timer.py -> build/lib.linux-x86_64-3.7/mmcv/runner/hooks
copying mmcv/runner/hooks/sampler_seed.py -> build/lib.linux-x86_64-3.7/mmcv/runner/hooks
copying mmcv/runner/hooks/optimizer.py -> build/lib.linux-x86_64-3.7/mmcv/runner/hooks
copying mmcv/runner/hooks/momentum_updater.py -> build/lib.linux-x86_64-3.7/mmcv/runner/hooks
copying mmcv/runner/hooks/__init__.py -> build/lib.linux-x86_64-3.7/mmcv/runner/hooks
copying mmcv/runner/hooks/ema.py -> build/lib.linux-x86_64-3.7/mmcv/runner/hooks
copying mmcv/runner/hooks/sync_buffer.py -> build/lib.linux-x86_64-3.7/mmcv/runner/hooks
copying mmcv/runner/hooks/hook.py -> build/lib.linux-x86_64-3.7/mmcv/runner/hooks
copying mmcv/runner/hooks/checkpoint.py -> build/lib.linux-x86_64-3.7/mmcv/runner/hooks
copying mmcv/runner/hooks/memory.py -> build/lib.linux-x86_64-3.7/mmcv/runner/hooks
copying mmcv/runner/hooks/closure.py -> build/lib.linux-x86_64-3.7/mmcv/runner/hooks
copying mmcv/runner/hooks/lr_updater.py -> build/lib.linux-x86_64-3.7/mmcv/runner/hooks
creating build/lib.linux-x86_64-3.7/mmcv/runner/optimizer
copying mmcv/runner/optimizer/__init__.py -> build/lib.linux-x86_64-3.7/mmcv/runner/optimizer
copying mmcv/runner/optimizer/default_constructor.py -> build/lib.linux-x86_64-3.7/mmcv/runner/optimizer
copying mmcv/runner/optimizer/builder.py -> build/lib.linux-x86_64-3.7/mmcv/runner/optimizer
creating build/lib.linux-x86_64-3.7/mmcv/runner/hooks/logger
copying mmcv/runner/hooks/logger/pavi.py -> build/lib.linux-x86_64-3.7/mmcv/runner/hooks/logger
copying mmcv/runner/hooks/logger/wandb.py -> build/lib.linux-x86_64-3.7/mmcv/runner/hooks/logger
copying mmcv/runner/hooks/logger/base.py -> build/lib.linux-x86_64-3.7/mmcv/runner/hooks/logger
copying mmcv/runner/hooks/logger/tensorboard.py -> build/lib.linux-x86_64-3.7/mmcv/runner/hooks/logger
copying mmcv/runner/hooks/logger/mlflow.py -> build/lib.linux-x86_64-3.7/mmcv/runner/hooks/logger
copying mmcv/runner/hooks/logger/__init__.py -> build/lib.linux-x86_64-3.7/mmcv/runner/hooks/logger
copying mmcv/runner/hooks/logger/text.py -> build/lib.linux-x86_64-3.7/mmcv/runner/hooks/logger
creating build/lib.linux-x86_64-3.7/mmcv/cnn/bricks
copying mmcv/cnn/bricks/generalized_attention.py -> build/lib.linux-x86_64-3.7/mmcv/cnn/bricks
copying mmcv/cnn/bricks/conv.py -> build/lib.linux-x86_64-3.7/mmcv/cnn/bricks
copying mmcv/cnn/bricks/context_block.py -> build/lib.linux-x86_64-3.7/mmcv/cnn/bricks
copying mmcv/cnn/bricks/conv2d_adaptive_padding.py -> build/lib.linux-x86_64-3.7/mmcv/cnn/bricks
copying mmcv/cnn/bricks/conv_module.py -> build/lib.linux-x86_64-3.7/mmcv/cnn/bricks
copying mmcv/cnn/bricks/padding.py -> build/lib.linux-x86_64-3.7/mmcv/cnn/bricks
copying mmcv/cnn/bricks/non_local.py -> build/lib.linux-x86_64-3.7/mmcv/cnn/bricks
copying mmcv/cnn/bricks/norm.py -> build/lib.linux-x86_64-3.7/mmcv/cnn/bricks
copying mmcv/cnn/bricks/__init__.py -> build/lib.linux-x86_64-3.7/mmcv/cnn/bricks
copying mmcv/cnn/bricks/hswish.py -> build/lib.linux-x86_64-3.7/mmcv/cnn/bricks
copying mmcv/cnn/bricks/conv_ws.py -> build/lib.linux-x86_64-3.7/mmcv/cnn/bricks
copying mmcv/cnn/bricks/wrappers.py -> build/lib.linux-x86_64-3.7/mmcv/cnn/bricks
copying mmcv/cnn/bricks/activation.py -> build/lib.linux-x86_64-3.7/mmcv/cnn/bricks
copying mmcv/cnn/bricks/depthwise_separable_conv_module.py -> build/lib.linux-x86_64-3.7/mmcv/cnn/bricks
copying mmcv/cnn/bricks/plugin.py -> build/lib.linux-x86_64-3.7/mmcv/cnn/bricks
copying mmcv/cnn/bricks/hsigmoid.py -> build/lib.linux-x86_64-3.7/mmcv/cnn/bricks
copying mmcv/cnn/bricks/swish.py -> build/lib.linux-x86_64-3.7/mmcv/cnn/bricks
copying mmcv/cnn/bricks/registry.py -> build/lib.linux-x86_64-3.7/mmcv/cnn/bricks
copying mmcv/cnn/bricks/upsample.py -> build/lib.linux-x86_64-3.7/mmcv/cnn/bricks
copying mmcv/cnn/bricks/scale.py -> build/lib.linux-x86_64-3.7/mmcv/cnn/bricks
creating build/lib.linux-x86_64-3.7/mmcv/cnn/utils
copying mmcv/cnn/utils/fuse_conv_bn.py -> build/lib.linux-x86_64-3.7/mmcv/cnn/utils
copying mmcv/cnn/utils/__init__.py -> build/lib.linux-x86_64-3.7/mmcv/cnn/utils
copying mmcv/cnn/utils/weight_init.py -> build/lib.linux-x86_64-3.7/mmcv/cnn/utils
copying mmcv/cnn/utils/flops_counter.py -> build/lib.linux-x86_64-3.7/mmcv/cnn/utils
creating build/lib.linux-x86_64-3.7/mmcv/video/optflow_warp
copying mmcv/video/optflow_warp/__init__.py -> build/lib.linux-x86_64-3.7/mmcv/video/optflow_warp
creating build/lib.linux-x86_64-3.7/mmcv/onnx/onnx_utils
copying mmcv/onnx/onnx_utils/__init__.py -> build/lib.linux-x86_64-3.7/mmcv/onnx/onnx_utils
copying mmcv/onnx/onnx_utils/symbolic_helper.py -> build/lib.linux-x86_64-3.7/mmcv/onnx/onnx_utils
running egg_info
writing mmcv_full.egg-info/PKG-INFO
writing dependency_links to mmcv_full.egg-info/dependency_links.txt
writing requirements to mmcv_full.egg-info/requires.txt
writing top-level names to mmcv_full.egg-info/top_level.txt
reading manifest file 'mmcv_full.egg-info/SOURCES.txt'
reading manifest template 'MANIFEST.in'
writing manifest file 'mmcv_full.egg-info/SOURCES.txt'
creating build/lib.linux-x86_64-3.7/mmcv/model_zoo
copying mmcv/model_zoo/deprecated.json -> build/lib.linux-x86_64-3.7/mmcv/model_zoo
copying mmcv/model_zoo/mmcls.json -> build/lib.linux-x86_64-3.7/mmcv/model_zoo
copying mmcv/model_zoo/open_mmlab.json -> build/lib.linux-x86_64-3.7/mmcv/model_zoo
creating build/lib.linux-x86_64-3.7/mmcv/ops/csrc
copying mmcv/ops/csrc/bbox_overlaps_cuda_kernel.cuh -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc
copying mmcv/ops/csrc/carafe_cuda_kernel.cuh -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc
copying mmcv/ops/csrc/carafe_naive_cuda_kernel.cuh -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc
copying mmcv/ops/csrc/cc_attention_cuda_kernel.cuh -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc
copying mmcv/ops/csrc/common_cuda_helper.hpp -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc
copying mmcv/ops/csrc/deform_conv_cuda_kernel.cuh -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc
copying mmcv/ops/csrc/deform_roi_pool_cuda_kernel.cuh -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc
copying mmcv/ops/csrc/masked_conv2d_cuda_kernel.cuh -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc
copying mmcv/ops/csrc/modulated_deform_conv_cuda_kernel.cuh -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc
copying mmcv/ops/csrc/nms_cuda_kernel.cuh -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc
copying mmcv/ops/csrc/parrots_cpp_helper.hpp -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc
copying mmcv/ops/csrc/parrots_cuda_helper.hpp -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc
copying mmcv/ops/csrc/parrots_cudawarpfunction.cuh -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc
copying mmcv/ops/csrc/psamask_cuda_kernel.cuh -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc
copying mmcv/ops/csrc/pytorch_cpp_helper.hpp -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc
copying mmcv/ops/csrc/pytorch_cuda_helper.hpp -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc
copying mmcv/ops/csrc/roi_align_cuda_kernel.cuh -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc
copying mmcv/ops/csrc/roi_pool_cuda_kernel.cuh -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc
copying mmcv/ops/csrc/sigmoid_focal_loss_cuda_kernel.cuh -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc
copying mmcv/ops/csrc/softmax_focal_loss_cuda_kernel.cuh -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc
copying mmcv/ops/csrc/sync_bn_cuda_kernel.cuh -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc
copying mmcv/ops/csrc/tin_shift_cuda_kernel.cuh -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc
creating build/lib.linux-x86_64-3.7/mmcv/ops/csrc/parrots
copying mmcv/ops/csrc/parrots/bbox_overlaps.cpp -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/parrots
copying mmcv/ops/csrc/parrots/bbox_overlaps_cuda.cu -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/parrots
copying mmcv/ops/csrc/parrots/carafe.cpp -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/parrots
copying mmcv/ops/csrc/parrots/carafe_cuda.cu -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/parrots
copying mmcv/ops/csrc/parrots/carafe_naive.cpp -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/parrots
copying mmcv/ops/csrc/parrots/carafe_naive_cuda.cu -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/parrots
copying mmcv/ops/csrc/parrots/cc_attention.cpp -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/parrots
copying mmcv/ops/csrc/parrots/cc_attention_cuda_kernel.cu -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/parrots
copying mmcv/ops/csrc/parrots/corner_pool.cpp -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/parrots
copying mmcv/ops/csrc/parrots/deform_conv.cpp -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/parrots
copying mmcv/ops/csrc/parrots/deform_conv_cuda.cu -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/parrots
copying mmcv/ops/csrc/parrots/deform_roi_pool.cpp -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/parrots
copying mmcv/ops/csrc/parrots/deform_roi_pool_cuda.cu -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/parrots
copying mmcv/ops/csrc/parrots/focal_loss.cpp -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/parrots
copying mmcv/ops/csrc/parrots/focal_loss_cuda.cu -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/parrots
copying mmcv/ops/csrc/parrots/masked_conv2d.cpp -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/parrots
copying mmcv/ops/csrc/parrots/masked_conv2d_cuda.cu -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/parrots
copying mmcv/ops/csrc/parrots/modulated_deform_conv.cpp -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/parrots
copying mmcv/ops/csrc/parrots/modulated_deform_conv_cuda.cu -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/parrots
copying mmcv/ops/csrc/parrots/nms.cpp -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/parrots
copying mmcv/ops/csrc/parrots/nms_cuda.cu -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/parrots
copying mmcv/ops/csrc/parrots/parrots_cpp_helper.cpp -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/parrots
copying mmcv/ops/csrc/parrots/parrots_cuda_helper.cu -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/parrots
copying mmcv/ops/csrc/parrots/psamask.cpp -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/parrots
copying mmcv/ops/csrc/parrots/psamask_cuda.cu -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/parrots
copying mmcv/ops/csrc/parrots/roi_align.cpp -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/parrots
copying mmcv/ops/csrc/parrots/roi_align_cuda.cu -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/parrots
copying mmcv/ops/csrc/parrots/roi_pool.cpp -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/parrots
copying mmcv/ops/csrc/parrots/roi_pool_cuda.cu -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/parrots
copying mmcv/ops/csrc/parrots/sync_bn.cpp -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/parrots
copying mmcv/ops/csrc/parrots/sync_bn_cuda.cu -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/parrots
copying mmcv/ops/csrc/parrots/tin_shift.cpp -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/parrots
copying mmcv/ops/csrc/parrots/tin_shift_cuda.cu -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/parrots
creating build/lib.linux-x86_64-3.7/mmcv/ops/csrc/pytorch
copying mmcv/ops/csrc/pytorch/bbox_overlaps.cpp -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/pytorch
copying mmcv/ops/csrc/pytorch/bbox_overlaps_cuda.cu -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/pytorch
copying mmcv/ops/csrc/pytorch/carafe.cpp -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/pytorch
copying mmcv/ops/csrc/pytorch/carafe_cuda.cu -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/pytorch
copying mmcv/ops/csrc/pytorch/carafe_naive.cpp -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/pytorch
copying mmcv/ops/csrc/pytorch/carafe_naive_cuda.cu -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/pytorch
copying mmcv/ops/csrc/pytorch/cc_attention.cpp -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/pytorch
copying mmcv/ops/csrc/pytorch/cc_attention_cuda.cu -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/pytorch
copying mmcv/ops/csrc/pytorch/corner_pool.cpp -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/pytorch
copying mmcv/ops/csrc/pytorch/deform_conv.cpp -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/pytorch
copying mmcv/ops/csrc/pytorch/deform_conv_cuda.cu -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/pytorch
copying mmcv/ops/csrc/pytorch/deform_roi_pool.cpp -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/pytorch
copying mmcv/ops/csrc/pytorch/deform_roi_pool_cuda.cu -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/pytorch
copying mmcv/ops/csrc/pytorch/focal_loss.cpp -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/pytorch
copying mmcv/ops/csrc/pytorch/focal_loss_cuda.cu -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/pytorch
copying mmcv/ops/csrc/pytorch/info.cpp -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/pytorch
copying mmcv/ops/csrc/pytorch/masked_conv2d.cpp -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/pytorch
copying mmcv/ops/csrc/pytorch/masked_conv2d_cuda.cu -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/pytorch
copying mmcv/ops/csrc/pytorch/modulated_deform_conv.cpp -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/pytorch
copying mmcv/ops/csrc/pytorch/modulated_deform_conv_cuda.cu -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/pytorch
copying mmcv/ops/csrc/pytorch/nms.cpp -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/pytorch
copying mmcv/ops/csrc/pytorch/nms_cuda.cu -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/pytorch
copying mmcv/ops/csrc/pytorch/psamask.cpp -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/pytorch
copying mmcv/ops/csrc/pytorch/psamask_cuda.cu -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/pytorch
copying mmcv/ops/csrc/pytorch/pybind.cpp -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/pytorch
copying mmcv/ops/csrc/pytorch/roi_align.cpp -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/pytorch
copying mmcv/ops/csrc/pytorch/roi_align_cpu.cpp -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/pytorch
copying mmcv/ops/csrc/pytorch/roi_align_cuda.cu -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/pytorch
copying mmcv/ops/csrc/pytorch/roi_pool.cpp -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/pytorch
copying mmcv/ops/csrc/pytorch/roi_pool_cuda.cu -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/pytorch
copying mmcv/ops/csrc/pytorch/sync_bn.cpp -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/pytorch
copying mmcv/ops/csrc/pytorch/sync_bn_cuda.cu -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/pytorch
copying mmcv/ops/csrc/pytorch/tin_shift.cpp -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/pytorch
copying mmcv/ops/csrc/pytorch/tin_shift_cuda.cu -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/pytorch
copying mmcv/video/optflow_warp/flow_warp.hpp -> build/lib.linux-x86_64-3.7/mmcv/video/optflow_warp
copying mmcv/video/optflow_warp/flow_warp_module.pyx -> build/lib.linux-x86_64-3.7/mmcv/video/optflow_warp
running build_ext
building 'mmcv._flow_warp_ext' extension
creating /tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/build/temp.linux-x86_64-3.7
creating /tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/build/temp.linux-x86_64-3.7/mmcv
creating /tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/build/temp.linux-x86_64-3.7/mmcv/video
creating /tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/build/temp.linux-x86_64-3.7/mmcv/video/optflow_warp
Emitting ninja build file /tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/build/temp.linux-x86_64-3.7/build.ninja...
Compiling objects...
Using envvar MAX_JOBS (4) as the number of workers...
[1/2] c++ -MMD -MF /tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/build/temp.linux-x86_64-3.7/mmcv/video/optflow_warp/flow_warp.o.d -pthread -B /home/ajay/anaconda3/envs/AlignPS/compiler_compat -Wl,--sysroot=/ -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC -I./mmcv/video/optflow_warp -I/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/numpy/core/include -I/home/ajay/anaconda3/envs/AlignPS/include/python3.7m -c -c /tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/mmcv/video/optflow_warp/flow_warp.cpp -o /tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/build/temp.linux-x86_64-3.7/mmcv/video/optflow_warp/flow_warp.o -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=_flow_warp_ext -D_GLIBCXX_USE_CXX11_ABI=0 -std=c++14
cc1plus: warning: command line option ‘-Wstrict-prototypes’ is valid for C/ObjC but not for C++
[2/2] c++ -MMD -MF /tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/build/temp.linux-x86_64-3.7/mmcv/video/optflow_warp/flow_warp_module.o.d -pthread -B /home/ajay/anaconda3/envs/AlignPS/compiler_compat -Wl,--sysroot=/ -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC -I./mmcv/video/optflow_warp -I/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/numpy/core/include -I/home/ajay/anaconda3/envs/AlignPS/include/python3.7m -c -c /tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/mmcv/video/optflow_warp/flow_warp_module.cpp -o /tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/build/temp.linux-x86_64-3.7/mmcv/video/optflow_warp/flow_warp_module.o -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=_flow_warp_ext -D_GLIBCXX_USE_CXX11_ABI=0 -std=c++14
cc1plus: warning: command line option ‘-Wstrict-prototypes’ is valid for C/ObjC but not for C++
In file included from /home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/numpy/core/include/numpy/ndarraytypes.h:1822:0,
from /home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/numpy/core/include/numpy/ndarrayobject.h:12,
from /home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/numpy/core/include/numpy/arrayobject.h:4,
from /tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/mmcv/video/optflow_warp/flow_warp_module.cpp:647:
/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/numpy/core/include/numpy/npy_1_7_deprecated_api.h:17:2: warning: #warning "Using deprecated NumPy API, disable it with " "#define NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION" [-Wcpp]
#warning "Using deprecated NumPy API, disable it with " \
^~~~~~~
g++ -pthread -shared -B /home/ajay/anaconda3/envs/AlignPS/compiler_compat -L/home/ajay/anaconda3/envs/AlignPS/lib -Wl,-rpath=/home/ajay/anaconda3/envs/AlignPS/lib -Wl,--no-as-needed -Wl,--sysroot=/ /tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/build/temp.linux-x86_64-3.7/./mmcv/video/optflow_warp/flow_warp_module.o /tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/build/temp.linux-x86_64-3.7/./mmcv/video/optflow_warp/flow_warp.o -o build/lib.linux-x86_64-3.7/mmcv/_flow_warp_ext.cpython-37m-x86_64-linux-gnu.so
building 'mmcv._ext' extension
creating /tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/build/temp.linux-x86_64-3.7/mmcv/ops
creating /tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/build/temp.linux-x86_64-3.7/mmcv/ops/csrc
creating /tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/build/temp.linux-x86_64-3.7/mmcv/ops/csrc/pytorch
Emitting ninja build file /tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/build/temp.linux-x86_64-3.7/build.ninja...
Compiling objects...
Using envvar MAX_JOBS (4) as the number of workers...
[1/34] /usr/local/cuda/bin/nvcc -DMMCV_WITH_CUDA -I/tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/mmcv/ops/csrc -I/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/torch/include -I/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/torch/include/torch/csrc/api/include -I/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/torch/include/TH -I/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/torch/include/THC -I/usr/local/cuda/include -I/home/ajay/anaconda3/envs/AlignPS/include/python3.7m -c -c /tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/mmcv/ops/csrc/pytorch/roi_pool_cuda.cu -o /tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/build/temp.linux-x86_64-3.7/mmcv/ops/csrc/pytorch/roi_pool_cuda.o -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr --compiler-options ''"'"'-fPIC'"'"'' -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=_ext -D_GLIBCXX_USE_CXX11_ABI=0 -gencode=arch=compute_61,code=sm_61 -std=c++14
FAILED: /tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/build/temp.linux-x86_64-3.7/mmcv/ops/csrc/pytorch/roi_pool_cuda.o
/usr/local/cuda/bin/nvcc -DMMCV_WITH_CUDA -I/tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/mmcv/ops/csrc -I/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/torch/include -I/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/torch/include/torch/csrc/api/include -I/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/torch/include/TH -I/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/torch/include/THC -I/usr/local/cuda/include -I/home/ajay/anaconda3/envs/AlignPS/include/python3.7m -c -c /tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/mmcv/ops/csrc/pytorch/roi_pool_cuda.cu -o /tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/build/temp.linux-x86_64-3.7/mmcv/ops/csrc/pytorch/roi_pool_cuda.o -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr --compiler-options ''"'"'-fPIC'"'"'' -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=_ext -D_GLIBCXX_USE_CXX11_ABI=0 -gencode=arch=compute_61,code=sm_61 -std=c++14
/usr/include/c++/7/bits/basic_string.tcc: In instantiation of ‘static std::basic_string<_CharT, _Traits, _Alloc>::_Rep* std::basic_string<_CharT, _Traits, _Alloc>::_Rep::_S_create(std::basic_string<_CharT, _Traits, _Alloc>::size_type, std::basic_string<_CharT, _Traits, _Alloc>::size_type, const _Alloc&) [with _CharT = char16_t; _Traits = std::char_traits<char16_t>; _Alloc = std::allocator<char16_t>; std::basic_string<_CharT, _Traits, _Alloc>::size_type = long unsigned int]’:
/usr/include/c++/7/bits/basic_string.tcc:578:28: required from ‘static _CharT* std::basic_string<_CharT, _Traits, _Alloc>::_S_construct(_InIterator, _InIterator, const _Alloc&, std::forward_iterator_tag) [with _FwdIterator = const char16_t*; _CharT = char16_t; _Traits = std::char_traits<char16_t>; _Alloc = std::allocator<char16_t>]’
/usr/include/c++/7/bits/basic_string.h:5042:20: required from ‘static _CharT* std::basic_string<_CharT, _Traits, _Alloc>::_S_construct_aux(_InIterator, _InIterator, const _Alloc&, std::__false_type) [with _InIterator = const char16_t*; _CharT = char16_t; _Traits = std::char_traits<char16_t>; _Alloc = std::allocator<char16_t>]’
/usr/include/c++/7/bits/basic_string.h:5063:24: required from ‘static _CharT* std::basic_string<_CharT, _Traits, _Alloc>::_S_construct(_InIterator, _InIterator, const _Alloc&) [with _InIterator = const char16_t*; _CharT = char16_t; _Traits = std::char_traits<char16_t>; _Alloc = std::allocator<char16_t>]’
/usr/include/c++/7/bits/basic_string.tcc:656:134: required from ‘std::basic_string<_CharT, _Traits, _Alloc>::basic_string(const _CharT*, std::basic_string<_CharT, _Traits, _Alloc>::size_type, const _Alloc&) [with _CharT = char16_t; _Traits = std::char_traits<char16_t>; _Alloc = std::allocator<char16_t>; std::basic_string<_CharT, _Traits, _Alloc>::size_type = long unsigned int]’
/usr/include/c++/7/bits/basic_string.h:6688:95: required from here
/usr/include/c++/7/bits/basic_string.tcc:1067:16: error: cannot call member function ‘void std::basic_string<_CharT, _Traits, _Alloc>::_Rep::_M_set_sharable() [with _CharT = char16_t; _Traits = std::char_traits<char16_t>; _Alloc = std::allocator<char16_t>]’ without object
__p->_M_set_sharable();
~~~~~~~~~^~
/usr/include/c++/7/bits/basic_string.tcc: In instantiation of ‘static std::basic_string<_CharT, _Traits, _Alloc>::_Rep* std::basic_string<_CharT, _Traits, _Alloc>::_Rep::_S_create(std::basic_string<_CharT, _Traits, _Alloc>::size_type, std::basic_string<_CharT, _Traits, _Alloc>::size_type, const _Alloc&) [with _CharT = char32_t; _Traits = std::char_traits<char32_t>; _Alloc = std::allocator<char32_t>; std::basic_string<_CharT, _Traits, _Alloc>::size_type = long unsigned int]’:
/usr/include/c++/7/bits/basic_string.tcc:578:28: required from ‘static _CharT* std::basic_string<_CharT, _Traits, _Alloc>::_S_construct(_InIterator, _InIterator, const _Alloc&, std::forward_iterator_tag) [with _FwdIterator = const char32_t*; _CharT = char32_t; _Traits = std::char_traits<char32_t>; _Alloc = std::allocator<char32_t>]’
/usr/include/c++/7/bits/basic_string.h:5042:20: required from ‘static _CharT* std::basic_string<_CharT, _Traits, _Alloc>::_S_construct_aux(_InIterator, _InIterator, const _Alloc&, std::__false_type) [with _InIterator = const char32_t*; _CharT = char32_t; _Traits = std::char_traits<char32_t>; _Alloc = std::allocator<char32_t>]’
/usr/include/c++/7/bits/basic_string.h:5063:24: required from ‘static _CharT* std::basic_string<_CharT, _Traits, _Alloc>::_S_construct(_InIterator, _InIterator, const _Alloc&) [with _InIterator = const char32_t*; _CharT = char32_t; _Traits = std::char_traits<char32_t>; _Alloc = std::allocator<char32_t>]’
/usr/include/c++/7/bits/basic_string.tcc:656:134: required from ‘std::basic_string<_CharT, _Traits, _Alloc>::basic_string(const _CharT*, std::basic_string<_CharT, _Traits, _Alloc>::size_type, const _Alloc&) [with _CharT = char32_t; _Traits = std::char_traits<char32_t>; _Alloc = std::allocator<char32_t>; std::basic_string<_CharT, _Traits, _Alloc>::size_type = long unsigned int]’
/usr/include/c++/7/bits/basic_string.h:6693:95: required from here
/usr/include/c++/7/bits/basic_string.tcc:1067:16: error: cannot call member function ‘void std::basic_string<_CharT, _Traits, _Alloc>::_Rep::_M_set_sharable() [with _CharT = char32_t; _Traits = std::char_traits<char32_t>; _Alloc = std::allocator<char32_t>]’ without object
[2/34] /usr/local/cuda/bin/nvcc -DMMCV_WITH_CUDA -I/tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/mmcv/ops/csrc -I/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/torch/include -I/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/torch/include/torch/csrc/api/include -I/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/torch/include/TH -I/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/torch/include/THC -I/usr/local/cuda/include -I/home/ajay/anaconda3/envs/AlignPS/include/python3.7m -c -c /tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/mmcv/ops/csrc/pytorch/carafe_cuda.cu -o /tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/build/temp.linux-x86_64-3.7/mmcv/ops/csrc/pytorch/carafe_cuda.o -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr --compiler-options ''"'"'-fPIC'"'"'' -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=_ext -D_GLIBCXX_USE_CXX11_ABI=0 -gencode=arch=compute_61,code=sm_61 -std=c++14
FAILED: /tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/build/temp.linux-x86_64-3.7/mmcv/ops/csrc/pytorch/carafe_cuda.o
/usr/local/cuda/bin/nvcc -DMMCV_WITH_CUDA -I/tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/mmcv/ops/csrc -I/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/torch/include -I/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/torch/include/torch/csrc/api/include -I/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/torch/include/TH -I/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/torch/include/THC -I/usr/local/cuda/include -I/home/ajay/anaconda3/envs/AlignPS/include/python3.7m -c -c /tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/mmcv/ops/csrc/pytorch/carafe_cuda.cu -o /tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/build/temp.linux-x86_64-3.7/mmcv/ops/csrc/pytorch/carafe_cuda.o -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr --compiler-options ''"'"'-fPIC'"'"'' -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=_ext -D_GLIBCXX_USE_CXX11_ABI=0 -gencode=arch=compute_61,code=sm_61 -std=c++14
/usr/include/c++/7/bits/basic_string.tcc: In instantiation of ‘static std::basic_string<_CharT, _Traits, _Alloc>::_Rep* std::basic_string<_CharT, _Traits, _Alloc>::_Rep::_S_create(std::basic_string<_CharT, _Traits, _Alloc>::size_type, std::basic_string<_CharT, _Traits, _Alloc>::size_type, const _Alloc&) [with _CharT = char16_t; _Traits = std::char_traits<char16_t>; _Alloc = std::allocator<char16_t>; std::basic_string<_CharT, _Traits, _Alloc>::size_type = long unsigned int]’:
/usr/include/c++/7/bits/basic_string.tcc:578:28: required from ‘static _CharT* std::basic_string<_CharT, _Traits, _Alloc>::_S_construct(_InIterator, _InIterator, const _Alloc&, std::forward_iterator_tag) [with _FwdIterator = const char16_t*; _CharT = char16_t; _Traits = std::char_traits<char16_t>; _Alloc = std::allocator<char16_t>]’
/usr/include/c++/7/bits/basic_string.h:5042:20: required from ‘static _CharT* std::basic_string<_CharT, _Traits, _Alloc>::_S_construct_aux(_InIterator, _InIterator, const _Alloc&, std::__false_type) [with _InIterator = const char16_t*; _CharT = char16_t; _Traits = std::char_traits<char16_t>; _Alloc = std::allocator<char16_t>]’
/usr/include/c++/7/bits/basic_string.h:5063:24: required from ‘static _CharT* std::basic_string<_CharT, _Traits, _Alloc>::_S_construct(_InIterator, _InIterator, const _Alloc&) [with _InIterator = const char16_t*; _CharT = char16_t; _Traits = std::char_traits<char16_t>; _Alloc = std::allocator<char16_t>]’
/usr/include/c++/7/bits/basic_string.tcc:656:134: required from ‘std::basic_string<_CharT, _Traits, _Alloc>::basic_string(const _CharT*, std::basic_string<_CharT, _Traits, _Alloc>::size_type, const _Alloc&) [with _CharT = char16_t; _Traits = std::char_traits<char16_t>; _Alloc = std::allocator<char16_t>; std::basic_string<_CharT, _Traits, _Alloc>::size_type = long unsigned int]’
/usr/include/c++/7/bits/basic_string.h:6688:95: required from here
/usr/include/c++/7/bits/basic_string.tcc:1067:16: error: cannot call member function ‘void std::basic_string<_CharT, _Traits, _Alloc>::_Rep::_M_set_sharable() [with _CharT = char16_t; _Traits = std::char_traits<char16_t>; _Alloc = std::allocator<char16_t>]’ without object
__p->_M_set_sharable();
~~~~~~~~~^~
/usr/include/c++/7/bits/basic_string.tcc: In instantiation of ‘static std::basic_string<_CharT, _Traits, _Alloc>::_Rep* std::basic_string<_CharT, _Traits, _Alloc>::_Rep::_S_create(std::basic_string<_CharT, _Traits, _Alloc>::size_type, std::basic_string<_CharT, _Traits, _Alloc>::size_type, const _Alloc&) [with _CharT = char32_t; _Traits = std::char_traits<char32_t>; _Alloc = std::allocator<char32_t>; std::basic_string<_CharT, _Traits, _Alloc>::size_type = long unsigned int]’:
/usr/include/c++/7/bits/basic_string.tcc:578:28: required from ‘static _CharT* std::basic_string<_CharT, _Traits, _Alloc>::_S_construct(_InIterator, _InIterator, const _Alloc&, std::forward_iterator_tag) [with _FwdIterator = const char32_t*; _CharT = char32_t; _Traits = std::char_traits<char32_t>; _Alloc = std::allocator<char32_t>]’
/usr/include/c++/7/bits/basic_string.h:5042:20: required from ‘static _CharT* std::basic_string<_CharT, _Traits, _Alloc>::_S_construct_aux(_InIterator, _InIterator, const _Alloc&, std::__false_type) [with _InIterator = const char32_t*; _CharT = char32_t; _Traits = std::char_traits<char32_t>; _Alloc = std::allocator<char32_t>]’
/usr/include/c++/7/bits/basic_string.h:5063:24: required from ‘static _CharT* std::basic_string<_CharT, _Traits, _Alloc>::_S_construct(_InIterator, _InIterator, const _Alloc&) [with _InIterator = const char32_t*; _CharT = char32_t; _Traits = std::char_traits<char32_t>; _Alloc = std::allocator<char32_t>]’
/usr/include/c++/7/bits/basic_string.tcc:656:134: required from ‘std::basic_string<_CharT, _Traits, _Alloc>::basic_string(const _CharT*, std::basic_string<_CharT, _Traits, _Alloc>::size_type, const _Alloc&) [with _CharT = char32_t; _Traits = std::char_traits<char32_t>; _Alloc = std::allocator<char32_t>; std::basic_string<_CharT, _Traits, _Alloc>::size_type = long unsigned int]’
/usr/include/c++/7/bits/basic_string.h:6693:95: required from here
/usr/include/c++/7/bits/basic_string.tcc:1067:16: error: cannot call member function ‘void std::basic_string<_CharT, _Traits, _Alloc>::_Rep::_M_set_sharable() [with _CharT = char32_t; _Traits = std::char_traits<char32_t>; _Alloc = std::allocator<char32_t>]’ without object
[3/34] c++ -MMD -MF /tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/build/temp.linux-x86_64-3.7/mmcv/ops/csrc/pytorch/roi_align.o.d -pthread -B /home/ajay/anaconda3/envs/AlignPS/compiler_compat -Wl,--sysroot=/ -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC -DMMCV_WITH_CUDA -I/tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/mmcv/ops/csrc -I/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/torch/include -I/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/torch/include/torch/csrc/api/include -I/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/torch/include/TH -I/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/torch/include/THC -I/usr/local/cuda/include -I/home/ajay/anaconda3/envs/AlignPS/include/python3.7m -c -c /tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/mmcv/ops/csrc/pytorch/roi_align.cpp -o /tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/build/temp.linux-x86_64-3.7/mmcv/ops/csrc/pytorch/roi_align.o -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=_ext -D_GLIBCXX_USE_CXX11_ABI=0 -std=c++14
cc1plus: warning: command line option ‘-Wstrict-prototypes’ is valid for C/ObjC but not for C++
In file included from /home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/torch/include/ATen/Parallel.h:149:0,
from /home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/utils.h:3,
from /home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h:5,
from /home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/nn.h:3,
from /home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/all.h:12,
from /home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/torch/include/torch/extension.h:4,
from /tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/mmcv/ops/csrc/pytorch_cpp_helper.hpp:3,
from /tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/mmcv/ops/csrc/pytorch/roi_align.cpp:1:
/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/torch/include/ATen/ParallelOpenMP.h:84:0: warning: ignoring #pragma omp parallel [-Wunknown-pragmas]
#pragma omp parallel for if ((end - begin) >= grain_size)
[4/34] c++ -MMD -MF /tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/build/temp.linux-x86_64-3.7/mmcv/ops/csrc/pytorch/sync_bn.o.d -pthread -B /home/ajay/anaconda3/envs/AlignPS/compiler_compat -Wl,--sysroot=/ -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC -DMMCV_WITH_CUDA -I/tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/mmcv/ops/csrc -I/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/torch/include -I/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/torch/include/torch/csrc/api/include -I/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/torch/include/TH -I/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/torch/include/THC -I/usr/local/cuda/include -I/home/ajay/anaconda3/envs/AlignPS/include/python3.7m -c -c /tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/mmcv/ops/csrc/pytorch/sync_bn.cpp -o /tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/build/temp.linux-x86_64-3.7/mmcv/ops/csrc/pytorch/sync_bn.o -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=_ext -D_GLIBCXX_USE_CXX11_ABI=0 -std=c++14
cc1plus: warning: command line option ‘-Wstrict-prototypes’ is valid for C/ObjC but not for C++
In file included from /home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/torch/include/ATen/Parallel.h:149:0,
from /home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/utils.h:3,
from /home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h:5,
from /home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/nn.h:3,
from /home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/all.h:12,
from /home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/torch/include/torch/extension.h:4,
from /tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/mmcv/ops/csrc/pytorch_cpp_helper.hpp:3,
from /tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/mmcv/ops/csrc/pytorch/sync_bn.cpp:1:
/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/torch/include/ATen/ParallelOpenMP.h:84:0: warning: ignoring #pragma omp parallel [-Wunknown-pragmas]
#pragma omp parallel for if ((end - begin) >= grain_size)
ninja: build stopped: subcommand failed.
Traceback (most recent call last):
File "/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/torch/utils/cpp_extension.py", line 1522, in _run_ninja_build
env=env)
File "/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/subprocess.py", line 512, in run
output=stdout, stderr=stderr)
subprocess.CalledProcessError: Command '['ninja', '-v', '-j', '4']' returned non-zero exit status 1.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "<string>", line 1, in <module>
File "/tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/setup.py", line 219, in <module>
zip_safe=False)
File "/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/setuptools/__init__.py", line 153, in setup
return distutils.core.setup(**attrs)
File "/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/distutils/core.py", line 148, in setup
dist.run_commands()
File "/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/distutils/dist.py", line 966, in run_commands
self.run_command(cmd)
File "/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/distutils/dist.py", line 985, in run_command
cmd_obj.run()
File "/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/wheel/bdist_wheel.py", line 299, in run
self.run_command('build')
File "/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/distutils/cmd.py", line 313, in run_command
self.distribution.run_command(command)
File "/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/distutils/dist.py", line 985, in run_command
cmd_obj.run()
File "/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/distutils/command/build.py", line 135, in run
self.run_command(cmd_name)
File "/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/distutils/cmd.py", line 313, in run_command
self.distribution.run_command(command)
File "/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/distutils/dist.py", line 985, in run_command
cmd_obj.run()
File "/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/setuptools/command/build_ext.py", line 79, in run
_build_ext.run(self)
File "/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/distutils/command/build_ext.py", line 340, in run
self.build_extensions()
File "/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/torch/utils/cpp_extension.py", line 653, in build_extensions
build_ext.build_extensions(self)
File "/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/distutils/command/build_ext.py", line 449, in build_extensions
self._build_extensions_serial()
File "/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/distutils/command/build_ext.py", line 474, in _build_extensions_serial
self.build_extension(ext)
File "/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/setuptools/command/build_ext.py", line 196, in build_extension
_build_ext.build_extension(self, ext)
File "/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/distutils/command/build_ext.py", line 534, in build_extension
depends=ext.depends)
File "/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/torch/utils/cpp_extension.py", line 482, in unix_wrap_ninja_compile
with_cuda=with_cuda)
File "/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/torch/utils/cpp_extension.py", line 1238, in _write_ninja_file_and_compile_objects
error_prefix='Error compiling objects for extension')
File "/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/torch/utils/cpp_extension.py", line 1538, in _run_ninja_build
raise RuntimeError(message) from e
RuntimeError: Error compiling objects for extension
----------------------------------------
ERROR: Failed building wheel for mmcv-full
Running setup.py clean for mmcv-full
Failed to build mmcv-full
Installing collected packages: mmcv-full
Running setup.py install for mmcv-full ... error
ERROR: Command errored out with exit status 1:
command: /home/ajay/anaconda3/envs/AlignPS/bin/python -u -c 'import sys, setuptools, tokenize; sys.argv[0] = '"'"'/tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/setup.py'"'"'; __file__='"'"'/tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/setup.py'"'"';f=getattr(tokenize, '"'"'open'"'"', open)(__file__);code=f.read().replace('"'"'\r\n'"'"', '"'"'\n'"'"');f.close();exec(compile(code, __file__, '"'"'exec'"'"'))' install --record /tmp/pip-record-h69x7dhk/install-record.txt --single-version-externally-managed --compile --install-headers /home/ajay/anaconda3/envs/AlignPS/include/python3.7m/mmcv-full
cwd: /tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/
Complete output (416 lines):
running install
running build
running build_py
creating build
creating build/lib.linux-x86_64-3.7
creating build/lib.linux-x86_64-3.7/mmcv
copying mmcv/version.py -> build/lib.linux-x86_64-3.7/mmcv
copying mmcv/__init__.py -> build/lib.linux-x86_64-3.7/mmcv
creating build/lib.linux-x86_64-3.7/mmcv/ops
copying mmcv/ops/roi_pool.py -> build/lib.linux-x86_64-3.7/mmcv/ops
copying mmcv/ops/cc_attention.py -> build/lib.linux-x86_64-3.7/mmcv/ops
copying mmcv/ops/deprecated_wrappers.py -> build/lib.linux-x86_64-3.7/mmcv/ops
copying mmcv/ops/focal_loss.py -> build/lib.linux-x86_64-3.7/mmcv/ops
copying mmcv/ops/sync_bn.py -> build/lib.linux-x86_64-3.7/mmcv/ops
copying mmcv/ops/carafe.py -> build/lib.linux-x86_64-3.7/mmcv/ops
copying mmcv/ops/saconv.py -> build/lib.linux-x86_64-3.7/mmcv/ops
copying mmcv/ops/roi_align.py -> build/lib.linux-x86_64-3.7/mmcv/ops
copying mmcv/ops/merge_cells.py -> build/lib.linux-x86_64-3.7/mmcv/ops
copying mmcv/ops/deform_conv.py -> build/lib.linux-x86_64-3.7/mmcv/ops
copying mmcv/ops/__init__.py -> build/lib.linux-x86_64-3.7/mmcv/ops
copying mmcv/ops/bbox.py -> build/lib.linux-x86_64-3.7/mmcv/ops
copying mmcv/ops/tin_shift.py -> build/lib.linux-x86_64-3.7/mmcv/ops
copying mmcv/ops/nms.py -> build/lib.linux-x86_64-3.7/mmcv/ops
copying mmcv/ops/psa_mask.py -> build/lib.linux-x86_64-3.7/mmcv/ops
copying mmcv/ops/deform_roi_pool.py -> build/lib.linux-x86_64-3.7/mmcv/ops
copying mmcv/ops/masked_conv.py -> build/lib.linux-x86_64-3.7/mmcv/ops
copying mmcv/ops/point_sample.py -> build/lib.linux-x86_64-3.7/mmcv/ops
copying mmcv/ops/corner_pool.py -> build/lib.linux-x86_64-3.7/mmcv/ops
copying mmcv/ops/modulated_deform_conv.py -> build/lib.linux-x86_64-3.7/mmcv/ops
copying mmcv/ops/info.py -> build/lib.linux-x86_64-3.7/mmcv/ops
creating build/lib.linux-x86_64-3.7/mmcv/fileio
copying mmcv/fileio/__init__.py -> build/lib.linux-x86_64-3.7/mmcv/fileio
copying mmcv/fileio/parse.py -> build/lib.linux-x86_64-3.7/mmcv/fileio
copying mmcv/fileio/io.py -> build/lib.linux-x86_64-3.7/mmcv/fileio
copying mmcv/fileio/file_client.py -> build/lib.linux-x86_64-3.7/mmcv/fileio
creating build/lib.linux-x86_64-3.7/mmcv/runner
copying mmcv/runner/log_buffer.py -> build/lib.linux-x86_64-3.7/mmcv/runner
copying mmcv/runner/dist_utils.py -> build/lib.linux-x86_64-3.7/mmcv/runner
copying mmcv/runner/iter_based_runner.py -> build/lib.linux-x86_64-3.7/mmcv/runner
copying mmcv/runner/__init__.py -> build/lib.linux-x86_64-3.7/mmcv/runner
copying mmcv/runner/epoch_based_runner.py -> build/lib.linux-x86_64-3.7/mmcv/runner
copying mmcv/runner/priority.py -> build/lib.linux-x86_64-3.7/mmcv/runner
copying mmcv/runner/utils.py -> build/lib.linux-x86_64-3.7/mmcv/runner
copying mmcv/runner/builder.py -> build/lib.linux-x86_64-3.7/mmcv/runner
copying mmcv/runner/checkpoint.py -> build/lib.linux-x86_64-3.7/mmcv/runner
copying mmcv/runner/fp16_utils.py -> build/lib.linux-x86_64-3.7/mmcv/runner
copying mmcv/runner/base_runner.py -> build/lib.linux-x86_64-3.7/mmcv/runner
creating build/lib.linux-x86_64-3.7/mmcv/image
copying mmcv/image/geometric.py -> build/lib.linux-x86_64-3.7/mmcv/image
copying mmcv/image/colorspace.py -> build/lib.linux-x86_64-3.7/mmcv/image
copying mmcv/image/photometric.py -> build/lib.linux-x86_64-3.7/mmcv/image
copying mmcv/image/__init__.py -> build/lib.linux-x86_64-3.7/mmcv/image
copying mmcv/image/io.py -> build/lib.linux-x86_64-3.7/mmcv/image
copying mmcv/image/misc.py -> build/lib.linux-x86_64-3.7/mmcv/image
creating build/lib.linux-x86_64-3.7/mmcv/utils
copying mmcv/utils/config.py -> build/lib.linux-x86_64-3.7/mmcv/utils
copying mmcv/utils/version_utils.py -> build/lib.linux-x86_64-3.7/mmcv/utils
copying mmcv/utils/__init__.py -> build/lib.linux-x86_64-3.7/mmcv/utils
copying mmcv/utils/timer.py -> build/lib.linux-x86_64-3.7/mmcv/utils
copying mmcv/utils/logging.py -> build/lib.linux-x86_64-3.7/mmcv/utils
copying mmcv/utils/env.py -> build/lib.linux-x86_64-3.7/mmcv/utils
copying mmcv/utils/progressbar.py -> build/lib.linux-x86_64-3.7/mmcv/utils
copying mmcv/utils/ext_loader.py -> build/lib.linux-x86_64-3.7/mmcv/utils
copying mmcv/utils/path.py -> build/lib.linux-x86_64-3.7/mmcv/utils
copying mmcv/utils/parrots_wrapper.py -> build/lib.linux-x86_64-3.7/mmcv/utils
copying mmcv/utils/misc.py -> build/lib.linux-x86_64-3.7/mmcv/utils
copying mmcv/utils/registry.py -> build/lib.linux-x86_64-3.7/mmcv/utils
creating build/lib.linux-x86_64-3.7/mmcv/parallel
copying mmcv/parallel/data_parallel.py -> build/lib.linux-x86_64-3.7/mmcv/parallel
copying mmcv/parallel/data_container.py -> build/lib.linux-x86_64-3.7/mmcv/parallel
copying mmcv/parallel/_functions.py -> build/lib.linux-x86_64-3.7/mmcv/parallel
copying mmcv/parallel/__init__.py -> build/lib.linux-x86_64-3.7/mmcv/parallel
copying mmcv/parallel/collate.py -> build/lib.linux-x86_64-3.7/mmcv/parallel
copying mmcv/parallel/distributed_deprecated.py -> build/lib.linux-x86_64-3.7/mmcv/parallel
copying mmcv/parallel/distributed.py -> build/lib.linux-x86_64-3.7/mmcv/parallel
copying mmcv/parallel/utils.py -> build/lib.linux-x86_64-3.7/mmcv/parallel
copying mmcv/parallel/registry.py -> build/lib.linux-x86_64-3.7/mmcv/parallel
copying mmcv/parallel/scatter_gather.py -> build/lib.linux-x86_64-3.7/mmcv/parallel
creating build/lib.linux-x86_64-3.7/mmcv/cnn
copying mmcv/cnn/resnet.py -> build/lib.linux-x86_64-3.7/mmcv/cnn
copying mmcv/cnn/vgg.py -> build/lib.linux-x86_64-3.7/mmcv/cnn
copying mmcv/cnn/__init__.py -> build/lib.linux-x86_64-3.7/mmcv/cnn
copying mmcv/cnn/alexnet.py -> build/lib.linux-x86_64-3.7/mmcv/cnn
creating build/lib.linux-x86_64-3.7/mmcv/video
copying mmcv/video/processing.py -> build/lib.linux-x86_64-3.7/mmcv/video
copying mmcv/video/__init__.py -> build/lib.linux-x86_64-3.7/mmcv/video
copying mmcv/video/io.py -> build/lib.linux-x86_64-3.7/mmcv/video
copying mmcv/video/optflow.py -> build/lib.linux-x86_64-3.7/mmcv/video
creating build/lib.linux-x86_64-3.7/mmcv/visualization
copying mmcv/visualization/image.py -> build/lib.linux-x86_64-3.7/mmcv/visualization
copying mmcv/visualization/__init__.py -> build/lib.linux-x86_64-3.7/mmcv/visualization
copying mmcv/visualization/color.py -> build/lib.linux-x86_64-3.7/mmcv/visualization
copying mmcv/visualization/optflow.py -> build/lib.linux-x86_64-3.7/mmcv/visualization
creating build/lib.linux-x86_64-3.7/mmcv/arraymisc
copying mmcv/arraymisc/__init__.py -> build/lib.linux-x86_64-3.7/mmcv/arraymisc
copying mmcv/arraymisc/quantization.py -> build/lib.linux-x86_64-3.7/mmcv/arraymisc
creating build/lib.linux-x86_64-3.7/mmcv/onnx
copying mmcv/onnx/__init__.py -> build/lib.linux-x86_64-3.7/mmcv/onnx
copying mmcv/onnx/symbolic.py -> build/lib.linux-x86_64-3.7/mmcv/onnx
creating build/lib.linux-x86_64-3.7/mmcv/fileio/handlers
copying mmcv/fileio/handlers/yaml_handler.py -> build/lib.linux-x86_64-3.7/mmcv/fileio/handlers
copying mmcv/fileio/handlers/base.py -> build/lib.linux-x86_64-3.7/mmcv/fileio/handlers
copying mmcv/fileio/handlers/json_handler.py -> build/lib.linux-x86_64-3.7/mmcv/fileio/handlers
copying mmcv/fileio/handlers/__init__.py -> build/lib.linux-x86_64-3.7/mmcv/fileio/handlers
copying mmcv/fileio/handlers/pickle_handler.py -> build/lib.linux-x86_64-3.7/mmcv/fileio/handlers
creating build/lib.linux-x86_64-3.7/mmcv/runner/hooks
copying mmcv/runner/hooks/iter_timer.py -> build/lib.linux-x86_64-3.7/mmcv/runner/hooks
copying mmcv/runner/hooks/sampler_seed.py -> build/lib.linux-x86_64-3.7/mmcv/runner/hooks
copying mmcv/runner/hooks/optimizer.py -> build/lib.linux-x86_64-3.7/mmcv/runner/hooks
copying mmcv/runner/hooks/momentum_updater.py -> build/lib.linux-x86_64-3.7/mmcv/runner/hooks
copying mmcv/runner/hooks/__init__.py -> build/lib.linux-x86_64-3.7/mmcv/runner/hooks
copying mmcv/runner/hooks/ema.py -> build/lib.linux-x86_64-3.7/mmcv/runner/hooks
copying mmcv/runner/hooks/sync_buffer.py -> build/lib.linux-x86_64-3.7/mmcv/runner/hooks
copying mmcv/runner/hooks/hook.py -> build/lib.linux-x86_64-3.7/mmcv/runner/hooks
copying mmcv/runner/hooks/checkpoint.py -> build/lib.linux-x86_64-3.7/mmcv/runner/hooks
copying mmcv/runner/hooks/memory.py -> build/lib.linux-x86_64-3.7/mmcv/runner/hooks
copying mmcv/runner/hooks/closure.py -> build/lib.linux-x86_64-3.7/mmcv/runner/hooks
copying mmcv/runner/hooks/lr_updater.py -> build/lib.linux-x86_64-3.7/mmcv/runner/hooks
creating build/lib.linux-x86_64-3.7/mmcv/runner/optimizer
copying mmcv/runner/optimizer/__init__.py -> build/lib.linux-x86_64-3.7/mmcv/runner/optimizer
copying mmcv/runner/optimizer/default_constructor.py -> build/lib.linux-x86_64-3.7/mmcv/runner/optimizer
copying mmcv/runner/optimizer/builder.py -> build/lib.linux-x86_64-3.7/mmcv/runner/optimizer
creating build/lib.linux-x86_64-3.7/mmcv/runner/hooks/logger
copying mmcv/runner/hooks/logger/pavi.py -> build/lib.linux-x86_64-3.7/mmcv/runner/hooks/logger
copying mmcv/runner/hooks/logger/wandb.py -> build/lib.linux-x86_64-3.7/mmcv/runner/hooks/logger
copying mmcv/runner/hooks/logger/base.py -> build/lib.linux-x86_64-3.7/mmcv/runner/hooks/logger
copying mmcv/runner/hooks/logger/tensorboard.py -> build/lib.linux-x86_64-3.7/mmcv/runner/hooks/logger
copying mmcv/runner/hooks/logger/mlflow.py -> build/lib.linux-x86_64-3.7/mmcv/runner/hooks/logger
copying mmcv/runner/hooks/logger/__init__.py -> build/lib.linux-x86_64-3.7/mmcv/runner/hooks/logger
copying mmcv/runner/hooks/logger/text.py -> build/lib.linux-x86_64-3.7/mmcv/runner/hooks/logger
creating build/lib.linux-x86_64-3.7/mmcv/cnn/bricks
copying mmcv/cnn/bricks/generalized_attention.py -> build/lib.linux-x86_64-3.7/mmcv/cnn/bricks
copying mmcv/cnn/bricks/conv.py -> build/lib.linux-x86_64-3.7/mmcv/cnn/bricks
copying mmcv/cnn/bricks/context_block.py -> build/lib.linux-x86_64-3.7/mmcv/cnn/bricks
copying mmcv/cnn/bricks/conv2d_adaptive_padding.py -> build/lib.linux-x86_64-3.7/mmcv/cnn/bricks
copying mmcv/cnn/bricks/conv_module.py -> build/lib.linux-x86_64-3.7/mmcv/cnn/bricks
copying mmcv/cnn/bricks/padding.py -> build/lib.linux-x86_64-3.7/mmcv/cnn/bricks
copying mmcv/cnn/bricks/non_local.py -> build/lib.linux-x86_64-3.7/mmcv/cnn/bricks
copying mmcv/cnn/bricks/norm.py -> build/lib.linux-x86_64-3.7/mmcv/cnn/bricks
copying mmcv/cnn/bricks/__init__.py -> build/lib.linux-x86_64-3.7/mmcv/cnn/bricks
copying mmcv/cnn/bricks/hswish.py -> build/lib.linux-x86_64-3.7/mmcv/cnn/bricks
copying mmcv/cnn/bricks/conv_ws.py -> build/lib.linux-x86_64-3.7/mmcv/cnn/bricks
copying mmcv/cnn/bricks/wrappers.py -> build/lib.linux-x86_64-3.7/mmcv/cnn/bricks
copying mmcv/cnn/bricks/activation.py -> build/lib.linux-x86_64-3.7/mmcv/cnn/bricks
copying mmcv/cnn/bricks/depthwise_separable_conv_module.py -> build/lib.linux-x86_64-3.7/mmcv/cnn/bricks
copying mmcv/cnn/bricks/plugin.py -> build/lib.linux-x86_64-3.7/mmcv/cnn/bricks
copying mmcv/cnn/bricks/hsigmoid.py -> build/lib.linux-x86_64-3.7/mmcv/cnn/bricks
copying mmcv/cnn/bricks/swish.py -> build/lib.linux-x86_64-3.7/mmcv/cnn/bricks
copying mmcv/cnn/bricks/registry.py -> build/lib.linux-x86_64-3.7/mmcv/cnn/bricks
copying mmcv/cnn/bricks/upsample.py -> build/lib.linux-x86_64-3.7/mmcv/cnn/bricks
copying mmcv/cnn/bricks/scale.py -> build/lib.linux-x86_64-3.7/mmcv/cnn/bricks
creating build/lib.linux-x86_64-3.7/mmcv/cnn/utils
copying mmcv/cnn/utils/fuse_conv_bn.py -> build/lib.linux-x86_64-3.7/mmcv/cnn/utils
copying mmcv/cnn/utils/__init__.py -> build/lib.linux-x86_64-3.7/mmcv/cnn/utils
copying mmcv/cnn/utils/weight_init.py -> build/lib.linux-x86_64-3.7/mmcv/cnn/utils
copying mmcv/cnn/utils/flops_counter.py -> build/lib.linux-x86_64-3.7/mmcv/cnn/utils
creating build/lib.linux-x86_64-3.7/mmcv/video/optflow_warp
copying mmcv/video/optflow_warp/__init__.py -> build/lib.linux-x86_64-3.7/mmcv/video/optflow_warp
creating build/lib.linux-x86_64-3.7/mmcv/onnx/onnx_utils
copying mmcv/onnx/onnx_utils/__init__.py -> build/lib.linux-x86_64-3.7/mmcv/onnx/onnx_utils
copying mmcv/onnx/onnx_utils/symbolic_helper.py -> build/lib.linux-x86_64-3.7/mmcv/onnx/onnx_utils
running egg_info
writing mmcv_full.egg-info/PKG-INFO
writing dependency_links to mmcv_full.egg-info/dependency_links.txt
writing requirements to mmcv_full.egg-info/requires.txt
writing top-level names to mmcv_full.egg-info/top_level.txt
reading manifest file 'mmcv_full.egg-info/SOURCES.txt'
reading manifest template 'MANIFEST.in'
writing manifest file 'mmcv_full.egg-info/SOURCES.txt'
creating build/lib.linux-x86_64-3.7/mmcv/model_zoo
copying mmcv/model_zoo/deprecated.json -> build/lib.linux-x86_64-3.7/mmcv/model_zoo
copying mmcv/model_zoo/mmcls.json -> build/lib.linux-x86_64-3.7/mmcv/model_zoo
copying mmcv/model_zoo/open_mmlab.json -> build/lib.linux-x86_64-3.7/mmcv/model_zoo
creating build/lib.linux-x86_64-3.7/mmcv/ops/csrc
copying mmcv/ops/csrc/bbox_overlaps_cuda_kernel.cuh -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc
copying mmcv/ops/csrc/carafe_cuda_kernel.cuh -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc
copying mmcv/ops/csrc/carafe_naive_cuda_kernel.cuh -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc
copying mmcv/ops/csrc/cc_attention_cuda_kernel.cuh -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc
copying mmcv/ops/csrc/common_cuda_helper.hpp -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc
copying mmcv/ops/csrc/deform_conv_cuda_kernel.cuh -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc
copying mmcv/ops/csrc/deform_roi_pool_cuda_kernel.cuh -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc
copying mmcv/ops/csrc/masked_conv2d_cuda_kernel.cuh -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc
copying mmcv/ops/csrc/modulated_deform_conv_cuda_kernel.cuh -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc
copying mmcv/ops/csrc/nms_cuda_kernel.cuh -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc
copying mmcv/ops/csrc/parrots_cpp_helper.hpp -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc
copying mmcv/ops/csrc/parrots_cuda_helper.hpp -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc
copying mmcv/ops/csrc/parrots_cudawarpfunction.cuh -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc
copying mmcv/ops/csrc/psamask_cuda_kernel.cuh -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc
copying mmcv/ops/csrc/pytorch_cpp_helper.hpp -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc
copying mmcv/ops/csrc/pytorch_cuda_helper.hpp -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc
copying mmcv/ops/csrc/roi_align_cuda_kernel.cuh -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc
copying mmcv/ops/csrc/roi_pool_cuda_kernel.cuh -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc
copying mmcv/ops/csrc/sigmoid_focal_loss_cuda_kernel.cuh -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc
copying mmcv/ops/csrc/softmax_focal_loss_cuda_kernel.cuh -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc
copying mmcv/ops/csrc/sync_bn_cuda_kernel.cuh -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc
copying mmcv/ops/csrc/tin_shift_cuda_kernel.cuh -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc
creating build/lib.linux-x86_64-3.7/mmcv/ops/csrc/parrots
copying mmcv/ops/csrc/parrots/bbox_overlaps.cpp -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/parrots
copying mmcv/ops/csrc/parrots/bbox_overlaps_cuda.cu -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/parrots
copying mmcv/ops/csrc/parrots/carafe.cpp -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/parrots
copying mmcv/ops/csrc/parrots/carafe_cuda.cu -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/parrots
copying mmcv/ops/csrc/parrots/carafe_naive.cpp -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/parrots
copying mmcv/ops/csrc/parrots/carafe_naive_cuda.cu -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/parrots
copying mmcv/ops/csrc/parrots/cc_attention.cpp -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/parrots
copying mmcv/ops/csrc/parrots/cc_attention_cuda_kernel.cu -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/parrots
copying mmcv/ops/csrc/parrots/corner_pool.cpp -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/parrots
copying mmcv/ops/csrc/parrots/deform_conv.cpp -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/parrots
copying mmcv/ops/csrc/parrots/deform_conv_cuda.cu -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/parrots
copying mmcv/ops/csrc/parrots/deform_roi_pool.cpp -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/parrots
copying mmcv/ops/csrc/parrots/deform_roi_pool_cuda.cu -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/parrots
copying mmcv/ops/csrc/parrots/focal_loss.cpp -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/parrots
copying mmcv/ops/csrc/parrots/focal_loss_cuda.cu -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/parrots
copying mmcv/ops/csrc/parrots/masked_conv2d.cpp -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/parrots
copying mmcv/ops/csrc/parrots/masked_conv2d_cuda.cu -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/parrots
copying mmcv/ops/csrc/parrots/modulated_deform_conv.cpp -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/parrots
copying mmcv/ops/csrc/parrots/modulated_deform_conv_cuda.cu -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/parrots
copying mmcv/ops/csrc/parrots/nms.cpp -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/parrots
copying mmcv/ops/csrc/parrots/nms_cuda.cu -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/parrots
copying mmcv/ops/csrc/parrots/parrots_cpp_helper.cpp -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/parrots
copying mmcv/ops/csrc/parrots/parrots_cuda_helper.cu -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/parrots
copying mmcv/ops/csrc/parrots/psamask.cpp -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/parrots
copying mmcv/ops/csrc/parrots/psamask_cuda.cu -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/parrots
copying mmcv/ops/csrc/parrots/roi_align.cpp -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/parrots
copying mmcv/ops/csrc/parrots/roi_align_cuda.cu -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/parrots
copying mmcv/ops/csrc/parrots/roi_pool.cpp -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/parrots
copying mmcv/ops/csrc/parrots/roi_pool_cuda.cu -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/parrots
copying mmcv/ops/csrc/parrots/sync_bn.cpp -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/parrots
copying mmcv/ops/csrc/parrots/sync_bn_cuda.cu -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/parrots
copying mmcv/ops/csrc/parrots/tin_shift.cpp -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/parrots
copying mmcv/ops/csrc/parrots/tin_shift_cuda.cu -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/parrots
creating build/lib.linux-x86_64-3.7/mmcv/ops/csrc/pytorch
copying mmcv/ops/csrc/pytorch/bbox_overlaps.cpp -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/pytorch
copying mmcv/ops/csrc/pytorch/bbox_overlaps_cuda.cu -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/pytorch
copying mmcv/ops/csrc/pytorch/carafe.cpp -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/pytorch
copying mmcv/ops/csrc/pytorch/carafe_cuda.cu -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/pytorch
copying mmcv/ops/csrc/pytorch/carafe_naive.cpp -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/pytorch
copying mmcv/ops/csrc/pytorch/carafe_naive_cuda.cu -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/pytorch
copying mmcv/ops/csrc/pytorch/cc_attention.cpp -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/pytorch
copying mmcv/ops/csrc/pytorch/cc_attention_cuda.cu -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/pytorch
copying mmcv/ops/csrc/pytorch/corner_pool.cpp -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/pytorch
copying mmcv/ops/csrc/pytorch/deform_conv.cpp -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/pytorch
copying mmcv/ops/csrc/pytorch/deform_conv_cuda.cu -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/pytorch
copying mmcv/ops/csrc/pytorch/deform_roi_pool.cpp -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/pytorch
copying mmcv/ops/csrc/pytorch/deform_roi_pool_cuda.cu -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/pytorch
copying mmcv/ops/csrc/pytorch/focal_loss.cpp -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/pytorch
copying mmcv/ops/csrc/pytorch/focal_loss_cuda.cu -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/pytorch
copying mmcv/ops/csrc/pytorch/info.cpp -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/pytorch
copying mmcv/ops/csrc/pytorch/masked_conv2d.cpp -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/pytorch
copying mmcv/ops/csrc/pytorch/masked_conv2d_cuda.cu -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/pytorch
copying mmcv/ops/csrc/pytorch/modulated_deform_conv.cpp -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/pytorch
copying mmcv/ops/csrc/pytorch/modulated_deform_conv_cuda.cu -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/pytorch
copying mmcv/ops/csrc/pytorch/nms.cpp -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/pytorch
copying mmcv/ops/csrc/pytorch/nms_cuda.cu -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/pytorch
copying mmcv/ops/csrc/pytorch/psamask.cpp -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/pytorch
copying mmcv/ops/csrc/pytorch/psamask_cuda.cu -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/pytorch
copying mmcv/ops/csrc/pytorch/pybind.cpp -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/pytorch
copying mmcv/ops/csrc/pytorch/roi_align.cpp -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/pytorch
copying mmcv/ops/csrc/pytorch/roi_align_cpu.cpp -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/pytorch
copying mmcv/ops/csrc/pytorch/roi_align_cuda.cu -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/pytorch
copying mmcv/ops/csrc/pytorch/roi_pool.cpp -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/pytorch
copying mmcv/ops/csrc/pytorch/roi_pool_cuda.cu -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/pytorch
copying mmcv/ops/csrc/pytorch/sync_bn.cpp -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/pytorch
copying mmcv/ops/csrc/pytorch/sync_bn_cuda.cu -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/pytorch
copying mmcv/ops/csrc/pytorch/tin_shift.cpp -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/pytorch
copying mmcv/ops/csrc/pytorch/tin_shift_cuda.cu -> build/lib.linux-x86_64-3.7/mmcv/ops/csrc/pytorch
copying mmcv/video/optflow_warp/flow_warp.hpp -> build/lib.linux-x86_64-3.7/mmcv/video/optflow_warp
copying mmcv/video/optflow_warp/flow_warp_module.pyx -> build/lib.linux-x86_64-3.7/mmcv/video/optflow_warp
running build_ext
building 'mmcv._flow_warp_ext' extension
creating /tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/build/temp.linux-x86_64-3.7
creating /tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/build/temp.linux-x86_64-3.7/mmcv
creating /tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/build/temp.linux-x86_64-3.7/mmcv/video
creating /tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/build/temp.linux-x86_64-3.7/mmcv/video/optflow_warp
Emitting ninja build file /tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/build/temp.linux-x86_64-3.7/build.ninja...
Compiling objects...
Using envvar MAX_JOBS (4) as the number of workers...
[1/2] c++ -MMD -MF /tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/build/temp.linux-x86_64-3.7/mmcv/video/optflow_warp/flow_warp.o.d -pthread -B /home/ajay/anaconda3/envs/AlignPS/compiler_compat -Wl,--sysroot=/ -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC -I./mmcv/video/optflow_warp -I/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/numpy/core/include -I/home/ajay/anaconda3/envs/AlignPS/include/python3.7m -c -c /tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/mmcv/video/optflow_warp/flow_warp.cpp -o /tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/build/temp.linux-x86_64-3.7/mmcv/video/optflow_warp/flow_warp.o -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=_flow_warp_ext -D_GLIBCXX_USE_CXX11_ABI=0 -std=c++14
cc1plus: warning: command line option ‘-Wstrict-prototypes’ is valid for C/ObjC but not for C++
[2/2] c++ -MMD -MF /tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/build/temp.linux-x86_64-3.7/mmcv/video/optflow_warp/flow_warp_module.o.d -pthread -B /home/ajay/anaconda3/envs/AlignPS/compiler_compat -Wl,--sysroot=/ -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC -I./mmcv/video/optflow_warp -I/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/numpy/core/include -I/home/ajay/anaconda3/envs/AlignPS/include/python3.7m -c -c /tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/mmcv/video/optflow_warp/flow_warp_module.cpp -o /tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/build/temp.linux-x86_64-3.7/mmcv/video/optflow_warp/flow_warp_module.o -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=_flow_warp_ext -D_GLIBCXX_USE_CXX11_ABI=0 -std=c++14
cc1plus: warning: command line option ‘-Wstrict-prototypes’ is valid for C/ObjC but not for C++
In file included from /home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/numpy/core/include/numpy/ndarraytypes.h:1822:0,
from /home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/numpy/core/include/numpy/ndarrayobject.h:12,
from /home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/numpy/core/include/numpy/arrayobject.h:4,
from /tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/mmcv/video/optflow_warp/flow_warp_module.cpp:647:
/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/numpy/core/include/numpy/npy_1_7_deprecated_api.h:17:2: warning: #warning "Using deprecated NumPy API, disable it with " "#define NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION" [-Wcpp]
#warning "Using deprecated NumPy API, disable it with " \
^~~~~~~
g++ -pthread -shared -B /home/ajay/anaconda3/envs/AlignPS/compiler_compat -L/home/ajay/anaconda3/envs/AlignPS/lib -Wl,-rpath=/home/ajay/anaconda3/envs/AlignPS/lib -Wl,--no-as-needed -Wl,--sysroot=/ /tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/build/temp.linux-x86_64-3.7/./mmcv/video/optflow_warp/flow_warp_module.o /tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/build/temp.linux-x86_64-3.7/./mmcv/video/optflow_warp/flow_warp.o -o build/lib.linux-x86_64-3.7/mmcv/_flow_warp_ext.cpython-37m-x86_64-linux-gnu.so
building 'mmcv._ext' extension
creating /tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/build/temp.linux-x86_64-3.7/mmcv/ops
creating /tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/build/temp.linux-x86_64-3.7/mmcv/ops/csrc
creating /tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/build/temp.linux-x86_64-3.7/mmcv/ops/csrc/pytorch
Emitting ninja build file /tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/build/temp.linux-x86_64-3.7/build.ninja...
Compiling objects...
Using envvar MAX_JOBS (4) as the number of workers...
[1/34] /usr/local/cuda/bin/nvcc -DMMCV_WITH_CUDA -I/tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/mmcv/ops/csrc -I/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/torch/include -I/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/torch/include/torch/csrc/api/include -I/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/torch/include/TH -I/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/torch/include/THC -I/usr/local/cuda/include -I/home/ajay/anaconda3/envs/AlignPS/include/python3.7m -c -c /tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/mmcv/ops/csrc/pytorch/roi_pool_cuda.cu -o /tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/build/temp.linux-x86_64-3.7/mmcv/ops/csrc/pytorch/roi_pool_cuda.o -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr --compiler-options ''"'"'-fPIC'"'"'' -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=_ext -D_GLIBCXX_USE_CXX11_ABI=0 -gencode=arch=compute_61,code=sm_61 -std=c++14
FAILED: /tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/build/temp.linux-x86_64-3.7/mmcv/ops/csrc/pytorch/roi_pool_cuda.o
/usr/local/cuda/bin/nvcc -DMMCV_WITH_CUDA -I/tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/mmcv/ops/csrc -I/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/torch/include -I/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/torch/include/torch/csrc/api/include -I/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/torch/include/TH -I/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/torch/include/THC -I/usr/local/cuda/include -I/home/ajay/anaconda3/envs/AlignPS/include/python3.7m -c -c /tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/mmcv/ops/csrc/pytorch/roi_pool_cuda.cu -o /tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/build/temp.linux-x86_64-3.7/mmcv/ops/csrc/pytorch/roi_pool_cuda.o -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr --compiler-options ''"'"'-fPIC'"'"'' -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=_ext -D_GLIBCXX_USE_CXX11_ABI=0 -gencode=arch=compute_61,code=sm_61 -std=c++14
/usr/include/c++/7/bits/basic_string.tcc: In instantiation of ‘static std::basic_string<_CharT, _Traits, _Alloc>::_Rep* std::basic_string<_CharT, _Traits, _Alloc>::_Rep::_S_create(std::basic_string<_CharT, _Traits, _Alloc>::size_type, std::basic_string<_CharT, _Traits, _Alloc>::size_type, const _Alloc&) [with _CharT = char16_t; _Traits = std::char_traits<char16_t>; _Alloc = std::allocator<char16_t>; std::basic_string<_CharT, _Traits, _Alloc>::size_type = long unsigned int]’:
/usr/include/c++/7/bits/basic_string.tcc:578:28: required from ‘static _CharT* std::basic_string<_CharT, _Traits, _Alloc>::_S_construct(_InIterator, _InIterator, const _Alloc&, std::forward_iterator_tag) [with _FwdIterator = const char16_t*; _CharT = char16_t; _Traits = std::char_traits<char16_t>; _Alloc = std::allocator<char16_t>]’
/usr/include/c++/7/bits/basic_string.h:5042:20: required from ‘static _CharT* std::basic_string<_CharT, _Traits, _Alloc>::_S_construct_aux(_InIterator, _InIterator, const _Alloc&, std::__false_type) [with _InIterator = const char16_t*; _CharT = char16_t; _Traits = std::char_traits<char16_t>; _Alloc = std::allocator<char16_t>]’
/usr/include/c++/7/bits/basic_string.h:5063:24: required from ‘static _CharT* std::basic_string<_CharT, _Traits, _Alloc>::_S_construct(_InIterator, _InIterator, const _Alloc&) [with _InIterator = const char16_t*; _CharT = char16_t; _Traits = std::char_traits<char16_t>; _Alloc = std::allocator<char16_t>]’
/usr/include/c++/7/bits/basic_string.tcc:656:134: required from ‘std::basic_string<_CharT, _Traits, _Alloc>::basic_string(const _CharT*, std::basic_string<_CharT, _Traits, _Alloc>::size_type, const _Alloc&) [with _CharT = char16_t; _Traits = std::char_traits<char16_t>; _Alloc = std::allocator<char16_t>; std::basic_string<_CharT, _Traits, _Alloc>::size_type = long unsigned int]’
/usr/include/c++/7/bits/basic_string.h:6688:95: required from here
/usr/include/c++/7/bits/basic_string.tcc:1067:16: error: cannot call member function ‘void std::basic_string<_CharT, _Traits, _Alloc>::_Rep::_M_set_sharable() [with _CharT = char16_t; _Traits = std::char_traits<char16_t>; _Alloc = std::allocator<char16_t>]’ without object
__p->_M_set_sharable();
~~~~~~~~~^~
/usr/include/c++/7/bits/basic_string.tcc: In instantiation of ‘static std::basic_string<_CharT, _Traits, _Alloc>::_Rep* std::basic_string<_CharT, _Traits, _Alloc>::_Rep::_S_create(std::basic_string<_CharT, _Traits, _Alloc>::size_type, std::basic_string<_CharT, _Traits, _Alloc>::size_type, const _Alloc&) [with _CharT = char32_t; _Traits = std::char_traits<char32_t>; _Alloc = std::allocator<char32_t>; std::basic_string<_CharT, _Traits, _Alloc>::size_type = long unsigned int]’:
/usr/include/c++/7/bits/basic_string.tcc:578:28: required from ‘static _CharT* std::basic_string<_CharT, _Traits, _Alloc>::_S_construct(_InIterator, _InIterator, const _Alloc&, std::forward_iterator_tag) [with _FwdIterator = const char32_t*; _CharT = char32_t; _Traits = std::char_traits<char32_t>; _Alloc = std::allocator<char32_t>]’
/usr/include/c++/7/bits/basic_string.h:5042:20: required from ‘static _CharT* std::basic_string<_CharT, _Traits, _Alloc>::_S_construct_aux(_InIterator, _InIterator, const _Alloc&, std::__false_type) [with _InIterator = const char32_t*; _CharT = char32_t; _Traits = std::char_traits<char32_t>; _Alloc = std::allocator<char32_t>]’
/usr/include/c++/7/bits/basic_string.h:5063:24: required from ‘static _CharT* std::basic_string<_CharT, _Traits, _Alloc>::_S_construct(_InIterator, _InIterator, const _Alloc&) [with _InIterator = const char32_t*; _CharT = char32_t; _Traits = std::char_traits<char32_t>; _Alloc = std::allocator<char32_t>]’
/usr/include/c++/7/bits/basic_string.tcc:656:134: required from ‘std::basic_string<_CharT, _Traits, _Alloc>::basic_string(const _CharT*, std::basic_string<_CharT, _Traits, _Alloc>::size_type, const _Alloc&) [with _CharT = char32_t; _Traits = std::char_traits<char32_t>; _Alloc = std::allocator<char32_t>; std::basic_string<_CharT, _Traits, _Alloc>::size_type = long unsigned int]’
/usr/include/c++/7/bits/basic_string.h:6693:95: required from here
/usr/include/c++/7/bits/basic_string.tcc:1067:16: error: cannot call member function ‘void std::basic_string<_CharT, _Traits, _Alloc>::_Rep::_M_set_sharable() [with _CharT = char32_t; _Traits = std::char_traits<char32_t>; _Alloc = std::allocator<char32_t>]’ without object
[2/34] /usr/local/cuda/bin/nvcc -DMMCV_WITH_CUDA -I/tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/mmcv/ops/csrc -I/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/torch/include -I/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/torch/include/torch/csrc/api/include -I/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/torch/include/TH -I/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/torch/include/THC -I/usr/local/cuda/include -I/home/ajay/anaconda3/envs/AlignPS/include/python3.7m -c -c /tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/mmcv/ops/csrc/pytorch/carafe_cuda.cu -o /tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/build/temp.linux-x86_64-3.7/mmcv/ops/csrc/pytorch/carafe_cuda.o -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr --compiler-options ''"'"'-fPIC'"'"'' -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=_ext -D_GLIBCXX_USE_CXX11_ABI=0 -gencode=arch=compute_61,code=sm_61 -std=c++14
FAILED: /tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/build/temp.linux-x86_64-3.7/mmcv/ops/csrc/pytorch/carafe_cuda.o
/usr/local/cuda/bin/nvcc -DMMCV_WITH_CUDA -I/tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/mmcv/ops/csrc -I/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/torch/include -I/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/torch/include/torch/csrc/api/include -I/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/torch/include/TH -I/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/torch/include/THC -I/usr/local/cuda/include -I/home/ajay/anaconda3/envs/AlignPS/include/python3.7m -c -c /tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/mmcv/ops/csrc/pytorch/carafe_cuda.cu -o /tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/build/temp.linux-x86_64-3.7/mmcv/ops/csrc/pytorch/carafe_cuda.o -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr --compiler-options ''"'"'-fPIC'"'"'' -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=_ext -D_GLIBCXX_USE_CXX11_ABI=0 -gencode=arch=compute_61,code=sm_61 -std=c++14
/usr/include/c++/7/bits/basic_string.tcc: In instantiation of ‘static std::basic_string<_CharT, _Traits, _Alloc>::_Rep* std::basic_string<_CharT, _Traits, _Alloc>::_Rep::_S_create(std::basic_string<_CharT, _Traits, _Alloc>::size_type, std::basic_string<_CharT, _Traits, _Alloc>::size_type, const _Alloc&) [with _CharT = char16_t; _Traits = std::char_traits<char16_t>; _Alloc = std::allocator<char16_t>; std::basic_string<_CharT, _Traits, _Alloc>::size_type = long unsigned int]’:
/usr/include/c++/7/bits/basic_string.tcc:578:28: required from ‘static _CharT* std::basic_string<_CharT, _Traits, _Alloc>::_S_construct(_InIterator, _InIterator, const _Alloc&, std::forward_iterator_tag) [with _FwdIterator = const char16_t*; _CharT = char16_t; _Traits = std::char_traits<char16_t>; _Alloc = std::allocator<char16_t>]’
/usr/include/c++/7/bits/basic_string.h:5042:20: required from ‘static _CharT* std::basic_string<_CharT, _Traits, _Alloc>::_S_construct_aux(_InIterator, _InIterator, const _Alloc&, std::__false_type) [with _InIterator = const char16_t*; _CharT = char16_t; _Traits = std::char_traits<char16_t>; _Alloc = std::allocator<char16_t>]’
/usr/include/c++/7/bits/basic_string.h:5063:24: required from ‘static _CharT* std::basic_string<_CharT, _Traits, _Alloc>::_S_construct(_InIterator, _InIterator, const _Alloc&) [with _InIterator = const char16_t*; _CharT = char16_t; _Traits = std::char_traits<char16_t>; _Alloc = std::allocator<char16_t>]’
/usr/include/c++/7/bits/basic_string.tcc:656:134: required from ‘std::basic_string<_CharT, _Traits, _Alloc>::basic_string(const _CharT*, std::basic_string<_CharT, _Traits, _Alloc>::size_type, const _Alloc&) [with _CharT = char16_t; _Traits = std::char_traits<char16_t>; _Alloc = std::allocator<char16_t>; std::basic_string<_CharT, _Traits, _Alloc>::size_type = long unsigned int]’
/usr/include/c++/7/bits/basic_string.h:6688:95: required from here
/usr/include/c++/7/bits/basic_string.tcc:1067:16: error: cannot call member function ‘void std::basic_string<_CharT, _Traits, _Alloc>::_Rep::_M_set_sharable() [with _CharT = char16_t; _Traits = std::char_traits<char16_t>; _Alloc = std::allocator<char16_t>]’ without object
__p->_M_set_sharable();
~~~~~~~~~^~
/usr/include/c++/7/bits/basic_string.tcc: In instantiation of ‘static std::basic_string<_CharT, _Traits, _Alloc>::_Rep* std::basic_string<_CharT, _Traits, _Alloc>::_Rep::_S_create(std::basic_string<_CharT, _Traits, _Alloc>::size_type, std::basic_string<_CharT, _Traits, _Alloc>::size_type, const _Alloc&) [with _CharT = char32_t; _Traits = std::char_traits<char32_t>; _Alloc = std::allocator<char32_t>; std::basic_string<_CharT, _Traits, _Alloc>::size_type = long unsigned int]’:
/usr/include/c++/7/bits/basic_string.tcc:578:28: required from ‘static _CharT* std::basic_string<_CharT, _Traits, _Alloc>::_S_construct(_InIterator, _InIterator, const _Alloc&, std::forward_iterator_tag) [with _FwdIterator = const char32_t*; _CharT = char32_t; _Traits = std::char_traits<char32_t>; _Alloc = std::allocator<char32_t>]’
/usr/include/c++/7/bits/basic_string.h:5042:20: required from ‘static _CharT* std::basic_string<_CharT, _Traits, _Alloc>::_S_construct_aux(_InIterator, _InIterator, const _Alloc&, std::__false_type) [with _InIterator = const char32_t*; _CharT = char32_t; _Traits = std::char_traits<char32_t>; _Alloc = std::allocator<char32_t>]’
/usr/include/c++/7/bits/basic_string.h:5063:24: required from ‘static _CharT* std::basic_string<_CharT, _Traits, _Alloc>::_S_construct(_InIterator, _InIterator, const _Alloc&) [with _InIterator = const char32_t*; _CharT = char32_t; _Traits = std::char_traits<char32_t>; _Alloc = std::allocator<char32_t>]’
/usr/include/c++/7/bits/basic_string.tcc:656:134: required from ‘std::basic_string<_CharT, _Traits, _Alloc>::basic_string(const _CharT*, std::basic_string<_CharT, _Traits, _Alloc>::size_type, const _Alloc&) [with _CharT = char32_t; _Traits = std::char_traits<char32_t>; _Alloc = std::allocator<char32_t>; std::basic_string<_CharT, _Traits, _Alloc>::size_type = long unsigned int]’
/usr/include/c++/7/bits/basic_string.h:6693:95: required from here
/usr/include/c++/7/bits/basic_string.tcc:1067:16: error: cannot call member function ‘void std::basic_string<_CharT, _Traits, _Alloc>::_Rep::_M_set_sharable() [with _CharT = char32_t; _Traits = std::char_traits<char32_t>; _Alloc = std::allocator<char32_t>]’ without object
[3/34] c++ -MMD -MF /tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/build/temp.linux-x86_64-3.7/mmcv/ops/csrc/pytorch/roi_align.o.d -pthread -B /home/ajay/anaconda3/envs/AlignPS/compiler_compat -Wl,--sysroot=/ -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC -DMMCV_WITH_CUDA -I/tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/mmcv/ops/csrc -I/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/torch/include -I/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/torch/include/torch/csrc/api/include -I/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/torch/include/TH -I/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/torch/include/THC -I/usr/local/cuda/include -I/home/ajay/anaconda3/envs/AlignPS/include/python3.7m -c -c /tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/mmcv/ops/csrc/pytorch/roi_align.cpp -o /tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/build/temp.linux-x86_64-3.7/mmcv/ops/csrc/pytorch/roi_align.o -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=_ext -D_GLIBCXX_USE_CXX11_ABI=0 -std=c++14
cc1plus: warning: command line option ‘-Wstrict-prototypes’ is valid for C/ObjC but not for C++
In file included from /home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/torch/include/ATen/Parallel.h:149:0,
from /home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/utils.h:3,
from /home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h:5,
from /home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/nn.h:3,
from /home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/all.h:12,
from /home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/torch/include/torch/extension.h:4,
from /tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/mmcv/ops/csrc/pytorch_cpp_helper.hpp:3,
from /tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/mmcv/ops/csrc/pytorch/roi_align.cpp:1:
/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/torch/include/ATen/ParallelOpenMP.h:84:0: warning: ignoring #pragma omp parallel [-Wunknown-pragmas]
#pragma omp parallel for if ((end - begin) >= grain_size)
[4/34] c++ -MMD -MF /tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/build/temp.linux-x86_64-3.7/mmcv/ops/csrc/pytorch/sync_bn.o.d -pthread -B /home/ajay/anaconda3/envs/AlignPS/compiler_compat -Wl,--sysroot=/ -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC -DMMCV_WITH_CUDA -I/tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/mmcv/ops/csrc -I/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/torch/include -I/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/torch/include/torch/csrc/api/include -I/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/torch/include/TH -I/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/torch/include/THC -I/usr/local/cuda/include -I/home/ajay/anaconda3/envs/AlignPS/include/python3.7m -c -c /tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/mmcv/ops/csrc/pytorch/sync_bn.cpp -o /tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/build/temp.linux-x86_64-3.7/mmcv/ops/csrc/pytorch/sync_bn.o -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=_ext -D_GLIBCXX_USE_CXX11_ABI=0 -std=c++14
cc1plus: warning: command line option ‘-Wstrict-prototypes’ is valid for C/ObjC but not for C++
In file included from /home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/torch/include/ATen/Parallel.h:149:0,
from /home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/utils.h:3,
from /home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h:5,
from /home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/nn.h:3,
from /home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/all.h:12,
from /home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/torch/include/torch/extension.h:4,
from /tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/mmcv/ops/csrc/pytorch_cpp_helper.hpp:3,
from /tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/mmcv/ops/csrc/pytorch/sync_bn.cpp:1:
/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/torch/include/ATen/ParallelOpenMP.h:84:0: warning: ignoring #pragma omp parallel [-Wunknown-pragmas]
#pragma omp parallel for if ((end - begin) >= grain_size)
ninja: build stopped: subcommand failed.
Traceback (most recent call last):
File "/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/torch/utils/cpp_extension.py", line 1522, in _run_ninja_build
env=env)
File "/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/subprocess.py", line 512, in run
output=stdout, stderr=stderr)
subprocess.CalledProcessError: Command '['ninja', '-v', '-j', '4']' returned non-zero exit status 1.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "<string>", line 1, in <module>
File "/tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/setup.py", line 219, in <module>
zip_safe=False)
File "/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/setuptools/__init__.py", line 153, in setup
return distutils.core.setup(**attrs)
File "/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/distutils/core.py", line 148, in setup
dist.run_commands()
File "/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/distutils/dist.py", line 966, in run_commands
self.run_command(cmd)
File "/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/distutils/dist.py", line 985, in run_command
cmd_obj.run()
File "/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/setuptools/command/install.py", line 61, in run
return orig.install.run(self)
File "/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/distutils/command/install.py", line 545, in run
self.run_command('build')
File "/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/distutils/cmd.py", line 313, in run_command
self.distribution.run_command(command)
File "/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/distutils/dist.py", line 985, in run_command
cmd_obj.run()
File "/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/distutils/command/build.py", line 135, in run
self.run_command(cmd_name)
File "/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/distutils/cmd.py", line 313, in run_command
self.distribution.run_command(command)
File "/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/distutils/dist.py", line 985, in run_command
cmd_obj.run()
File "/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/setuptools/command/build_ext.py", line 79, in run
_build_ext.run(self)
File "/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/distutils/command/build_ext.py", line 340, in run
self.build_extensions()
File "/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/torch/utils/cpp_extension.py", line 653, in build_extensions
build_ext.build_extensions(self)
File "/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/distutils/command/build_ext.py", line 449, in build_extensions
self._build_extensions_serial()
File "/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/distutils/command/build_ext.py", line 474, in _build_extensions_serial
self.build_extension(ext)
File "/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/setuptools/command/build_ext.py", line 196, in build_extension
_build_ext.build_extension(self, ext)
File "/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/distutils/command/build_ext.py", line 534, in build_extension
depends=ext.depends)
File "/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/torch/utils/cpp_extension.py", line 482, in unix_wrap_ninja_compile
with_cuda=with_cuda)
File "/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/torch/utils/cpp_extension.py", line 1238, in _write_ninja_file_and_compile_objects
error_prefix='Error compiling objects for extension')
File "/home/ajay/anaconda3/envs/AlignPS/lib/python3.7/site-packages/torch/utils/cpp_extension.py", line 1538, in _run_ninja_build
raise RuntimeError(message) from e
RuntimeError: Error compiling objects for extension
----------------------------------------
ERROR: Command errored out with exit status 1: /home/ajay/anaconda3/envs/AlignPS/bin/python -u -c 'import sys, setuptools, tokenize; sys.argv[0] = '"'"'/tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/setup.py'"'"'; __file__='"'"'/tmp/pip-install-xxdqo6qv/mmcv-full_4dc33eb84f094f3ca1f5d4b2a1700673/setup.py'"'"';f=getattr(tokenize, '"'"'open'"'"', open)(__file__);code=f.read().replace('"'"'\r\n'"'"', '
Bug fix
If you have already identified the reason, you can provide the information here. If you are willing to create a PR to fix it, please also leave a comment here and that would be much appreciated!
Different Configuration for CUHK-SYSU and PRW
Thanks for your great work! I find that the training configuration for CUHK-SYSU and PRW differs a lot. As shown in their config files, the code employ different type of bbox_head and weight_decay. Would you like to explain the reason behind such an implementation? Thanks a lot.
when i test,it takes error
(open-mmlab) goo@goo-Z390-GAMING-X:~/yx/AlignPS$ sh run_test.sh
loading annotations into memory...
Done (t=0.12s)
creating index...
index created!
/home/goo/anaconda3/envs/open-mmlab/lib/python3.7/site-packages/mmcv/cnn/bricks/conv_module.py:100: UserWarning: ConvModule has norm and bias at the same time
warnings.warn('ConvModule has norm and bias at the same time')
[ ] 0/6978, elapsed: 0s, ETA:/home/goo/anaconda3/envs/open-mmlab/lib/python3.7/site-packages/torch/nn/functional.py:3328: UserWarning: nn.functional.upsample is deprecated. Use nn.functional.interpolate instead.
warnings.warn("nn.functional.upsample is deprecated. Use nn.functional.interpolate instead.")
/home/goo/anaconda3/envs/open-mmlab/lib/python3.7/site-packages/torch/nn/functional.py:3458: UserWarning: Default upsampling behavior when mode=bilinear is changed to align_corners=False since 0.4.0. Please specify align_corners=True if the old behavior is desired. See the documentation of nn.Upsample for details.
"See the documentation of nn.Upsample for details.".format(mode)
Traceback (most recent call last):
File "./tools/test.py", line 226, in
main()
File "./tools/test.py", line 187, in main
args.gpu_collect)
File "/home/goo/yx/AlignPS/mmdet/apis/test.py", line 98, in multi_gpu_test
result = model(return_loss=False, rescale=True, **data)
File "/home/goo/anaconda3/envs/open-mmlab/lib/python3.7/site-packages/torch/nn/modules/module.py", line 889, in _call_impl
result = self.forward(*input, **kwargs)
File "/home/goo/anaconda3/envs/open-mmlab/lib/python3.7/site-packages/torch/nn/parallel/distributed.py", line 705, in forward
output = self.module(*inputs[0], **kwargs[0])
File "/home/goo/anaconda3/envs/open-mmlab/lib/python3.7/site-packages/torch/nn/modules/module.py", line 889, in _call_impl
result = self.forward(*input, **kwargs)
File "/home/goo/yx/AlignPS/mmdet/core/fp16/decorators.py", line 51, in new_func
return old_func(*args, **kwargs)
File "/home/goo/yx/AlignPS/mmdet/models/detectors/base.py", line 170, in forward
return self.forward_test(img, img_metas, **kwargs)
File "/home/goo/yx/AlignPS/mmdet/models/detectors/base.py", line 147, in forward_test
return self.simple_test(imgs[0], img_metas[0], **kwargs)
File "/home/goo/yx/AlignPS/mmdet/models/detectors/single_stage_reid.py", line 118, in simple_test
*outs, img_metas, rescale=rescale)
File "/home/goo/yx/AlignPS/mmdet/core/fp16/decorators.py", line 131, in new_func
return old_func(*args, **kwargs)
File "/home/goo/yx/AlignPS/mmdet/models/dense_heads/fcos_reid_head_focal_sub_triqueue.py", line 454, in get_bboxes
img_shape = img_metas[img_id]['img_shape']
TypeError: 'DataContainer' object is not subscriptable
Killing subprocess 6428
Traceback (most recent call last):
File "/home/goo/anaconda3/envs/open-mmlab/lib/python3.7/runpy.py", line 193, in _run_module_as_main
"main", mod_spec)
File "/home/goo/anaconda3/envs/open-mmlab/lib/python3.7/runpy.py", line 85, in _run_code
exec(code, run_globals)
File "/home/goo/anaconda3/envs/open-mmlab/lib/python3.7/site-packages/torch/distributed/launch.py", line 340, in
main()
File "/home/goo/anaconda3/envs/open-mmlab/lib/python3.7/site-packages/torch/distributed/launch.py", line 326, in main
sigkill_handler(signal.SIGTERM, None) # not coming back
File "/home/goo/anaconda3/envs/open-mmlab/lib/python3.7/site-packages/torch/distributed/launch.py", line 301, in sigkill_handler
raise subprocess.CalledProcessError(returncode=last_return_code, cmd=cmd)
subprocess.CalledProcessError: Command '['/home/goo/anaconda3/envs/open-mmlab/bin/python', '-u', './tools/test.py', '--local_rank=0', './configs/fcos/fcos_center-normbbox-centeronreg-giou_r50_caffe_fpn_gn-head_dcn_4x4_1x_cuhk_reid_1500_stage1_fpncat_dcn_epoch24_multiscale_focal_x4_bg-2_lconv3dcn_sub_triqueue_dcn0.py', 'work_dirs/fcos_center-normbbox-centeronreg-giou_r50_caffe_fpn_gn-head_dcn_4x4_1x_cuhk_reid_1500_stage1_fpncat_dcn_epoch24_multiscale_focal_x4_bg-2_lconv3dcn_sub_triqueue_dcn0/epoch_24.pth', '--launcher', 'pytorch', '--out', 'work_dirs/fcos_center-normbbox-centeronreg-giou_r50_caffe_fpn_gn-head_dcn_4x4_1x_cuhk_reid_1500_stage1_fpncat_dcn_epoch24_multiscale_focal_x4_bg-2_lconv3dcn_sub_triqueue_dcn0/results_1000.pkl']' returned non-zero exit status 1.
Traceback (most recent call last):
File "./tools/test_results.py", line 75, in
with open(os.path.join(results_path, 'results_1000.pkl'), 'rb') as fid:
FileNotFoundError: [Errno 2] No such file or directory: '/home/goo/yx/AlignPS/work_dirs/fcos_center-normbbox-centeronreg-giou_r50_caffe_fpn_gn-head_dcn_4x4_1x_cuhk_reid_1500_stage1_fpncat_dcn_epoch24_multiscale_focal_x4_bg-2_lconv3dcn_sub_triqueue_dcn0/results_1000.pkl'
fcos_center-normbbox-centeronreg-giou_r50_caffe_fpn_gn-head_dcn_4x4_1x_cuhk_reid_1500_stage1_fpncat_dcn_epoch24_multiscale_focal_x4_bg-2_lconv3dcn_sub_triqueue_dcn0
I don't know why .Maybe you can help me .Thank you !
Running INference error
@erjanmx @daodaofr hi thanks for open sourcing the code base, i have a few queries on running the inference
-
I have downloaded the dataset of Chuk-sys and i have only these folders
-
you have mentioned changing the path of the data in the config file "config file L3, L38, L43, L48" i do not have any annotations available with me so how to generate json file
Please share your thoughts
The effect of subtracting the mean value of p3
Hi, thanks for your excellent work. When I try to reimplement the result of scale alignment, I find you substract the mean value of feature map p3 in mmdet/models/dense_heads/fcos_reid_head_focal_sub_triqueue.py as follow:
h, w = feats[0].shape[2], feats[0].shape[3]
mean_value = nn.functional.adaptive_avg_pool2d(feats[0], 1)
mean_value = F.upsample(input=mean_value, size=(h, w), mode='bilinear')
feats[0] = feats[0] - mean_value
And I remove this part, the performance decreases to mAP = 90.82%. I wonder how it works and if I need to add this operation in other levels of feature map.
installation using docker file
i am currently testing to build the image using docker in a virtual machine, if so does it require any gpu usage?
scale alignment
1.我理解的对吗？
1.Am I right to understand that?
假如同一个人，他的大图和小图分别对应不同层次的特征图。不同的层次特征图肯定不完全一样。同一个人不同大小的图片的特征竟然在不同的特征图上不一样，很可能认为为不是一个人。如果query是个小图，是高层次的特征，gallery是大图，使用低层次的特，由于两个特征来自不同尺度的特征图，因此有可能导致特征向量点乘不正常，从而造成误判。所以你只用了一层特征图。
If it is the same person, his large picture and small picture correspond to different levels of feature maps. Different hierarchical feature maps are certainly not exactly the same. The characteristics of different size pictures of the same person are different on different feature maps. Probably think not as a person. If the query is a small graph, which is a high-level feature, and the gallery is a large graph, using a low-level feature, because the two features come from a feature map of different scales, it is possible to cause the feature vector point multiplication is not normal, resulting in misjudgment. So you only use one layer of feature maps.
2.有没有好的方法，来解决因为两个特征来自不同特征图，而导致误判的问题呢，这样就不用删掉其他层次的FPN了，这样的话就能进一步提高了。
很期待你的进一步科研成果。
2.Is there a good way to solve the problem of misjudgment because the two features come from different feature maps, so that there is no need to delete other levels of FPN, so that it can be further improved.
I look forward to your further research results
Issue with results_1000.pkl when running run_test_prw.sh!
Hello, I am getting error like this when I want to starting testing the model with pth file.
" FileNotFoundError: [Errno 2] No such file or directory: 'work_dirs/prw_dcn_base_focal_labelnorm_sub_ldcn_fg15_wd7-4/results_1000.pkl'"
There is a dir work_dirs/prw_dcn_base_focal_labelnorm_sub_ldcn_fg15_wd7-4/
created when I run the training.
Do I need to wait until the training finish to obtain "results_1000.pkl"??
or How can I get results_1000.pkl?
Thanks in advance.
Where can i get the checkpoints files please?
Whether to support distributed training
hello，thanks for your project. i want to know whether to support distributed training. And what should i do to make it support distributed training.
run_test_prw.sh TypeError: 'DataContainer' object is not subscriptable
run_test_prw.sh but cmd shows: TypeError: 'DataContainer' object is not subscriptable
my env: torch-1.8.1+cu111 torchaudio-0.8.1 torchvision-0.9.1+cu111
mmcv-full=1.1.5
more info in cmd:
(pytorch_hbs) amax@amax:~/Desktop/personsearch/AlignPS$ sh run_test_prw.sh
:228: RuntimeWarning: scipy._lib.messagestream.MessageStream size changed, may indicate binary incompatibility. Expected 56 from C header, got 64 from PyObject
loading annotations into memory...
Done (t=0.12s)
creating index...
index created!
/home/amax/anaconda3/envs/pytorch_hbs/lib/python3.9/site-packages/mmcv/cnn/bricks/conv_module.py:100: UserWarning: ConvModule has norm and bias at the same time
warnings.warn('ConvModule has norm and bias at the same time')
[ ] 0/6112, elapsed: 0s, ETA::228: RuntimeWarning: scipy._lib.messagestream.MessageStream size changed, may indicate binary incompatibility. Expected 56 from C header, got 64 from PyObject
:228: RuntimeWarning: scipy._lib.messagestream.MessageStream size changed, may indicate binary incompatibility. Expected 56 from C header, got 64 from PyObject
:228: RuntimeWarning: scipy._lib.messagestream.MessageStream size changed, may indicate binary incompatibility. Expected 56 from C header, got 64 from PyObject
:228: RuntimeWarning: scipy._lib.messagestream.MessageStream size changed, may indicate binary incompatibility. Expected 56 from C header, got 64 from PyObject
/home/amax/anaconda3/envs/pytorch_hbs/lib/python3.9/site-packages/torch/nn/functional.py:3328: UserWarning: nn.functional.upsample is deprecated. Use nn.functional.interpolate instead.
warnings.warn("nn.functional.upsample is deprecated. Use nn.functional.interpolate instead.")
/home/amax/anaconda3/envs/pytorch_hbs/lib/python3.9/site-packages/torch/nn/functional.py:3454: UserWarning: Default upsampling behavior when mode=bilinear is changed to align_corners=False since 0.4.0. Please specify align_corners=True if the old behavior is desired. See the documentation of nn.Upsample for details.
warnings.warn(
Traceback (most recent call last):
File "/home/amax/Desktop/personsearch/AlignPS/./tools/test.py", line 226, in
main()
File "/home/amax/Desktop/personsearch/AlignPS/./tools/test.py", line 186, in main
outputs = multi_gpu_test(model, data_loader, args.tmpdir,
File "/home/amax/Desktop/personsearch/AlignPS/mmdet/apis/test.py", line 98, in multi_gpu_test
result = model(return_loss=False, rescale=True, **data)
File "/home/amax/anaconda3/envs/pytorch_hbs/lib/python3.9/site-packages/torch/nn/modules/module.py", line 889, in _call_impl
result = self.forward(*input, **kwargs)
File "/home/amax/anaconda3/envs/pytorch_hbs/lib/python3.9/site-packages/torch/nn/parallel/distributed.py", line 705, in forward
output = self.module(*inputs[0], **kwargs[0])
File "/home/amax/anaconda3/envs/pytorch_hbs/lib/python3.9/site-packages/torch/nn/modules/module.py", line 889, in _call_impl
result = self.forward(*input, **kwargs)
File "/home/amax/Desktop/personsearch/AlignPS/mmdet/core/fp16/decorators.py", line 51, in new_func
return old_func(*args, **kwargs)
File "/home/amax/Desktop/personsearch/AlignPS/mmdet/models/detectors/base.py", line 170, in forward
return self.forward_test(img, img_metas, **kwargs)
File "/home/amax/Desktop/personsearch/AlignPS/mmdet/models/detectors/base.py", line 147, in forward_test
return self.simple_test(imgs[0], img_metas[0], **kwargs)
File "/home/amax/Desktop/personsearch/AlignPS/mmdet/models/detectors/single_stage_reid.py", line 117, in simple_test
bbox_list = self.bbox_head.get_bboxes(
File "/home/amax/Desktop/personsearch/AlignPS/mmdet/core/fp16/decorators.py", line 131, in new_func
return old_func(*args, **kwargs)
File "/home/amax/Desktop/personsearch/AlignPS/mmdet/models/dense_heads/fcos_reid_head_focal_oim_sub.py", line 456, in get_bboxes
img_shape = img_metas[img_id]['img_shape']
TypeError: 'DataContainer' object is not subscriptable
No such file or directory: '....../annotation/test/train_test/TestG100.mat'
when i run 'bash run_test.sh', I can get results_1000.pkl successfully. However, there is a FileNotFoundError after that. There are not data, of which the structrue is like '.mat' in CUHK-SYSU. I will appreciate it if you can help.
Traceback (most recent call last):
File "/yes/lib/python3.7/site-packages/scipy/io/matlab/mio.py", line 33, in _open_file
return open(file_like, 'rb'), True
FileNotFoundError: [Errno 2] No such file or directory: '/data/CUHK-SYSU/annotation/test/train_test/TestG100.mat'
KeyError: 'FCOSReid is not in the detector registry'
Thanks for sharing your code! I am trying run_train.sh but receive the following error (in short: KeyError: 'FCOSReid is not in the detector registry'). Do you have any suggestions on how to resolve this? Info on my environment is at the bottom.
By the way, I re-scaled the images, set it to a single sample per gpu, and reduced the total epochs to help it run on a smaller GPU.
Contents of run_train.sh:
# CUHK-SYSU, AlignPS
python tools/train.py configs/fcos/fcos_center-normbbox-centeronreg-giou_r50_caffe_fpn_gn-head_dcn_4x4_1x_cuhk_reid_1500_stage1_fpncat_dcn_epoch24_multiscale_focal_x4_bg-2_lconv3dcn_sub_triqueue_dcn0.py --gpu-ids 0 --no-validate
Error message:
AlignPS$ sh run_train.sh
2021-06-03 16:57:18,310 - mmdet - INFO - Environment info:
------------------------------------------------------------
sys.platform: linux
Python: 3.7.7 (default, Mar 26 2020, 15:48:22) [GCC 7.3.0]
CUDA available: True
GPU 0: Tesla K80
CUDA_HOME: /usr/local/cuda-10.1
NVCC: Cuda compilation tools, release 10.1, V10.1.243
GCC: gcc (Ubuntu 5.4.0-6ubuntu1~16.04.12) 5.4.0 20160609
PyTorch: 1.7.0
PyTorch compiling details: PyTorch built with:
- GCC 7.3
- C++ Version: 201402
- Intel(R) Math Kernel Library Version 2020.0.0 Product Build 20191122 for Intel(R) 64 architecture applications
- Intel(R) MKL-DNN v1.6.0 (Git Hash 5ef631a030a6f73131c77892041042805a06064f)
- OpenMP 201511 (a.k.a. OpenMP 4.5)
- NNPACK is enabled
- CPU capability usage: AVX2
- CUDA Runtime 10.1
- NVCC architecture flags: -gencode;arch=compute_37,code=sm_37;-gencode;arch=compute_50,code=sm_50;-gencode;arch=compute_60,code=sm_60;-gencode;arch=compute_61,code=sm_61;-gencode;arch=compute_70,code=sm_70;-gencode;arch=compute_75,code=sm_75;-gencode;arch=compute_37,code=compute_37
- CuDNN 7.6.3
- Magma 2.5.2
- Build settings: BLAS=MKL, BUILD_TYPE=Release, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -fopenmp -DNDEBUG -DUSE_FBGEMM -DUSE_QNNPACK -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DUSE_VULKAN_WRAPPER -O2 -fPIC -Wno-narrowing -Wall -Wextra -Werror=return-type -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-sign-compare -Wno-unused-parameter -Wno-unused-variable -Wno-unused-function -Wno-unused-result -Wno-unused-local-typedefs -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Wno-stringop-overflow, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, USE_CUDA=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=ON, USE_MKLDNN=ON, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=ON, USE_OPENMP=ON,
TorchVision: 0.8.0
OpenCV: 4.5.2
MMCV: 1.2.0
MMCV Compiler: GCC 7.3
MMCV CUDA Compiler: 10.1
MMDetection: 2.7.0+aa244c1
------------------------------------------------------------
2021-06-03 16:57:19,495 - mmdet - INFO - Distributed training: False
2021-06-03 16:57:20,764 - mmdet - INFO - Config:
dataset_type = 'CuhkDataset'
data_root = '.../Datasets/CUHK-SYSU/'
img_norm_cfg = dict(
mean=[103.53, 116.28, 123.675], std=[1.0, 1.0, 1.0], to_rgb=False)
train_pipeline = [
dict(type='LoadImageFromFile'),
dict(type='LoadAnnotations', with_bbox=True),
dict(
type='Resize',
img_scale=[(333, 200), (500, 300), (666, 400), (750, 450), (833, 500),
(1000, 600)],
multiscale_mode='value',
keep_ratio=True),
dict(type='RandomFlip', flip_ratio=0.5),
dict(
type='Normalize',
mean=[103.53, 116.28, 123.675],
std=[1.0, 1.0, 1.0],
to_rgb=False),
dict(type='Pad', size_divisor=32),
dict(type='DefaultFormatBundle'),
dict(type='Collect', keys=['img', 'gt_bboxes', 'gt_labels', 'gt_ids'])
]
test_pipeline = [
dict(type='LoadImageFromFile'),
dict(
type='MultiScaleFlipAug',
img_scale=(750, 450),
flip=False,
transforms=[
dict(type='Resize', keep_ratio=True),
dict(type='RandomFlip'),
dict(
type='Normalize',
mean=[103.53, 116.28, 123.675],
std=[1.0, 1.0, 1.0],
to_rgb=False),
dict(type='Pad', size_divisor=32),
dict(type='ImageToTensor', keys=['img']),
dict(type='Collect', keys=['img'])
])
]
data = dict(
samples_per_gpu=1,
workers_per_gpu=4,
train=dict(
type='CuhkDataset',
ann_file=
'.../AlignPS/demo/anno/cuhk-sysu/train_pid_new.json',
img_prefix='.../Datasets/CUHK-SYSU/Image/SSM/',
pipeline=[
dict(type='LoadImageFromFile'),
dict(type='LoadAnnotations', with_bbox=True),
dict(
type='Resize',
img_scale=[(333, 200), (500, 300), (666, 400), (750, 450),
(833, 500), (1000, 600)],
multiscale_mode='value',
keep_ratio=True),
dict(type='RandomFlip', flip_ratio=0.5),
dict(
type='Normalize',
mean=[103.53, 116.28, 123.675],
std=[1.0, 1.0, 1.0],
to_rgb=False),
dict(type='Pad', size_divisor=32),
dict(type='DefaultFormatBundle'),
dict(
type='Collect',
keys=['img', 'gt_bboxes', 'gt_labels', 'gt_ids'])
]),
val=dict(
type='CuhkDataset',
ann_file=
'.../AlignPS/demo/anno/cuhk-sysu/test_new.json',
img_prefix='.../Datasets/CUHK-SYSU/Image/SSM/',
pipeline=[
dict(type='LoadImageFromFile'),
dict(
type='MultiScaleFlipAug',
img_scale=(750, 450),
flip=False,
transforms=[
dict(type='Resize', keep_ratio=True),
dict(type='RandomFlip'),
dict(
type='Normalize',
mean=[103.53, 116.28, 123.675],
std=[1.0, 1.0, 1.0],
to_rgb=False),
dict(type='Pad', size_divisor=32),
dict(type='ImageToTensor', keys=['img']),
dict(type='Collect', keys=['img'])
])
]),
test=dict(
type='CuhkDataset',
ann_file=
'.../AlignPS/demo/anno/cuhk-sysu/test_new.json',
img_prefix='.../Datasets/CUHK-SYSU/Image/SSM/',
proposal_file=
'.../Datasets/CUHK-SYSU/annotation/test/train_test/TestG50.mat',
pipeline=[
dict(type='LoadImageFromFile'),
dict(
type='MultiScaleFlipAug',
img_scale=(750, 450),
flip=False,
transforms=[
dict(type='Resize', keep_ratio=True),
dict(type='RandomFlip'),
dict(
type='Normalize',
mean=[103.53, 116.28, 123.675],
std=[1.0, 1.0, 1.0],
to_rgb=False),
dict(type='Pad', size_divisor=32),
dict(type='ImageToTensor', keys=['img']),
dict(type='Collect', keys=['img'])
])
]))
evaluation = dict(interval=1, metric='bbox')
optimizer = dict(
type='SGD',
lr=0.001,
momentum=0.9,
weight_decay=0.0001,
paramwise_cfg=dict(bias_lr_mult=2.0, bias_decay_mult=0.0))
optimizer_config = dict(grad_clip=dict(max_norm=35, norm_type=2))
lr_config = dict(
policy='step',
warmup='linear',
warmup_iters=500,
warmup_ratio=0.3333333333333333,
step=[16, 22])
total_epochs = 1
checkpoint_config = dict(interval=1)
log_config = dict(interval=50, hooks=[dict(type='TextLoggerHook')])
dist_params = dict(backend='nccl')
log_level = 'INFO'
load_from = None
resume_from = None
workflow = [('train', 1)]
model = dict(
type='FCOSReid',
pretrained='open-mmlab://detectron2/resnet50_caffe',
backbone=dict(
type='ResNet',
depth=50,
num_stages=4,
out_indices=(0, 1, 2, 3),
frozen_stages=1,
norm_cfg=dict(type='BN', requires_grad=False),
norm_eval=True,
style='caffe',
dcn=dict(type='DCNv2', deform_groups=1, fallback_on_stride=False),
stage_with_dcn=(False, False, False, False)),
neck=dict(
type='FPNDcnLconv3Dcn',
in_channels=[256, 512, 1024, 2048],
out_channels=256,
start_level=1,
add_extra_convs=True,
extra_convs_on_inputs=False,
num_outs=5,
relu_before_extra_convs=True),
bbox_head=dict(
type='FCOSReidHeadFocalSubTriQueue',
num_classes=1,
in_channels=256,
stacked_convs=4,
feat_channels=256,
strides=[8, 16, 32, 64, 128],
loss_cls=dict(
type='FocalLoss',
use_sigmoid=True,
gamma=2.0,
alpha=0.25,
loss_weight=1.0),
loss_bbox=dict(type='GIoULoss', loss_weight=1.0),
loss_centerness=dict(
type='CrossEntropyLoss', use_sigmoid=True, loss_weight=1.0),
norm_on_bbox=True,
centerness_on_reg=True,
dcn_on_last_conv=True,
center_sampling=True,
conv_bias=True))
train_cfg = dict(
assigner=dict(
type='MaxIoUAssigner',
pos_iou_thr=0.5,
neg_iou_thr=0.4,
min_pos_iou=0,
ignore_iof_thr=-1),
allowed_border=-1,
pos_weight=-1,
debug=False)
test_cfg = dict(
nms_pre=1000,
min_bbox_size=0,
score_thr=0.05,
nms=dict(type='nms', iou_threshold=0.5),
max_per_img=100)
work_dir = './work_dirs/fcos_center-normbbox-centeronreg-giou_r50_caffe_fpn_gn-head_dcn_4x4_1x_cuhk_reid_1500_stage1_fpncat_dcn_epoch24_multiscale_focal_x4_bg-2_lconv3dcn_sub_triqueue_dcn0'
gpu_ids = [0]
**Traceback (most recent call last):
File "tools/train.py", line 177, in <module>
main()
File "tools/train.py", line 151, in main
cfg.model, train_cfg=cfg.train_cfg, test_cfg=cfg.test_cfg)
File "/home/ubuntu/anaconda3/lib/python3.7/site-packages/mmdet/models/builder.py", line 67, in build_detector
return build(cfg, DETECTORS, dict(train_cfg=train_cfg, test_cfg=test_cfg))
File "/home/ubuntu/anaconda3/lib/python3.7/site-packages/mmdet/models/builder.py", line 32, in build
return build_from_cfg(cfg, registry, default_args)
File "/home/ubuntu/anaconda3/lib/python3.7/site-packages/mmcv/utils/registry.py", line 164, in build_from_cfg
f'{obj_type} is not in the {registry.name} registry')
KeyError: 'FCOSReid is not in the detector registry'**
My environment:
AlignPS$ python mmdet/utils/collect_env.py
sys.platform: linux
Python: 3.6.10 |Anaconda, Inc.| (default, Mar 25 2020, 23:51:54) [GCC 7.3.0]
CUDA available: True
CUDA_HOME: /usr/local/cuda-10.1
NVCC: Cuda compilation tools, release 10.1, V10.1.243
GPU 0: Tesla K80
GCC: gcc (Ubuntu 5.4.0-6ubuntu1~16.04.12) 5.4.0 20160609
PyTorch: 1.6.0
PyTorch compiling details: PyTorch built with:
- GCC 7.3
- C++ Version: 201402
- Intel(R) Math Kernel Library Version 2020.0.0 Product Build 20191122 for Intel(R) 64 architecture applications
- Intel(R) MKL-DNN v1.5.0 (Git Hash e2ac1fac44c5078ca927cb9b90e1b3066a0b2ed0)
- OpenMP 201511 (a.k.a. OpenMP 4.5)
- NNPACK is enabled
- CPU capability usage: AVX2
- CUDA Runtime 10.1
- NVCC architecture flags: -gencode;arch=compute_37,code=sm_37;-gencode;arch=compute_50,code=sm_50;-gencode;arch=compute_60,code=sm_60;-gencode;arch=compute_61,code=sm_61;-gencode;arch=compute_70,code=sm_70;-gencode;arch=compute_75,code=sm_75;-gencode;arch=compute_37,code=compute_37
- CuDNN 7.6.3
- Magma 2.5.2
- Build settings: BLAS=MKL, BUILD_TYPE=Release, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -fopenmp -DNDEBUG -DUSE_FBGEMM -DUSE_QNNPACK -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DUSE_VULKAN_WRAPPER -O2 -fPIC -Wno-narrowing -Wall -Wextra -Werror=return-type -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-sign-compare -Wno-unused-parameter -Wno-unused-variable -Wno-unused-function -Wno-unused-result -Wno-unused-local-typedefs -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Wno-stringop-overflow, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, USE_CUDA=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=ON, USE_MKLDNN=ON, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=ON, USE_OPENMP=ON, USE_STATIC_DISPATCH=OFF,
TorchVision: 0.7.0
OpenCV: 4.2.0
MMCV: 1.1.5
MMDetection: 2.7.0+aa244c1
MMDetection Compiler: GCC 7.3
MMDetection CUDA Compiler: 10.1
Convert PRW to COCO ?
Hi, I found a directory named convert_datasets where I further found a script to convert CUHK dataset to COCO format, so I wonder,
whether there is a script to convert another dataset PRW to COCO format ?
A Question about the Unlabedmatching
Thanks for sharing you excellent work! I have a question about the update function of unlabeled queue:
Why only update the front 64 channels of unlabeled queue? Does it bring any performance improvements?
loss_cls: nan, loss_bbox: nan, loss_centerness: nan, loss_oim: nan, loss: nan, grad_norm: nan
Hi:
I encountered some problems when running the source code：
2022-02-17 14:43:37,319 - mmdet - INFO - Epoch [1][50/2852] lr: 3.987e-04, eta: 2 days, 6:05:49, time: 1.423, data_time: 0.068, memory: 7011, loss_cls: 0.6662, loss_bbox: 0.9846, loss_centerness: 0.6260, loss_oim: 5.6912, loss: 7.9680, grad_norm: 118.5072
2022-02-17 14:44:35,675 - mmdet - INFO - Epoch [1][100/2852] lr: 4.653e-04, eta: 2 days, 1:12:47, time: 1.167, data_time: 0.016, memory: 7363, loss_cls: 0.5805, loss_bbox: 0.8021, loss_centerness: 0.5967, loss_oim: 5.8589, loss: 7.8382, grad_norm: 104.7832
2022-02-17 14:45:52,820 - mmdet - INFO - Epoch [1][150/2852] lr: 5.320e-04, eta: 2 days, 4:19:57, time: 1.543, data_time: 0.017, memory: 7363, loss_cls: 0.6106, loss_bbox: 0.5222, loss_centerness: 0.5782, loss_oim: 6.3371, loss: 8.0482, grad_norm: 108.9552
2022-02-17 14:47:02,130 - mmdet - INFO - Epoch [1][200/2852] lr: 5.987e-04, eta: 2 days, 4:23:37, time: 1.386, data_time: 0.017, memory: 7363, loss_cls: 0.4726, loss_bbox: 0.5253, loss_centerness: 0.6215, loss_oim: 5.8503, loss: 7.4698, grad_norm: 86.1120
2022-02-17 14:48:04,005 - mmdet - INFO - Epoch [1][250/2852] lr: 6.653e-04, eta: 2 days, 3:17:38, time: 1.237, data_time: 0.015, memory: 7363, loss_cls: 0.4858, loss_bbox: 0.4937, loss_centerness: 0.6017, loss_oim: 6.1532, loss: 7.7343, grad_norm: 94.5427
2022-02-17 14:49:06,965 - mmdet - INFO - Epoch [1][300/2852] lr: 7.320e-04, eta: 2 days, 2:41:31, time: 1.259, data_time: 0.017, memory: 7363, loss_cls: 0.5772, loss_bbox: 0.5174, loss_centerness: 0.5998, loss_oim: 6.5115, loss: 8.2059, grad_norm: 92.6229
2022-02-17 14:50:16,175 - mmdet - INFO - Epoch [1][350/2852] lr: 7.987e-04, eta: 2 days, 2:56:04, time: 1.384, data_time: 0.018, memory: 7363, loss_cls: 0.5621, loss_bbox: 0.5079, loss_centerness: 0.6014, loss_oim: 6.6282, loss: 8.2996, grad_norm: 83.7950
2022-02-17 14:51:23,770 - mmdet - INFO - Epoch [1][400/2852] lr: 8.653e-04, eta: 2 days, 2:57:31, time: 1.352, data_time: 0.019, memory: 7363, loss_cls: 0.6787, loss_bbox: 0.5543, loss_centerness: 0.5968, loss_oim: 6.6915, loss: 8.5213, grad_norm: 136.0015
2022-02-17 14:52:28,603 - mmdet - INFO - Epoch [1][450/2852] lr: 9.320e-04, eta: 2 days, 2:44:25, time: 1.297, data_time: 0.016, memory: 7363, loss_cls: 0.6619, loss_bbox: 0.5619, loss_centerness: 0.6255, loss_oim: 8.8492, loss: 10.6984, grad_norm: 40.6709
2022-02-17 14:53:31,481 - mmdet - INFO - Epoch [1][500/2852] lr: 9.987e-04, eta: 2 days, 2:24:51, time: 1.258, data_time: 0.018, memory: 7363, loss_cls: 0.6701, loss_bbox: 0.5613, loss_centerness: 0.6302, loss_oim: 8.8498, loss: 10.7114, grad_norm: 56.6717
2022-02-17 14:54:34,786 - mmdet - INFO - Epoch [1][550/2852] lr: 1.000e-03, eta: 2 days, 2:10:25, time: 1.266, data_time: 0.015, memory: 7363, loss_cls: nan, loss_bbox: nan, loss_centerness: nan, loss_oim: nan, loss: nan, grad_norm: nan
2022-02-17 14:55:39,327 - mmdet - INFO - Epoch [1][600/2852] lr: 1.000e-03, eta: 2 days, 2:02:53, time: 1.291, data_time: 0.018, memory: 7363, loss_cls: nan, loss_bbox: nan, loss_centerness: nan, loss_oim: nan, loss: nan, grad_norm: nan
2022-02-17 14:56:43,064 - mmdet - INFO - Epoch [1][650/2852] lr: 1.000e-03, eta: 2 days, 1:53:32, time: 1.275, data_time: 0.018, memory: 7363, loss_cls: nan, loss_bbox: nan, loss_centerness: nan, loss_oim: nan, loss: nan, grad_norm: nan
2022-02-17 14:57:46,297 - mmdet - INFO - Epoch [1][700/2852] lr: 1.000e-03, eta: 2 days, 1:43:44, time: 1.265, data_time: 0.017, memory: 7363, loss_cls: nan, loss_bbox: nan, loss_centerness: nan, loss_oim: nan, loss: nan, grad_norm: nan
All these values become nan，the command I ran was：python tools/train.py configs/fcos/prw_base_focal_labelnorm_sub_ldcn_fg15_wd1-3.py --gpu-ids 6 --no-validate
and I did not change the parameters in the configuration file。
Can you help me？
When I implementatiaon ROI-AlignPS, I have a problem
(open-mmlab) lxz@lxz-System-Product-Name:~/KunPeng_Liu/AlignPS$ /bin/bash /home/lxz/KunPeng_Liu/AlignPS/run_train.sh
fatal: not a git repository (or any of the parent directories): .git
2021-09-13 17:36:13,497 - mmdet - INFO - Environment info:
sys.platform: linux
Python: 3.7.10 | packaged by conda-forge | (default, Feb 19 2021, 16:07:37) [GCC 9.3.0]
CUDA available: True
CUDA_HOME: /usr/local/cuda-11.0
NVCC: Build cuda_11.0_bu.TC445_37.28845127_0
GPU 0: NVIDIA GeForce RTX 3090
GCC: gcc (Ubuntu 7.5.0-3ubuntu1~18.04) 7.5.0
PyTorch: 1.7.0
PyTorch compiling details: PyTorch built with:
- GCC 7.3
- C++ Version: 201402
- Intel(R) oneAPI Math Kernel Library Version 2021.3-Product Build 20210617 for Intel(R) 64 architecture applications
- Intel(R) MKL-DNN v1.6.0 (Git Hash 5ef631a030a6f73131c77892041042805a06064f)
- OpenMP 201511 (a.k.a. OpenMP 4.5)
- NNPACK is enabled
- CPU capability usage: AVX2
- CUDA Runtime 11.0
- NVCC architecture flags: -gencode;arch=compute_37,code=sm_37;-gencode;arch=compute_50,code=sm_50;-gencode;arch=compute_60,code=sm_60;-gencode;arch=compute_61,code=sm_61;-gencode;arch=compute_70,code=sm_70;-gencode;arch=compute_75,code=sm_75;-gencode;arch=compute_80,code=sm_80;-gencode;arch=compute_37,code=compute_37
- CuDNN 8.0.3
- Magma 2.5.2
- Build settings: BLAS=MKL, BUILD_TYPE=Release, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -fopenmp -DNDEBUG -DUSE_FBGEMM -DUSE_QNNPACK -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DUSE_VULKAN_WRAPPER -O2 -fPIC -Wno-narrowing -Wall -Wextra -Werror=return-type -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-sign-compare -Wno-unused-parameter -Wno-unused-variable -Wno-unused-function -Wno-unused-result -Wno-unused-local-typedefs -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Wno-stringop-overflow, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, USE_CUDA=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=ON, USE_MKLDNN=ON, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=ON, USE_OPENMP=ON,
TorchVision: 0.8.0
OpenCV: 4.5.3
MMCV: 1.3.13
MMDetection: 2.4.0+
MMDetection Compiler: GCC 7.3
MMDetection CUDA Compiler: 11.0
2021-09-13 17:36:14,238 - mmdet - INFO - Distributed training: False
2021-09-13 17:36:14,971 - mmdet - INFO - Config:
dataset_type = 'CuhkDataset'
data_root = '/home/lxz/KunPeng_Liu/dataset/PRW/PRW-v16.04.20/'
img_norm_cfg = dict(
mean=[103.53, 116.28, 123.675], std=[1.0, 1.0, 1.0], to_rgb=False)
train_pipeline = [
dict(type='LoadImageFromFile'),
dict(type='LoadAnnotations', with_bbox=True),
dict(
type='Resize',
img_scale=[(667, 400), (1000, 600), (1333, 800), (1500, 900),
(1666, 1000), (2000, 1200)],
multiscale_mode='value',
keep_ratio=True),
dict(type='RandomFlip', flip_ratio=0.5),
dict(
type='Normalize',
mean=[103.53, 116.28, 123.675],
std=[1.0, 1.0, 1.0],
to_rgb=False),
dict(type='Pad', size_divisor=32),
dict(type='DefaultFormatBundle'),
dict(type='Collect', keys=['img', 'gt_bboxes', 'gt_labels', 'gt_ids'])
]
test_pipeline = [
dict(type='LoadImageFromFile'),
dict(
type='MultiScaleFlipAug',
img_scale=(1500, 900),
flip=False,
transforms=[
dict(type='Resize', keep_ratio=True),
dict(type='RandomFlip'),
dict(
type='Normalize',
mean=[103.53, 116.28, 123.675],
std=[1.0, 1.0, 1.0],
to_rgb=False),
dict(type='Pad', size_divisor=32),
dict(type='ImageToTensor', keys=['img']),
dict(type='Collect', keys=['img'])
])
]
data = dict(
samples_per_gpu=5,
workers_per_gpu=5,
train=dict(
type='CuhkDataset',
ann_file=
'/home/lxz/KunPeng_Liu/dataset/PRW/PRW-v16.04.20/train_pid.json',
img_prefix='/home/lxz/KunPeng_Liu/dataset/PRW/PRW-v16.04.20/frames/',
pipeline=[
dict(type='LoadImageFromFile'),
dict(type='LoadAnnotations', with_bbox=True),
dict(
type='Resize',
img_scale=[(667, 400), (1000, 600), (1333, 800), (1500, 900),
(1666, 1000), (2000, 1200)],
multiscale_mode='value',
keep_ratio=True),
dict(type='RandomFlip', flip_ratio=0.5),
dict(
type='Normalize',
mean=[103.53, 116.28, 123.675],
std=[1.0, 1.0, 1.0],
to_rgb=False),
dict(type='Pad', size_divisor=32),
dict(type='DefaultFormatBundle'),
dict(
type='Collect',
keys=['img', 'gt_bboxes', 'gt_labels', 'gt_ids'])
]),
val=dict(
type='CuhkDataset',
ann_file=
'/home/lxz/KunPeng_Liu/dataset/PRW/PRW-v16.04.20/test_pid.json',
img_prefix='/home/lxz/KunPeng_Liu/dataset/PRW/PRW-v16.04.20/frames/',
pipeline=[
dict(type='LoadImageFromFile'),
dict(
type='MultiScaleFlipAug',
img_scale=(1500, 900),
flip=False,
transforms=[
dict(type='Resize', keep_ratio=True),
dict(type='RandomFlip'),
dict(
type='Normalize',
mean=[103.53, 116.28, 123.675],
std=[1.0, 1.0, 1.0],
to_rgb=False),
dict(type='Pad', size_divisor=32),
dict(type='ImageToTensor', keys=['img']),
dict(type='Collect', keys=['img'])
])
]),
test=dict(
type='CuhkDataset',
ann_file=
'/home/lxz/KunPeng_Liu/dataset/PRW/PRW-v16.04.20/test_pid.json',
img_prefix='/home/lxz/KunPeng_Liu/dataset/PRW/PRW-v16.04.20/frames/',
proposal_file=
'/home/lxz/KunPeng_Liu/dataset/PRW/PRW-v16.04.20/annotation/test/train_test/TestG50.mat',
pipeline=[
dict(type='LoadImageFromFile'),
dict(
type='MultiScaleFlipAug',
img_scale=(1500, 900),
flip=False,
transforms=[
dict(type='Resize', keep_ratio=True),
dict(type='RandomFlip'),
dict(
type='Normalize',
mean=[103.53, 116.28, 123.675],
std=[1.0, 1.0, 1.0],
to_rgb=False),
dict(type='Pad', size_divisor=32),
dict(type='ImageToTensor', keys=['img']),
dict(type='Collect', keys=['img'])
])
]))
evaluation = dict(interval=1, metric='bbox')
norm_cfg = dict(type='BN', requires_grad=False)
model = dict(
type='SingleTwoStageDetector176PRW',
pretrained='open-mmlab://detectron2/resnet50_caffe',
backbone=dict(
type='ResNet',
depth=50,
num_stages=4,
out_indices=(0, 1, 2, 3),
frozen_stages=1,
norm_cfg=dict(type='BN', requires_grad=False),
norm_eval=True,
style='caffe'),
rpn_head=dict(
type='RPNHead',
in_channels=1024,
feat_channels=1024,
anchor_generator=dict(
type='AnchorGenerator',
scales=[2, 4, 8, 16, 32],
ratios=[0.5, 1.0, 2.0],
strides=[16]),
bbox_coder=dict(
type='DeltaXYWHBBoxCoder',
target_means=[0.0, 0.0, 0.0, 0.0],
target_stds=[1.0, 1.0, 1.0, 1.0]),
loss_cls=dict(
type='CrossEntropyLoss', use_sigmoid=True, loss_weight=1.0),
loss_bbox=dict(type='L1Loss', loss_weight=1.0)),
roi_head=dict(
type='PersonSearchRoIHead2Input1',
shared_head=dict(
type='ResLayer',
depth=50,
stage=3,
stride=2,
dilation=1,
style='caffe',
norm_cfg=dict(type='BN', requires_grad=False),
norm_eval=True),
bbox_roi_extractor=dict(
type='SingleRoIExtractor',
roi_layer=dict(type='RoIAlign', out_size=14, sample_num=0),
out_channels=1024,
featmap_strides=[16]),
bbox_head=dict(
type='PersonSearchNormAwareNewoim2InputBNBBoxHeadPRW',
with_avg_pool=True,
roi_feat_size=7,
in_channels=2048,
num_classes=1,
bbox_coder=dict(
type='DeltaXYWHBBoxCoder',
target_means=[0.0, 0.0, 0.0, 0.0],
target_stds=[0.1, 0.1, 0.2, 0.2]),
reg_class_agnostic=False,
loss_cls=dict(
type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0),
loss_bbox=dict(type='L1Loss', loss_weight=10.0))),
neck=dict(
type='FPNDcnLconv3Dcn',
in_channels=[256, 512, 1024, 2048],
out_channels=256,
start_level=1,
add_extra_convs=True,
extra_convs_on_inputs=False,
num_outs=5,
relu_before_extra_convs=True),
bbox_head=dict(
type='FCOSReidHeadFocalSubTriQueue3PRW',
num_classes=1,
in_channels=256,
stacked_convs=4,
feat_channels=256,
strides=[8, 16, 32, 64, 128],
loss_cls=dict(
type='FocalLoss',
use_sigmoid=True,
gamma=2.0,
alpha=0.25,
loss_weight=1.0),
loss_bbox=dict(type='GIoULoss', loss_weight=1.0),
loss_centerness=dict(
type='CrossEntropyLoss', use_sigmoid=True, loss_weight=1.0),
norm_on_bbox=True,
centerness_on_reg=True,
dcn_on_last_conv=True,
center_sampling=True,
conv_bias=True))
train_cfg = dict(
rpn=dict(
assigner=dict(
type='MaxIoUAssigner',
pos_iou_thr=0.7,
neg_iou_thr=0.3,
min_pos_iou=0.3,
match_low_quality=True,
ignore_iof_thr=-1),
sampler=dict(
type='RandomSampler',
num=256,
pos_fraction=0.5,
neg_pos_ub=-1,
add_gt_as_proposals=False),
allowed_border=0,
pos_weight=-1,
debug=False),
rpn_proposal=dict(
nms_across_levels=False,
nms_pre=12000,
nms_post=2000,
max_num=2000,
nms_thr=0.7,
min_bbox_size=0),
rcnn=dict(
assigner=dict(
type='MaxIoUAssigner',
pos_iou_thr=0.5,
neg_iou_thr=0.1,
min_pos_iou=0.5,
match_low_quality=False,
ignore_iof_thr=-1),
sampler=dict(
type='RandomSampler',
num=128,
pos_fraction=0.5,
neg_pos_ub=-1,
add_gt_as_proposals=True),
pos_weight=-1,
debug=False),
assigner=dict(
type='MaxIoUAssigner',
pos_iou_thr=0.5,
neg_iou_thr=0.4,
min_pos_iou=0,
ignore_iof_thr=-1),
allowed_border=-1,
pos_weight=-1,
debug=False)
test_cfg = dict(
rpn=dict(
nms_across_levels=False,
nms_pre=6000,
nms_post=300,
max_num=1000,
nms_thr=0.7,
min_bbox_size=0),
rcnn=dict(
score_thr=0.05, nms=dict(type='nms', iou_thr=0.5), max_per_img=100),
nms_pre=1000,
min_bbox_size=0,
score_thr=0.05,
nms=dict(type='nms', iou_threshold=0.5),
max_per_img=100)
optimizer = dict(type='SGD', lr=0.0015, momentum=0.9, weight_decay=0.0005)
optimizer_config = dict(grad_clip=dict(max_norm=10, norm_type=2))
lr_config = dict(
policy='step',
warmup='linear',
warmup_iters=1141,
warmup_ratio=0.005,
step=[16, 22])
total_epochs = 24
checkpoint_config = dict(interval=1)
log_config = dict(interval=50, hooks=[dict(type='TextLoggerHook')])
dist_params = dict(backend='nccl')
log_level = 'INFO'
load_from = None
resume_from = None
workflow = [('train', 1)]
work_dir = './work_dirs/faster_rcnn_r50_caffe_c4_1x_cuhk_single_two_stage17_6_nae1_prw'
gpu_ids = [0]
/home/lxz/.local/lib/python3.7/site-packages/mmcv/utils/misc.py:324: UserWarning: "out_size" is deprecated in RoIAlign.__init__, please use "output_size" instead
f'"{src_arg_name}" is deprecated in '
/home/lxz/.local/lib/python3.7/site-packages/mmcv/utils/misc.py:324: UserWarning: "sample_num" is deprecated in RoIAlign.__init__, please use "sampling_ratio" instead
f'"{src_arg_name}" is deprecated in '
2021-09-13 17:36:15,307 - mmdet - INFO - load model from: open-mmlab://detectron2/resnet50_caffe
2021-09-13 17:36:15,308 - mmdet - INFO - Use load_from_openmmlab loader
2021-09-13 17:36:15,367 - mmdet - WARNING - The model and loaded state dict do not match exactly
unexpected key in source state_dict: conv1.bias
2021-09-13 17:36:15,432 - mmdet - INFO - Use load_from_openmmlab loader
2021-09-13 17:36:15,477 - mmdet - WARNING - The model and loaded state dict do not match exactly
unexpected key in source state_dict: conv1.weight, conv1.bias, bn1.bias, bn1.weight, bn1.running_mean, bn1.running_var, layer1.0.downsample.0.weight, layer1.0.downsample.1.bias, layer1.0.downsample.1.weight, layer1.0.downsample.1.running_mean, layer1.0.downsample.1.running_var, layer1.0.conv1.weight, layer1.0.bn1.bias, layer1.0.bn1.weight, layer1.0.bn1.running_mean, layer1.0.bn1.running_var, layer1.0.conv2.weight, layer1.0.bn2.bias, layer1.0.bn2.weight, layer1.0.bn2.running_mean, layer1.0.bn2.running_var, layer1.0.conv3.weight, layer1.0.bn3.bias, layer1.0.bn3.weight, layer1.0.bn3.running_mean, layer1.0.bn3.running_var, layer1.1.conv1.weight, layer1.1.bn1.bias, layer1.1.bn1.weight, layer1.1.bn1.running_mean, layer1.1.bn1.running_var, layer1.1.conv2.weight, layer1.1.bn2.bias, layer1.1.bn2.weight, layer1.1.bn2.running_mean, layer1.1.bn2.running_var, layer1.1.conv3.weight, layer1.1.bn3.bias, layer1.1.bn3.weight, layer1.1.bn3.running_mean, layer1.1.bn3.running_var, layer1.2.conv1.weight, layer1.2.bn1.bias, layer1.2.bn1.weight, layer1.2.bn1.running_mean, layer1.2.bn1.running_var, layer1.2.conv2.weight, layer1.2.bn2.bias, layer1.2.bn2.weight, layer1.2.bn2.running_mean, layer1.2.bn2.running_var, layer1.2.conv3.weight, layer1.2.bn3.bias, layer1.2.bn3.weight, layer1.2.bn3.running_mean, layer1.2.bn3.running_var, layer2.0.downsample.0.weight, layer2.0.downsample.1.bias, layer2.0.downsample.1.weight, layer2.0.downsample.1.running_mean, layer2.0.downsample.1.running_var, layer2.0.conv1.weight, layer2.0.bn1.bias, layer2.0.bn1.weight, layer2.0.bn1.running_mean, layer2.0.bn1.running_var, layer2.0.conv2.weight, layer2.0.bn2.bias, layer2.0.bn2.weight, layer2.0.bn2.running_mean, layer2.0.bn2.running_var, layer2.0.conv3.weight, layer2.0.bn3.bias, layer2.0.bn3.weight, layer2.0.bn3.running_mean, layer2.0.bn3.running_var, layer2.1.conv1.weight, layer2.1.bn1.bias, layer2.1.bn1.weight, layer2.1.bn1.running_mean, layer2.1.bn1.running_var, layer2.1.conv2.weight, layer2.1.bn2.bias, layer2.1.bn2.weight, layer2.1.bn2.running_mean, layer2.1.bn2.running_var, layer2.1.conv3.weight, layer2.1.bn3.bias, layer2.1.bn3.weight, layer2.1.bn3.running_mean, layer2.1.bn3.running_var, layer2.2.conv1.weight, layer2.2.bn1.bias, layer2.2.bn1.weight, layer2.2.bn1.running_mean, layer2.2.bn1.running_var, layer2.2.conv2.weight, layer2.2.bn2.bias, layer2.2.bn2.weight, layer2.2.bn2.running_mean, layer2.2.bn2.running_var, layer2.2.conv3.weight, layer2.2.bn3.bias, layer2.2.bn3.weight, layer2.2.bn3.running_mean, layer2.2.bn3.running_var, layer2.3.conv1.weight, layer2.3.bn1.bias, layer2.3.bn1.weight, layer2.3.bn1.running_mean, layer2.3.bn1.running_var, layer2.3.conv2.weight, layer2.3.bn2.bias, layer2.3.bn2.weight, layer2.3.bn2.running_mean, layer2.3.bn2.running_var, layer2.3.conv3.weight, layer2.3.bn3.bias, layer2.3.bn3.weight, layer2.3.bn3.running_mean, layer2.3.bn3.running_var, layer3.0.downsample.0.weight, layer3.0.downsample.1.bias, layer3.0.downsample.1.weight, layer3.0.downsample.1.running_mean, layer3.0.downsample.1.running_var, layer3.0.conv1.weight, layer3.0.bn1.bias, layer3.0.bn1.weight, layer3.0.bn1.running_mean, layer3.0.bn1.running_var, layer3.0.conv2.weight, layer3.0.bn2.bias, layer3.0.bn2.weight, layer3.0.bn2.running_mean, layer3.0.bn2.running_var, layer3.0.conv3.weight, layer3.0.bn3.bias, layer3.0.bn3.weight, layer3.0.bn3.running_mean, layer3.0.bn3.running_var, layer3.1.conv1.weight, layer3.1.bn1.bias, layer3.1.bn1.weight, layer3.1.bn1.running_mean, layer3.1.bn1.running_var, layer3.1.conv2.weight, layer3.1.bn2.bias, layer3.1.bn2.weight, layer3.1.bn2.running_mean, layer3.1.bn2.running_var, layer3.1.conv3.weight, layer3.1.bn3.bias, layer3.1.bn3.weight, layer3.1.bn3.running_mean, layer3.1.bn3.running_var, layer3.2.conv1.weight, layer3.2.bn1.bias, layer3.2.bn1.weight, layer3.2.bn1.running_mean, layer3.2.bn1.running_var, layer3.2.conv2.weight, layer3.2.bn2.bias, layer3.2.bn2.weight, layer3.2.bn2.running_mean, layer3.2.bn2.running_var, layer3.2.conv3.weight, layer3.2.bn3.bias, layer3.2.bn3.weight, layer3.2.bn3.running_mean, layer3.2.bn3.running_var, layer3.3.conv1.weight, layer3.3.bn1.bias, layer3.3.bn1.weight, layer3.3.bn1.running_mean, layer3.3.bn1.running_var, layer3.3.conv2.weight, layer3.3.bn2.bias, layer3.3.bn2.weight, layer3.3.bn2.running_mean, layer3.3.bn2.running_var, layer3.3.conv3.weight, layer3.3.bn3.bias, layer3.3.bn3.weight, layer3.3.bn3.running_mean, layer3.3.bn3.running_var, layer3.4.conv1.weight, layer3.4.bn1.bias, layer3.4.bn1.weight, layer3.4.bn1.running_mean, layer3.4.bn1.running_var, layer3.4.conv2.weight, layer3.4.bn2.bias, layer3.4.bn2.weight, layer3.4.bn2.running_mean, layer3.4.bn2.running_var, layer3.4.conv3.weight, layer3.4.bn3.bias, layer3.4.bn3.weight, layer3.4.bn3.running_mean, layer3.4.bn3.running_var, layer3.5.conv1.weight, layer3.5.bn1.bias, layer3.5.bn1.weight, layer3.5.bn1.running_mean, layer3.5.bn1.running_var, layer3.5.conv2.weight, layer3.5.bn2.bias, layer3.5.bn2.weight, layer3.5.bn2.running_mean, layer3.5.bn2.running_var, layer3.5.conv3.weight, layer3.5.bn3.bias, layer3.5.bn3.weight, layer3.5.bn3.running_mean, layer3.5.bn3.running_var
loading annotations into memory...
Done (t=0.03s)
creating index...
index created!
fatal: not a git repository (or any of the parent directories): .git
2021-09-13 17:36:16,813 - mmdet - INFO - Start running, host: lxz@lxz-System-Product-Name, work_dir: /home/lxz/KunPeng_Liu/AlignPS/work_dirs/faster_rcnn_r50_caffe_c4_1x_cuhk_single_two_stage17_6_nae1_prw
2021-09-13 17:36:16,813 - mmdet - INFO - Hooks will be executed in the following order:
before_run:
(VERY_HIGH ) StepLrUpdaterHook
(NORMAL ) CheckpointHook
(VERY_LOW ) TextLoggerHook
before_train_epoch:
(VERY_HIGH ) StepLrUpdaterHook
(LOW ) IterTimerHook
(VERY_LOW ) TextLoggerHook
before_train_iter:
(VERY_HIGH ) StepLrUpdaterHook
(LOW ) IterTimerHook
after_train_iter:
(ABOVE_NORMAL) OptimizerHook
(NORMAL ) CheckpointHook
(LOW ) IterTimerHook
(VERY_LOW ) TextLoggerHook
after_train_epoch:
(NORMAL ) CheckpointHook
(VERY_LOW ) TextLoggerHook
before_val_epoch:
(LOW ) IterTimerHook
(VERY_LOW ) TextLoggerHook
before_val_iter:
(LOW ) IterTimerHook
after_val_iter:
(LOW ) IterTimerHook
after_val_epoch:
(VERY_LOW ) TextLoggerHook
2021-09-13 17:36:16,813 - mmdet - INFO - workflow: [('train', 1)], max: 24 epochs
/home/lxz/anaconda3/envs/open-mmlab/lib/python3.7/site-packages/torch/nn/functional.py:2952: UserWarning: nn.functional.upsample is deprecated. Use nn.functional.interpolate instead.
warnings.warn("nn.functional.upsample is deprecated. Use nn.functional.interpolate instead.")
/home/lxz/anaconda3/envs/open-mmlab/lib/python3.7/site-packages/torch/nn/functional.py:3063: UserWarning: Default upsampling behavior when mode=bilinear is changed to align_corners=False since 0.4.0. Please specify align_corners=True if the old behavior is desired. See the documentation of nn.Upsample for details.
"See the documentation of nn.Upsample for details.".format(mode))
/home/lxz/KunPeng_Liu/AlignPS/mmdet/models/dense_heads/fcos_reid_head_focal_sub_triqueue3_prw.py:306: UserWarning: This overload of nonzero is deprecated:
nonzero()
Consider using one of the following signatures instead:
nonzero(*, bool as_tuple) (Triggered internally at /opt/conda/conda-bld/pytorch_1603729047590/work/torch/csrc/utils/python_arg_parser.cpp:882.)
& (flatten_labels < bg_class_ind)).nonzero().reshape(-1)
/opt/conda/conda-bld/pytorch_1603729047590/work/aten/src/THCUNN/ClassNLLCriterion.cu:187: cunn_ClassNLLCriterion_updateGradInput_kernel: block: [0,0,0], thread: [0,0,0] Assertion t >= 0 && t < n_classes failed.
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Traceback (most recent call last):
File "tools/train.py", line 177, in
main()
File "tools/train.py", line 173, in main
meta=meta)
File "/home/lxz/KunPeng_Liu/AlignPS/mmdet/apis/train.py", line 146, in train_detector
runner.run(data_loaders, cfg.workflow, cfg.total_epochs)
File "/home/lxz/.local/lib/python3.7/site-packages/mmcv/runner/epoch_based_runner.py", line 127, in run
epoch_runner(data_loaders[i], **kwargs)
File "/home/lxz/.local/lib/python3.7/site-packages/mmcv/runner/epoch_based_runner.py", line 51, in train
self.call_hook('after_train_iter')
File "/home/lxz/.local/lib/python3.7/site-packages/mmcv/runner/base_runner.py", line 307, in call_hook
getattr(hook, fn_name)(self)
File "/home/lxz/.local/lib/python3.7/site-packages/mmcv/runner/hooks/optimizer.py", line 35, in after_train_iter
runner.outputs['loss'].backward()
File "/home/lxz/anaconda3/envs/open-mmlab/lib/python3.7/site-packages/torch/tensor.py", line 221, in backward
torch.autograd.backward(self, gradient, retain_graph, create_graph)
File "/home/lxz/anaconda3/envs/open-mmlab/lib/python3.7/site-packages/torch/autograd/init.py", line 132, in backward
allow_unreachable=True) # allow_unreachable flag
File "/home/lxz/anaconda3/envs/open-mmlab/lib/python3.7/site-packages/torch/autograd/function.py", line 89, in apply
return self._forward_cls.backward(self, *args) # type: ignore
File "/home/lxz/KunPeng_Liu/AlignPS/mmdet/models/roi_heads/bbox_heads/oim_nae_new.py", line 29, in backward
if y >= 0:
RuntimeError: CUDA error: device-side assert triggered
When i implementation AlignPS, the program can run sucessfully.
ImportError: cannot import name 'multiclass_nms_reid_nae'
Do you have any scripts for visible result?
Hello, I'm very new in this field.
And I want run and show the results by the images of the videos.
MMDetect provides some demos like image_demo.py or webcam_demo.py.
Do you have any scripts or code like this, or how can I get this?
Thank you for your helps.
Why didn't I get the right result？mAP = 0.00%Top- 1 = 0.00%Top- 5 = 0.00%Top-10 = 0.00%
writing results to work_dirs/fcos_center-normbbox-centeronreg-giou_r50_caffe_fpn_gn-head_dcn_4x4_1x_cuhk_reid_1500_stage1_fpncat_dcn_epoch24_multiscale_focal_x4_bg-2_lconv3dcn_sub_triqueue_dcn0/results_1000.pkl
threshold: 0.2
mAP = 0.00%
Top- 1 = 0.00%
Top- 5 = 0.00%
Top-10 = 0.00%
fcos_center-normbbox-centeronreg-giou_r50_caffe_fpn_gn-head_dcn_4x4_1x_cuhk_reid_1500_stage1_fpncat_dcn_epoch24_multiscale_focal_x4_bg-2_lconv3dcn_sub_triqueue_dcn0
Why only use focal and triplet loss in AlignPS branch
Hi, thanks for your awesome work.
I noticed that the focal and triplet loss are only used in AlignPS branch, not used in RoI-Align branch. And I don't really understand this setting.
But I have a explanation. The reason is positive samples in AlignPS branch (FCOS center 3x3 area) is much more than them in RoI-Align branch (positive proposals). So in AlignPS branch, for focal loss, features from neighbor location is similar and contain many easy samples. For triplet loss, it is much easier to build triplets with more samples.
Looking forward to your reply. Thanks in advance!
Error when running run_test_prw.sh
Hello,when i run the script run_test_prw.sh,the following error appears：
run_test_prw.sh: 12: run_test_prw.sh: ./tools/di
I want to hear your opinion. Results for one image
Hi,
Do you have any guideline to use final similarity score?
I want to know, how does it work when there is no query person in just one image?
Even if it is an incorrect result, since the person with the highest score is found?
Thank you.
Mismatch problem occurred while training the network
Hello, I want to reimplement the experiment, however, when I started training AlignPS (on CUHK), I encountered the following problems. No errors were reported, but the network is not training.
''''''''
2021-04-11 00:00:02,350 - mmdet - INFO - load model from: open-mmlab://detectron2/resnet50_caffe
2021-04-11 00:00:02,719 - mmdet - WARNING - The model and loaded state dict do not match exactly
unexpected key in source state_dict: conv1.bias
2021-04-11 00:00:08,895 - mmdet - INFO - Start running, host: xxxxx, work_dir: /home/xxxxx/AlignPS/work_dirs/fcos_center-normbbox-centeronreg-giou_r50_caffe_fpn_gn-head_dcn_4x4_1x_cuhk_reid_1500_stage1_fpncat_dcn_epoch24_multiscale_focal_x4_bg-2_lconv3dcn_sub_triqueue_dcn0
2021-04-11 00:00:08,908 - mmdet - INFO - workflow: [('train', 1)], max: 24 epochs
'''''''''
I completely followed the steps in install.md to configure the environment, and my conda list is as follows(python3.6.13 + pytorch1.4.0 + mmdet2.4.0 + mmcv-full1.1.5):
_libgcc_mutex 0.1 main https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
addict 2.4.0 pypi_0 pypi
blas 1.0 mkl https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
ca-certificates 2021.1.19 h06a4308_1 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
certifi 2020.12.5 py36h06a4308_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
cudatoolkit 10.1.243 h6bb024c_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
cycler 0.10.0 pypi_0 pypi
cython 0.29.22 pypi_0 pypi
freetype 2.10.4 h5ab3b9f_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
intel-openmp 2020.2 254 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
jpeg 9b h024ee3a_2 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
kiwisolver 1.3.1 pypi_0 pypi
lcms2 2.12 h3be6417_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
ld_impl_linux-64 2.33.1 h53a641e_7 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
libffi 3.3 he6710b0_2 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
libgcc-ng 9.1.0 hdf63c60_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
libgfortran-ng 7.3.0 hdf63c60_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
libpng 1.6.37 hbc83047_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
libstdcxx-ng 9.1.0 hdf63c60_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
libtiff 4.1.0 h2733197_1 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
lz4-c 1.9.3 h2531618_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
matplotlib 3.3.4 pypi_0 pypi
mkl 2020.2 256 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
mkl-service 2.3.0 py36he8ac12f_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
mkl_fft 1.3.0 py36h54f3939_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
mkl_random 1.1.1 py36h0573a6f_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
mmcv-full 1.1.5 pypi_0 pypi
mmdet 2.4.0 dev_0
mmpycocotools 12.0.3 pypi_0 pypi
ncurses 6.2 he6710b0_1 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
ninja 1.10.2 py36hff7bd54_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
numpy 1.19.2 py36h54aff64_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
numpy-base 1.19.2 py36hfa32c7d_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
olefile 0.46 py36_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
opencv-python 4.5.1.48 pypi_0 pypi
openssl 1.1.1k h27cfd23_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
pillow 8.2.0 py36he98fc37_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
pip 21.0.1 py36h06a4308_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
pyparsing 2.4.7 pypi_0 pypi
python 3.6.13 hdb3f193_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
python-dateutil 2.8.1 pypi_0 pypi
pytorch 1.4.0 py3.6_cuda10.1.243_cudnn7.6.3_0 pytorch
pyyaml 5.4.1 pypi_0 pypi
readline 8.1 h27cfd23_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
scipy 1.5.2 py36h0b6359f_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
setuptools 52.0.0 py36h06a4308_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
six 1.15.0 py36h06a4308_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
sqlite 3.35.4 hdfb4753_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
terminaltables 3.1.0 pypi_0 pypi
tk 8.6.10 hbc83047_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
torchvision 0.5.0 py36_cu101 pytorch
wheel 0.36.2 pyhd3eb1b0_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
xz 5.2.5 h7b6447c_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
yapf 0.31.0 pypi_0 pypi
zlib 1.2.11 h7b6447c_3 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
zstd 1.4.9 haebb681_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
I checked ISSUES in open-mmlab/mmdetection, someone said:
"This is not an error. It is normal when using the resnet pre-trained model as the conv1.bais has been absorbed in the conv1.weight."
But my network cannot continue training. Could you give me some guidance? Thank you!
Environment
sys.platform: linux
Python: 3.6.13 |Anaconda, Inc.| (default, Feb 23 2021, 21:15:04) [GCC 7.3.0]
CUDA available: True
CUDA_HOME: /usr/local/cuda
NVCC: Cuda compilation tools, release 10.1, V10.1.243
GPU 0,1,2,3: Tesla P100-PCIE-16GB
GCC: gcc (Ubuntu 5.4.0-6ubuntu1~16.04.12) 5.4.0 20160609
PyTorch: 1.4.0
PyTorch compiling details: PyTorch built with:
- GCC 7.3
- Intel(R) Math Kernel Library Version 2020.0.2 Product Build 20200624 for Intel(R) 64 architecture applications
- Intel(R) MKL-DNN v0.21.1 (Git Hash 7d2fd500bc78936d1d648ca713b901012f470dbc)
- OpenMP 201511 (a.k.a. OpenMP 4.5)
- NNPACK is enabled
- CUDA Runtime 10.1
- NVCC architecture flags: -gencode;arch=compute_37,code=sm_37;-gencode;arch=compute_50,code=sm_50;-gencode;arch=compute_60,code=sm_60;-gencode;arch=compute_61,code=sm_61;-gencode;arch=compute_70,code=sm_70;-gencode;arch=compute_75,code=sm_75;-gencode;arch=compute_37,code=compute_37
- CuDNN 7.6.3
- Magma 2.5.1
- Build settings: BLAS=MKL, BUILD_NAMEDTENSOR=OFF, BUILD_TYPE=Release, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -fopenmp -DUSE_FBGEMM -DUSE_QNNPACK -DUSE_PYTORCH_QNNPACK -O2 -fPIC -Wno-narrowing -Wall -Wextra -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-sign-compare -Wno-unused-parameter -Wno-unused-variable -Wno-unused-function -Wno-unused-result -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Wno-stringop-overflow, DISABLE_NUMA=1, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, USE_CUDA=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=ON, USE_MKLDNN=ON, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=ON, USE_OPENMP=ON, USE_STATIC_DISPATCH=OFF,
TorchVision: 0.5.0
OpenCV: 4.5.1
MMCV: 1.1.5
MMDetection: 2.4.0+c20cf32
MMDetection Compiler: GCC 7.3
MMDetection CUDA Compiler: 10.1
About code implementation
Does this workspace support the implementation of the journal version paper?
Efficient Person Search: An Anchor-Free Approach.
The implemention of scale alignment
Hi, thanks for your excellent work. However, I have some question about the implemention of scale alignment.
In your paper, it is said that you only make predictions based on a single layer of AFA. But in the forward function of mmdet/models/dense_heads/fcos_reid_head_focal_sub_triqueue.py, feature of different FPN level are all used for detection and reid.
I am looking forward to your reply.
How to use the Occlusion and Resolution on CUHK dataset?
here I only find how to change the gallery_size, but I
don't know how to use the Occlusion and Resolution on CUHK dataset, Have you done research in this area, or can you give me some advice? Thank you very much for your help!
Cuda out of memory!
I reproduce the paper and an error occured, I use the prompt nvidia-smi,my GPU have 14% usage. Then what should I do to solve the problem?
I will be appreciate if you can help me.
The detail of the problem is in the following:
(lph) g303@g303:~/lph/AlignPS-master$ /bin/bash /home/g303/lph/AlignPS-master/run_train.sh
2021-07-06 16:59:41,544 - mmdet - INFO - Environment info:
sys.platform: linux
Python: 3.8.10 (default, Jun 4 2021, 15:09:15) [GCC 7.5.0]
CUDA available: True
CUDA_HOME: /usr/local/cuda
NVCC: Build cuda_11.3.r11.3/compiler.29920130_0
GPU 0: NVIDIA GeForce RTX 2070 SUPER
GCC: gcc (Ubuntu 7.5.0-3ubuntu1~18.04) 7.5.0
PyTorch: 1.7.0+cu110
PyTorch compiling details: PyTorch built with:
- GCC 7.3
- C++ Version: 201402
- Intel(R) oneAPI Math Kernel Library Version 2021.2-Product Build 20210312 for Intel(R) 64 architecture applications
- Intel(R) MKL-DNN v1.6.0 (Git Hash 5ef631a030a6f73131c77892041042805a06064f)
- OpenMP 201511 (a.k.a. OpenMP 4.5)
- NNPACK is enabled
- CPU capability usage: AVX2
- CUDA Runtime 11.0
- NVCC architecture flags: -gencode;arch=compute_37,code=sm_37;-gencode;arch=compute_50,code=sm_50;-gencode;arch=compute_60,code=sm_60;-gencode;arch=compute_70,code=sm_70;-gencode;arch=compute_75,code=sm_75;-gencode;arch=compute_80,code=sm_80
- CuDNN 8.0.4
- Magma 2.5.2
- Build settings: BLAS=MKL, BUILD_TYPE=Release, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -fopenmp -DNDEBUG -DUSE_FBGEMM -DUSE_QNNPACK -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DUSE_VULKAN_WRAPPER -O2 -fPIC -Wno-narrowing -Wall -Wextra -Werror=return-type -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-sign-compare -Wno-unused-parameter -Wno-unused-variable -Wno-unused-function -Wno-unused-result -Wno-unused-local-typedefs -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Wno-stringop-overflow, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, USE_CUDA=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=ON, USE_MKLDNN=ON, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=ON, USE_OPENMP=ON,
TorchVision: 0.8.1+cu110
OpenCV: 4.5.2
MMCV: 1.1.5
MMDetection: 2.4.0+unknown
MMDetection Compiler: GCC 7.5
MMDetection CUDA Compiler: 11.3
2021-07-06 16:59:42,319 - mmdet - INFO - Distributed training: False
2021-07-06 16:59:43,098 - mmdet - INFO - Config:
dataset_type = 'CuhkDataset'
data_root = '/home/g303/lph/datasets/PRW-v16.04.20/'
img_norm_cfg = dict(
mean=[103.53, 116.28, 123.675], std=[1.0, 1.0, 1.0], to_rgb=False)
train_pipeline = [
dict(type='LoadImageFromFile'),
dict(type='LoadAnnotations', with_bbox=True),
dict(
type='Resize',
img_scale=[(667, 400), (1000, 600), (1333, 800), (1500, 900),
(1666, 1000), (2000, 1200)],
multiscale_mode='value',
keep_ratio=True),
dict(type='RandomFlip', flip_ratio=0.5),
dict(
type='Normalize',
mean=[103.53, 116.28, 123.675],
std=[1.0, 1.0, 1.0],
to_rgb=False),
dict(type='Pad', size_divisor=32),
dict(type='DefaultFormatBundle'),
dict(type='Collect', keys=['img', 'gt_bboxes', 'gt_labels', 'gt_ids'])
]
test_pipeline = [
dict(type='LoadImageFromFile'),
dict(
type='MultiScaleFlipAug',
img_scale=(1500, 900),
flip=False,
transforms=[
dict(type='Resize', keep_ratio=True),
dict(type='RandomFlip'),
dict(
type='Normalize',
mean=[103.53, 116.28, 123.675],
std=[1.0, 1.0, 1.0],
to_rgb=False),
dict(type='Pad', size_divisor=32),
dict(type='ImageToTensor', keys=['img']),
dict(type='Collect', keys=['img'])
])
]
data = dict(
samples_per_gpu=4,
workers_per_gpu=4,
train=dict(
type='CuhkDataset',
ann_file='/home/g303/lph/datasets/PRW-v16.04.20/train_pid.json',
img_prefix='/home/g303/lph/datasets/PRW-v16.04.20/frames/',
pipeline=[
dict(type='LoadImageFromFile'),
dict(type='LoadAnnotations', with_bbox=True),
dict(
type='Resize',
img_scale=[(667, 400), (1000, 600), (1333, 800), (1500, 900),
(1666, 1000), (2000, 1200)],
multiscale_mode='value',
keep_ratio=True),
dict(type='RandomFlip', flip_ratio=0.5),
dict(
type='Normalize',
mean=[103.53, 116.28, 123.675],
std=[1.0, 1.0, 1.0],
to_rgb=False),
dict(type='Pad', size_divisor=32),
dict(type='DefaultFormatBundle'),
dict(
type='Collect',
keys=['img', 'gt_bboxes', 'gt_labels', 'gt_ids'])
]),
val=dict(
type='CuhkDataset',
ann_file='/home/g303/lph/datasets/PRW-v16.04.20/test_pid.json',
img_prefix='/home/g303/lph/datasets/PRW-v16.04.20/frames/',
pipeline=[
dict(type='LoadImageFromFile'),
dict(
type='MultiScaleFlipAug',
img_scale=(1500, 900),
flip=False,
transforms=[
dict(type='Resize', keep_ratio=True),
dict(type='RandomFlip'),
dict(
type='Normalize',
mean=[103.53, 116.28, 123.675],
std=[1.0, 1.0, 1.0],
to_rgb=False),
dict(type='Pad', size_divisor=32),
dict(type='ImageToTensor', keys=['img']),
dict(type='Collect', keys=['img'])
])
]),
test=dict(
type='CuhkDataset',
ann_file='/home/g303/lph/datasets/PRW-v16.04.20/test_pid.json',
img_prefix='/home/g303/lph/datasets/PRW-v16.04.20/frames/',
proposal_file=
'/home/g303/lph/datasets/PRW-v16.04.20/annotation/test/train_test/TestG50.mat',
pipeline=[
dict(type='LoadImageFromFile'),
dict(
type='MultiScaleFlipAug',
img_scale=(1500, 900),
flip=False,
transforms=[
dict(type='Resize', keep_ratio=True),
dict(type='RandomFlip'),
dict(
type='Normalize',
mean=[103.53, 116.28, 123.675],
std=[1.0, 1.0, 1.0],
to_rgb=False),
dict(type='Pad', size_divisor=32),
dict(type='ImageToTensor', keys=['img']),
dict(type='Collect', keys=['img'])
])
]))
evaluation = dict(interval=1, metric='bbox')
optimizer = dict(
type='SGD',
lr=0.001,
momentum=0.9,
weight_decay=0.001,
paramwise_cfg=dict(bias_lr_mult=2.0, bias_decay_mult=0.0))
optimizer_config = dict(grad_clip=dict(max_norm=35, norm_type=2))
lr_config = dict(
policy='step',
warmup='linear',
warmup_iters=500,
warmup_ratio=0.3333333333333333,
step=[16, 22])
total_epochs = 24
checkpoint_config = dict(interval=1)
log_config = dict(interval=50, hooks=[dict(type='TextLoggerHook')])
dist_params = dict(backend='nccl')
log_level = 'INFO'
load_from = None
resume_from = None
workflow = [('train', 1)]
model = dict(
type='FCOSReid',
pretrained='open-mmlab://detectron2/resnet50_caffe',
backbone=dict(
type='ResNet',
depth=50,
num_stages=4,
out_indices=(0, 1, 2, 3),
frozen_stages=1,
norm_cfg=dict(type='BN', requires_grad=False),
norm_eval=True,
style='caffe'),
neck=dict(
type='FPNDcnLconv3Dcn',
in_channels=[256, 512, 1024, 2048],
out_channels=256,
start_level=1,
add_extra_convs=True,
extra_convs_on_inputs=False,
num_outs=5,
relu_before_extra_convs=True),
bbox_head=dict(
type='FCOSReidHeadFocalOimSub',
num_classes=1,
in_channels=256,
stacked_convs=4,
feat_channels=256,
strides=[8, 16, 32, 64, 128],
loss_cls=dict(
type='FocalLoss',
use_sigmoid=True,
gamma=2.0,
alpha=0.25,
loss_weight=1.0),
loss_bbox=dict(type='GIoULoss', loss_weight=1.0),
loss_centerness=dict(
type='CrossEntropyLoss', use_sigmoid=True, loss_weight=1.0),
unlabel_weight=10,
temperature=15,
label_norm=True,
num_person=483,
queue_size=500,
norm_on_bbox=True,
centerness_on_reg=True,
dcn_on_last_conv=True,
center_sampling=True,
conv_bias=True))
train_cfg = dict(
assigner=dict(
type='MaxIoUAssigner',
pos_iou_thr=0.5,
neg_iou_thr=0.4,
min_pos_iou=0,
ignore_iof_thr=-1),
allowed_border=-1,
pos_weight=-1,
debug=False)
test_cfg = dict(
nms_pre=1000,
min_bbox_size=0,
score_thr=0.05,
nms=dict(type='nms', iou_threshold=0.5),
max_per_img=100)
work_dir = './work_dirs/prw_base_focal_labelnorm_sub_ldcn_fg15_wd1-3'
gpu_ids = [0]
/home/g303/anaconda3/envs/lph/lib/python3.8/site-packages/mmcv/cnn/bricks/conv_module.py:100: UserWarning: ConvModule has norm and bias at the same time
warnings.warn('ConvModule has norm and bias at the same time')
2021-07-06 16:59:43,348 - mmdet - INFO - load model from: open-mmlab://detectron2/resnet50_caffe
2021-07-06 16:59:43,409 - mmdet - WARNING - The model and loaded state dict do not match exactly
unexpected key in source state_dict: conv1.bias
loading annotations into memory...
Done (t=0.03s)
creating index...
index created!
2021-07-06 16:59:45,482 - mmdet - INFO - Start running, host: g303@g303, work_dir: /home/g303/lph/AlignPS-master/work_dirs/prw_base_focal_labelnorm_sub_ldcn_fg15_wd1-3
2021-07-06 16:59:45,482 - mmdet - INFO - workflow: [('train', 1)], max: 24 epochs
/home/g303/anaconda3/envs/lph/lib/python3.8/site-packages/torch/nn/functional.py:2952: UserWarning: nn.functional.upsample is deprecated. Use nn.functional.interpolate instead.
warnings.warn("nn.functional.upsample is deprecated. Use nn.functional.interpolate instead.")
/home/g303/anaconda3/envs/lph/lib/python3.8/site-packages/torch/nn/functional.py:3060: UserWarning: Default upsampling behavior when mode=bilinear is changed to align_corners=False since 0.4.0. Please specify align_corners=True if the old behavior is desired. See the documentation of nn.Upsample for details.
warnings.warn("Default upsampling behavior when mode={} is changed "
/home/g303/lph/AlignPS-master/mmdet/models/dense_heads/fcos_reid_head_focal_oim_sub.py:316: UserWarning: This overload of nonzero is deprecated:
nonzero()
Consider using one of the following signatures instead:
nonzero(*, bool as_tuple) (Triggered internally at /pytorch/torch/csrc/utils/python_arg_parser.cpp:882.)
pos_inds = ((flatten_labels >= 0)
Traceback (most recent call last):
File "tools/train.py", line 177, in
main()
File "tools/train.py", line 166, in main
train_detector(
File "/home/g303/lph/AlignPS-master/mmdet/apis/train.py", line 147, in train_detector
runner.run(data_loaders, cfg.workflow, cfg.total_epochs)
File "/home/g303/anaconda3/envs/lph/lib/python3.8/site-packages/mmcv/runner/epoch_based_runner.py", line 125, in run
epoch_runner(data_loaders[i], **kwargs)
File "/home/g303/anaconda3/envs/lph/lib/python3.8/site-packages/mmcv/runner/epoch_based_runner.py", line 50, in train
self.run_iter(data_batch, train_mode=True)
File "/home/g303/anaconda3/envs/lph/lib/python3.8/site-packages/mmcv/runner/epoch_based_runner.py", line 29, in run_iter
outputs = self.model.train_step(data_batch, self.optimizer,
File "/home/g303/anaconda3/envs/lph/lib/python3.8/site-packages/mmcv/parallel/data_parallel.py", line 67, in train_step
return self.module.train_step(*inputs[0], **kwargs[0])
File "/home/g303/lph/AlignPS-master/mmdet/models/detectors/base.py", line 234, in train_step
losses = self(**data)
File "/home/g303/anaconda3/envs/lph/lib/python3.8/site-packages/torch/nn/modules/module.py", line 727, in _call_impl
result = self.forward(*input, **kwargs)
File "/home/g303/lph/AlignPS-master/mmdet/core/fp16/decorators.py", line 51, in new_func
return old_func(*args, **kwargs)
File "/home/g303/lph/AlignPS-master/mmdet/models/detectors/base.py", line 168, in forward
return self.forward_train(img, img_metas, **kwargs)
File "/home/g303/lph/AlignPS-master/mmdet/models/detectors/single_stage_reid.py", line 94, in forward_train
x = self.extract_feat(img)
File "/home/g303/lph/AlignPS-master/mmdet/models/detectors/single_stage_reid.py", line 56, in extract_feat
x = self.neck(x)
File "/home/g303/anaconda3/envs/lph/lib/python3.8/site-packages/torch/nn/modules/module.py", line 727, in _call_impl
result = self.forward(*input, **kwargs)
File "/home/g303/lph/AlignPS-master/mmdet/core/fp16/decorators.py", line 51, in new_func
return old_func(*args, **kwargs)
File "/home/g303/lph/AlignPS-master/mmdet/models/necks/fpn_dcn_lconv3_dcn.py", line 203, in forward
outs = [
File "/home/g303/lph/AlignPS-master/mmdet/models/necks/fpn_dcn_lconv3_dcn.py", line 204, in
self.fpn_convsi for i in range(used_backbone_levels)
File "/home/g303/anaconda3/envs/lph/lib/python3.8/site-packages/torch/nn/modules/module.py", line 727, in _call_impl
result = self.forward(*input, **kwargs)
File "/home/g303/anaconda3/envs/lph/lib/python3.8/site-packages/mmcv/ops/deform_conv.py", line 288, in forward
return deform_conv2d(x, offset, self.weight, self.stride, self.padding,
File "/home/g303/anaconda3/envs/lph/lib/python3.8/site-packages/mmcv/ops/deform_conv.py", line 73, in forward
ext_module.deform_conv_forward(
RuntimeError: CUDA out of memory. Tried to allocate 2.01 GiB (GPU 0; 7.79 GiB total capacity; 4.92 GiB already allocated; 164.56 MiB free; 6.21 GiB reserved in total by PyTorch)
oim_tri.py
thx for your great work! I wonder if Class OIMLossNewFocal in oim_tri.py can be used as a loss to replace [oim.py] (https://github.com/DeanChan/NAE4PS/blob/master/lib/loss/oim.py) and how to used it
can somebody help me
(open-mmlab) a@b:~/AlignPS$ sh run_test.sh
Traceback (most recent call last):
File "./tools/test.py", line 13, in
from mmdet.apis import multi_gpu_test, single_gpu_test
File "/home/a/AlignPS/mmdet/apis/init.py", line 1, in
from .inference import (async_inference_detector, inference_detector,
File "/home/a/AlignPS/mmdet/apis/inference.py", line 7, in
from mmcv.ops import RoIAlign, RoIPool
File "/home/a/anaconda3/envs/open-mmlab/lib/python3.7/site-packages/mmcv/ops/init.py", line 3, in
from .cc_attention import CrissCrossAttention
File "/home/a/anaconda3/envs/open-mmlab/lib/python3.7/site-packages/mmcv/ops/cc_attention.py", line 10, in
'_ext', ['ca_forward', 'ca_backward', 'ca_map_forward', 'ca_map_backward'])
File "/home/a/anaconda3/envs/open-mmlab/lib/python3.7/site-packages/mmcv/utils/ext_loader.py", line 13, in load_ext
assert hasattr(ext, fun), f'{fun} miss in module {name}'
AssertionError: ca_forward miss in module _ext
Traceback (most recent call last):
File "/home/a/anaconda3/envs/open-mmlab/lib/python3.7/runpy.py", line 193, in _run_module_as_main
"main", mod_spec)
File "/home/a/anaconda3/envs/open-mmlab/lib/python3.7/runpy.py", line 85, in _run_code
exec(code, run_globals)
File "/home/a/anaconda3/envs/open-mmlab/lib/python3.7/site-packages/torch/distributed/launch.py", line 260, in
main()
File "/home/a/anaconda3/envs/open-mmlab/lib/python3.7/site-packages/torch/distributed/launch.py", line 256, in main
cmd=cmd)
subprocess.CalledProcessError: Command '['/home/a/anaconda3/envs/open-mmlab/bin/python', '-u', './tools/test.py', '--local_rank=0', './configs/fcos/fcos_center-normbbox-centeronreg-giou_r50_caffe_fpn_gn-head_dcn_4x4_1x_cuhk_reid_1500_stage1_fpncat_dcn_epoch24_multiscale_focal_x4_bg-2_lconv3dcn_sub_triqueue_dcn0.py', 'work_dirs/fcos_center-normbbox-centeronreg-giou_r50_caffe_fpn_gn-head_dcn_4x4_1x_cuhk_reid_1500_stage1_fpncat_dcn_epoch24_multiscale_focal_x4_bg-2_lconv3dcn_sub_triqueue_dcn0/cuhk_alignps.pth', '--launcher', 'pytorch', '--out', 'work_dirs/fcos_center-normbbox-centeronreg-giou_r50_caffe_fpn_gn-head_dcn_4x4_1x_cuhk_reid_1500_stage1_fpncat_dcn_epoch24_multiscale_focal_x4_bg-2_lconv3dcn_sub_triqueue_dcn0/results_1000.pkl']' returned non-zero exit status 1.
Can't find any TestG50.mat file in PRW dataset
I downloaded the PRW dataset by following your link, then i extracted this file but I can't find any TestG50.mat file in PRW dataset
https://github.com/daodaofr/AlignPS/blob/master/configs/fcos/prw_base_focal_labelnorm_sub_ldcn_fg15_wd1-3.py#L74
Can you show me how to get this file?
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