mmdetection
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open-mmlab
import custom model error
I run tools/train.py on my machine and got a KeyError! 2022-05-14 15:19:32,105 - mmdet - INFO - Set random seed to 640356377, deterministic: False Traceback (most recent call last): File "/home/sdxx/hgf/anaconda3/envs/mmdet/lib/python3.8/site-packages/mmcv/utils/registry.py", line 52, in build_from_cfg return obj_cls(**args) File "/home/sdxx/hgf/anaconda3/envs/mmdet/lib/python3.8/site-packages/mmdet/models/detectors/yolox.py", line 58, in init super(YOLOX, self).init(backbone, neck, bbox_head, train_cfg, File "/home/sdxx/hgf/anaconda3/envs/mmdet/lib/python3.8/site-packages/mmdet/models/detectors/single_stage.py", line 32, in init self.backbone = build_backbone(backbone) File "/home/sdxx/hgf/anaconda3/envs/mmdet/lib/python3.8/site-packages/mmdet/models/builder.py", line 20, in build_backbone return BACKBONES.build(cfg) File "/home/sdxx/hgf/anaconda3/envs/mmdet/lib/python3.8/site-packages/mmcv/utils/registry.py", line 212, in build return self.build_func(*args, **kwargs, registry=self) File "/home/sdxx/hgf/anaconda3/envs/mmdet/lib/python3.8/site-packages/mmcv/cnn/builder.py", line 27, in build_model_from_cfg return build_from_cfg(cfg, registry, default_args) File "/home/sdxx/hgf/anaconda3/envs/mmdet/lib/python3.8/site-packages/mmcv/utils/registry.py", line 44, in build_from_cfg raise KeyError( KeyError: 'ConvNeXt is not in the models registry'
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "tools/train.py", line 237, in
However, i run it on pycharm with ssh interpreter, and the code works
Sorry, i think i didn’t describe my question clearly, all I want to ask is , i run the code with pycharm by ssh liking my server ,no error occur, but run the code in server shell got a error. For more information,I would like describing my question again in Chinese. 我在pycharm上通过ssh远程连接服务器，然后在pycharm上运行代码，没有报错。但是在服务器的终端上运行代码就报错？ convnext我已经实现并通过加入到mmdet/models/backbones/init.py里面了，也通过custom_imports加入到配置文件中了
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------------------ Original ------------------ From: Cedric Luo @.> Date: Sat,May 14,2022 7:09 PM To: open-mmlab/mmdetection @.> Cc: GF1447571253 @.>, Author @.> Subject: Re: [open-mmlab/mmdetection] import custom model error (Issue #7983)
ConvNeXt is not support yet, #7281
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Please check whether convnext exists on the sever and whether you use the expected the conda or pip environment.
yes, I'm sure that i have check convnext on mmdetection/mmdet/models/backbones/ folders and conda envs is same whether pycharm or shell.
and i have tried to add the code below
custom_imports = dict(
imports=[
'mmdet.models.backbones._csp_darknet.py'
],
allow_failed_imports=False)
and it turns out
(mmdet) sdxx@sdxx-Precision-5820-Tower:~/hgf/mmdetection$ python tools/train.py
Traceback (most recent call last):
File "/home/sdxx/hgf/anaconda3/envs/mmdet/lib/python3.8/site-packages/mmcv/utils/misc.py", line 73, in import_modules_from_strings
imported_tmp = import_module(imp)
File "/home/sdxx/hgf/anaconda3/envs/mmdet/lib/python3.8/importlib/init.py", line 127, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
File "
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "tools/train.py", line 237, in
In the picture, the path is mmdet.models.backbones.csp_darknet.py, not mmdet.models.backbones._csp_darknet.py
yes, i just want to show you convnext existing, _csp_darknet.py is in the bottom.
Please paste your config file and your env infomation when running in terminal. By the way, ConvNext is supported in mmclassification https://github.com/open-mmlab/mmclassification/tree/master/configs/convnext, you can directly used in mmdet
I copied yolox_head.py and pasted in a new a python file named yolox_head_with_iou_aware.py in which the class name is YOLOXHead_. Similarly, I new a sim_ota_assigner.py in which the class name is SimOTAAssigner_. Thank for your help. (mmdet) sdxx@sdxx-Precision-5820-Tower:~/hgf/mmdetection$ pip install -v -e . Using pip 21.2.4 from /home/sdxx/.local/lib/python3.6/site-packages/pip (python 3.6) Defaulting to user installation because normal site-packages is not writeable Obtaining file:///home/sdxx/hgf/mmdetection Running command python setup.py egg_info running egg_info creating /tmp/pip-pip-egg-info-prd__y7y/mmdet.egg-info writing /tmp/pip-pip-egg-info-prd__y7y/mmdet.egg-info/PKG-INFO writing dependency_links to /tmp/pip-pip-egg-info-prd__y7y/mmdet.egg-info/dependency_links.txt writing requirements to /tmp/pip-pip-egg-info-prd__y7y/mmdet.egg-info/requires.txt writing top-level names to /tmp/pip-pip-egg-info-prd__y7y/mmdet.egg-info/top_level.txt writing manifest file '/tmp/pip-pip-egg-info-prd__y7y/mmdet.egg-info/SOURCES.txt' reading manifest file '/tmp/pip-pip-egg-info-prd__y7y/mmdet.egg-info/SOURCES.txt' reading manifest template 'MANIFEST.in' warning: no files found matching 'mmdet/VERSION' warning: no files found matching 'mmdet/.mim/demo//' adding license file 'LICENSE' writing manifest file '/tmp/pip-pip-egg-info-prd__y7y/mmdet.egg-info/SOURCES.txt' Requirement already satisfied: matplotlib in /home/sdxx/.local/lib/python3.6/site-packages (from mmdet==2.24.1) (3.3.4) Requirement already satisfied: numpy in /home/sdxx/.local/lib/python3.6/site-packages (from mmdet==2.24.1) (1.19.5) Requirement already satisfied: pycocotools in /home/sdxx/.local/lib/python3.6/site-packages (from mmdet==2.24.1) (2.0.4) Requirement already satisfied: six in /home/sdxx/.local/lib/python3.6/site-packages (from mmdet==2.24.1) (1.15.0) Requirement already satisfied: terminaltables in /home/sdxx/.local/lib/python3.6/site-packages (from mmdet==2.24.1) (3.1.10) Requirement already satisfied: cycler>=0.10 in /home/sdxx/.local/lib/python3.6/site-packages (from matplotlib->mmdet==2.24.1) (0.10.0) Requirement already satisfied: kiwisolver>=1.0.1 in /home/sdxx/.local/lib/python3.6/site-packages (from matplotlib->mmdet==2.24.1) (1.3.1) Requirement already satisfied: python-dateutil>=2.1 in /home/sdxx/.local/lib/python3.6/site-packages (from matplotlib->mmdet==2.24.1) (2.8.2) Requirement already satisfied: pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=2.0.3 in /home/sdxx/.local/lib/python3.6/site-packages (from matplotlib->mmdet==2.24.1) (2.4.7) Requirement already satisfied: pillow>=6.2.0 in /home/sdxx/.local/lib/python3.6/site-packages (from matplotlib->mmdet==2.24.1) (8.3.2) Installing collected packages: mmdet Attempting uninstall: mmdet Found existing installation: mmdet 2.24.1 Uninstalling mmdet-2.24.1: Removing file or directory /home/sdxx/.local/lib/python3.6/site-packages/mmdet.egg-link Removing pth entries from /home/sdxx/.local/lib/python3.6/site-packages/easy-install.pth: Removing entry: /home/sdxx/hgf/mmdetection Successfully uninstalled mmdet-2.24.1 Running setup.py develop for mmdet Running command /usr/bin/python3 -c 'import io, os, sys, setuptools, tokenize; sys.argv[0] = '"'"'/home/sdxx/hgf/mmdetection/setup.py'"'"'; file='"'"'/home/sdxx/hgf/mmdetection/setup.py'"'"';f = getattr(tokenize, '"'"'open'"'"', open)(file) if os.path.exists(file) else io.StringIO('"'"'from setuptools import setup; setup()'"'"');code = f.read().replace('"'"'\r\n'"'"', '"'"'\n'"'"');f.close();exec(compile(code, file, '"'"'exec'"'"'))' develop --no-deps --user --prefix= running develop running egg_info writing mmdet.egg-info/PKG-INFO writing dependency_links to mmdet.egg-info/dependency_links.txt writing requirements to mmdet.egg-info/requires.txt writing top-level names to mmdet.egg-info/top_level.txt reading manifest file 'mmdet.egg-info/SOURCES.txt' reading manifest template 'MANIFEST.in' warning: no files found matching 'mmdet/VERSION' warning: no files found matching 'mmdet/.mim/demo//' adding license file 'LICENSE' writing manifest file 'mmdet.egg-info/SOURCES.txt' running build_ext Creating /home/sdxx/.local/lib/python3.6/site-packages/mmdet.egg-link (link to .) Adding mmdet 2.24.1 to easy-install.pth file
Installed /home/sdxx/hgf/mmdetection
Successfully installed mmdet-2.24.1
Could not fetch URL https://pypi.org/simple/pip/: There was a problem confirming the ssl certificate: HTTPSConnectionPool(host='pypi.org', port=443): Max retries exceeded with url: /simple/pip/ (Caused by SSLError(SSLError(1, '[SSL: CERTIFICATE_VERIFY_FAILED] certificate verify failed (_ssl.c:852)'),)) - skipping (mmdet) sdxx@sdxx-Precision-5820-Tower:~/hgf/mmdetection$ (mmdet) sdxx@sdxx-Precision-5820-Tower:~/hgf/mmdetection$ python tools/train.py /home/sdxx/hgf/anaconda3/envs/mmdet/lib/python3.8/site-packages/mmdet/utils/setup_env.py:38: UserWarning: Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. warnings.warn( /home/sdxx/hgf/anaconda3/envs/mmdet/lib/python3.8/site-packages/mmdet/utils/setup_env.py:48: UserWarning: Setting MKL_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. warnings.warn( 2022-05-19 09:28:01,205 - mmdet - INFO - Environment info:
sys.platform: linux Python: 3.8.13 (default, Mar 28 2022, 11:38:47) [GCC 7.5.0] CUDA available: True GPU 0: NVIDIA GeForce RTX 3090 CUDA_HOME: :/usr/local/cuda GCC: gcc (Ubuntu 7.5.0-3ubuntu1~18.04) 7.5.0 PyTorch: 1.8.0 PyTorch compiling details: PyTorch built with:
- GCC 7.3
- C++ Version: 201402
- Intel(R) oneAPI Math Kernel Library Version 2021.4-Product Build 20210904 for Intel(R) 64 architecture applications
- Intel(R) MKL-DNN v1.7.0 (Git Hash 7aed236906b1f7a05c0917e5257a1af05e9ff683)
- OpenMP 201511 (a.k.a. OpenMP 4.5)
- NNPACK is enabled
- CPU capability usage: AVX2
- CUDA Runtime 11.1
- 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_80,code=sm_80;-gencode;arch=compute_86,code=sm_86;-gencode;arch=compute_37,code=compute_37
- CuDNN 8.0.5
- Magma 2.5.2
- Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, CUDA_VERSION=11.1, CUDNN_VERSION=8.0.5, CXX_COMPILER=/opt/rh/devtoolset-7/root/usr/bin/c++, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -fopenmp -DNDEBUG -DUSE_KINETO -DUSE_FBGEMM -DUSE_QNNPACK -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -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, LAPACK_INFO=mkl, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_VERSION=1.8.0, USE_CUDA=ON, USE_CUDNN=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: 0.9.0 OpenCV: 4.5.5 MMCV: 1.4.2 MMCV Compiler: GCC 7.3 MMCV CUDA Compiler: 11.1 MMDetection: 2.24.1+240d7a3
2022-05-19 09:28:01,435 - mmdet - INFO - Distributed training: False 2022-05-19 09:28:01,622 - mmdet - INFO - Config: optimizer = dict( type='SGD', lr=0.01, momentum=0.9, weight_decay=0.0005, nesterov=True, paramwise_cfg=dict(norm_decay_mult=0.0, bias_decay_mult=0.0)) optimizer_config = dict(grad_clip=None) lr_config = dict( policy='YOLOX', warmup='exp', by_epoch=False, warmup_by_epoch=True, warmup_ratio=1, warmup_iters=5, num_last_epochs=15, min_lr_ratio=0.05) runner = dict(type='EpochBasedRunner', max_epochs=100) checkpoint_config = dict(interval=10) log_config = dict(interval=50, hooks=[dict(type='TextLoggerHook')]) custom_hooks = [ dict(type='YOLOXModeSwitchHook', num_last_epochs=15, priority=48), dict(type='SyncNormHook', num_last_epochs=15, interval=10, priority=48), dict( type='ExpMomentumEMAHook', resume_from=None, momentum=0.0001, priority=49) ] dist_params = dict(backend='nccl') log_level = 'INFO' load_from = None resume_from = None workflow = [('train', 1)] opencv_num_threads = 0 mp_start_method = 'fork' auto_scale_lr = dict(enable=False, base_batch_size=16) img_scale = (640, 640) model = dict( type='YOLOX', input_size=(640, 640), random_size_range=(15, 25), random_size_interval=10, backbone=dict(type='CSPDarknet', deepen_factor=0.33, widen_factor=0.5), neck=dict( type='YOLOXPAFPN', in_channels=[128, 256, 512], out_channels=128, num_csp_blocks=1), bbox_head=dict( type='YOLOXHead_', num_classes=80, in_channels=128, feat_channels=128), train_cfg=dict(assigner=dict(type='SimOTAAssigner_', center_radius=2.5)), test_cfg=dict(score_thr=0.01, nms=dict(type='nms', iou_threshold=0.65))) data_root = '/data/coco/' dataset_type = 'CocoDataset' train_pipeline = [ dict(type='Mosaic', img_scale=(640, 640), pad_val=114.0), dict( type='RandomAffine', scaling_ratio_range=(0.1, 2), border=(-320, -320)), dict( type='MixUp', img_scale=(640, 640), ratio_range=(0.8, 1.6), pad_val=114.0), dict(type='YOLOXHSVRandomAug'), dict(type='RandomFlip', flip_ratio=0.5), dict(type='Resize', img_scale=(640, 640), keep_ratio=True), dict( type='Pad', pad_to_square=True, pad_val=dict(img=(114.0, 114.0, 114.0))), dict(type='FilterAnnotations', min_gt_bbox_wh=(1, 1), keep_empty=False), dict(type='DefaultFormatBundle'), dict(type='Collect', keys=['img', 'gt_bboxes', 'gt_labels']) ] train_dataset = dict( type='MultiImageMixDataset', dataset=dict( type='CocoDataset', ann_file='/data/coco/annotations/instances_train2017.json', img_prefix='/data/coco/images/train2017/', pipeline=[ dict(type='LoadImageFromFile'), dict(type='LoadAnnotations', with_bbox=True) ], filter_empty_gt=False), pipeline=[ dict(type='Mosaic', img_scale=(640, 640), pad_val=114.0), dict( type='RandomAffine', scaling_ratio_range=(0.1, 2), border=(-320, -320)), dict( type='MixUp', img_scale=(640, 640), ratio_range=(0.8, 1.6), pad_val=114.0), dict(type='YOLOXHSVRandomAug'), dict(type='RandomFlip', flip_ratio=0.5), dict(type='Resize', img_scale=(640, 640), keep_ratio=True), dict( type='Pad', pad_to_square=True, pad_val=dict(img=(114.0, 114.0, 114.0))), dict( type='FilterAnnotations', min_gt_bbox_wh=(1, 1), keep_empty=False), dict(type='DefaultFormatBundle'), dict(type='Collect', keys=['img', 'gt_bboxes', 'gt_labels']) ]) test_pipeline = [ dict(type='LoadImageFromFile'), dict( type='MultiScaleFlipAug', img_scale=(640, 640), flip=False, transforms=[ dict(type='Resize', keep_ratio=True), dict(type='RandomFlip'), dict( type='Pad', pad_to_square=True, pad_val=dict(img=(114.0, 114.0, 114.0))), dict(type='DefaultFormatBundle'), dict(type='Collect', keys=['img']) ]) ] data = dict( samples_per_gpu=16, workers_per_gpu=8, persistent_workers=True, train=dict( type='MultiImageMixDataset', dataset=dict( type='CocoDataset', ann_file='/data/coco/annotations/instances_train2017.json', img_prefix='/data/coco/images/train2017/', pipeline=[ dict(type='LoadImageFromFile'), dict(type='LoadAnnotations', with_bbox=True) ], filter_empty_gt=False), pipeline=[ dict(type='Mosaic', img_scale=(640, 640), pad_val=114.0), dict( type='RandomAffine', scaling_ratio_range=(0.1, 2), border=(-320, -320)), dict( type='MixUp', img_scale=(640, 640), ratio_range=(0.8, 1.6), pad_val=114.0), dict(type='YOLOXHSVRandomAug'), dict(type='RandomFlip', flip_ratio=0.5), dict(type='Resize', img_scale=(640, 640), keep_ratio=True), dict( type='Pad', pad_to_square=True, pad_val=dict(img=(114.0, 114.0, 114.0))), dict( type='FilterAnnotations', min_gt_bbox_wh=(1, 1), keep_empty=False), dict(type='DefaultFormatBundle'), dict(type='Collect', keys=['img', 'gt_bboxes', 'gt_labels']) ]), val=dict( type='CocoDataset', ann_file='/data/coco/annotations/instances_val2017.json', img_prefix='/data/coco/images/val2017/', pipeline=[ dict(type='LoadImageFromFile'), dict( type='MultiScaleFlipAug', img_scale=(640, 640), flip=False, transforms=[ dict(type='Resize', keep_ratio=True), dict(type='RandomFlip'), dict( type='Pad', pad_to_square=True, pad_val=dict(img=(114.0, 114.0, 114.0))), dict(type='DefaultFormatBundle'), dict(type='Collect', keys=['img']) ]) ]), test=dict( type='CocoDataset', ann_file='/data/coco/annotations/instances_val2017.json', img_prefix='/data/coco/images/val2017/', pipeline=[ dict(type='LoadImageFromFile'), dict( type='MultiScaleFlipAug', img_scale=(640, 640), flip=False, transforms=[ dict(type='Resize', keep_ratio=True), dict(type='RandomFlip'), dict( type='Pad', pad_to_square=True, pad_val=dict(img=(114.0, 114.0, 114.0))), dict(type='DefaultFormatBundle'), dict(type='Collect', keys=['img']) ]) ])) max_epochs = 100 num_last_epochs = 15 interval = 10 evaluation = dict( save_best='auto', interval=10, dynamic_intervals=[(85, 1)], metric='bbox') work_dir = './work_dirs/modified_yolox_s_1x16_100e_coco' auto_resume = False gpu_ids = [0]
2022-05-19 09:28:01,622 - mmdet - INFO - Set random seed to 839702807, deterministic: False Traceback (most recent call last): File "/home/sdxx/hgf/anaconda3/envs/mmdet/lib/python3.8/site-packages/mmcv/utils/registry.py", line 52, in build_from_cfg return obj_cls(**args) File "/home/sdxx/hgf/anaconda3/envs/mmdet/lib/python3.8/site-packages/mmdet/models/detectors/yolox.py", line 58, in init super(YOLOX, self).init(backbone, neck, bbox_head, train_cfg, File "/home/sdxx/hgf/anaconda3/envs/mmdet/lib/python3.8/site-packages/mmdet/models/detectors/single_stage.py", line 37, in init self.bbox_head = build_head(bbox_head) File "/home/sdxx/hgf/anaconda3/envs/mmdet/lib/python3.8/site-packages/mmdet/models/builder.py", line 40, in build_head return HEADS.build(cfg) File "/home/sdxx/hgf/anaconda3/envs/mmdet/lib/python3.8/site-packages/mmcv/utils/registry.py", line 212, in build return self.build_func(*args, **kwargs, registry=self) File "/home/sdxx/hgf/anaconda3/envs/mmdet/lib/python3.8/site-packages/mmcv/cnn/builder.py", line 27, in build_model_from_cfg return build_from_cfg(cfg, registry, default_args) File "/home/sdxx/hgf/anaconda3/envs/mmdet/lib/python3.8/site-packages/mmcv/utils/registry.py", line 44, in build_from_cfg raise KeyError( KeyError: 'YOLOXHead_ is not in the models registry'
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "tools/train.py", line 238, in
Did you add @HEAD.register_module() for YOLOXHead_ ? If not, please read https://mmdetection.readthedocs.io/en/latest/tutorials/customize_models.html
It's strange that running is okay in pycharm which connected to the remote server, but failed in terminal. Running is okay in pycharm verifyed that your modifcation is correct. So is there any special setting in pycharm?
I downloaded the mmdetection in my laptop and remote server respectively，and then I added a ssh interpreter.
and I'm not done anything special in pycharm and all the modfication i've done in pycharm can be seen in the remote server(inlcuding new a python file, modify the code and so on)
no
Sent from my iPhone
------------------ Original ------------------ From: cc @.> Date: Mon,Jun 13,2022 10:14 AM To: open-mmlab/mmdetection @.> Cc: GF1447571253 @.>, Author @.> Subject: Re: [open-mmlab/mmdetection] import custom model error (Issue #7983)
hi, did you solve this problem? I met the same problem.
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I designed a network structure name "SpinMLP" and configured it according to the documentation, but he got the same error：KeyError: 'SpinMLP is not in the models registry'
This issue is marked as stale because it has been marked as invalid or awaiting response for 7 days without any further response. It will be closed in 5 days if the stale label is not removed or if there is no further response.
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This issue is closed because it has been stale for 5 days. Please open a new issue if you have similar issues or you have any new updates now.