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nanodet-pytorch-cpu's Issues

复现报错!

# 报错error

(nanodet) PS F:\my_projects\NanoDet-PyTorch-CPU\NanoDet-PyTorch-CPU-master> python detect_main.py webcam --config ./config/nanodet-m.yml --model model/nanodet_m.pth --path  0
f:\my_projects\nanodet\nanodet-main\nanodet\model\arch\__init__.py:26: UserWarning: Model architecture name is changed to 'OneStageDetector'. The name 'GFL' is deprecated, please change the model->arch->name in your YAML config file to OneStageDetector.
  warnings.warn(
model size is  1.0x
init weights...
=> loading pretrained model https://download.pytorch.org/models/shufflenetv2_x1-5666bf0f80.pth
Finish initialize NanoDet Head.
[root][12-18 12:45:10]INFO:Press "Esc", "q" or "Q" to exit.
Traceback (most recent call last):
  File "detect_main.py", line 115, in <module>
    main()
  File "detect_main.py", line 107, in main
    meta, res = predictor.inference(frame)
  File "detect_main.py", line 58, in inference
    meta = self.pipeline(meta, self.cfg.data.val.input_size)
TypeError: __call__() missing 1 required positional argument: 'dst_shape'
(nanodet) PS F:\my_projects\NanoDet-PyTorch-CPU\NanoDet-PyTorch-CPU-master>
# 环境: Windows
(nanodet) PS F:\my_projects\NanoDet-PyTorch-CPU\NanoDet-PyTorch-CPU-master> pip list
Package                 Version     Editable project location
----------------------- ----------- -----------------------------------
absl-py                 1.3.0
aiohttp                 3.8.3
aiosignal               1.3.1
antlr4-python3-runtime  4.9.3
async-timeout           4.0.2
attrs                   22.1.0
cachetools              5.2.0
certifi                 2022.9.24
charset-normalizer      2.1.1
colorama                0.4.6
commonmark              0.9.1
contourpy               1.0.6
cycler                  0.11.0
Cython                  0.29.32
fonttools               4.38.0
frozenlist              1.3.3
fsspec                  2022.11.0
google-auth             2.15.0
google-auth-oauthlib    0.4.6
grpcio                  1.51.1
idna                    3.4
importlib-metadata      5.1.0
kiwisolver              1.4.4
lightning-utilities     0.4.2
Markdown                3.4.1
MarkupSafe              2.1.1
matplotlib              3.6.2
multidict               6.0.3
nanodet                 1.0.0a0     f:\my_projects\nanodet\nanodet-main
numpy                   1.23.5
oauthlib                3.2.2
omegaconf               2.3.0
onnx                    1.13.0
onnx-simplifier         0.4.10
opencv-python           4.6.0.66
packaging               22.0
Pillow                  9.3.0
pip                     22.3.1
protobuf                3.20.3
pyaml                   21.10.1
pyasn1                  0.4.8
pyasn1-modules          0.2.8
pycocotools             2.0.6
Pygments                2.13.0
pyparsing               3.0.9
python-dateutil         2.8.2
pytorch-lightning       1.8.5.post0
PyYAML                  6.0
requests                2.28.1
requests-oauthlib       1.3.1
rich                    12.6.0
rsa                     4.9
setuptools              65.5.0
six                     1.16.0
tabulate                0.9.0
tensorboard             2.11.0
tensorboard-data-server 0.6.1
tensorboard-plugin-wit  1.8.1
tensorboardX            2.5
termcolor               2.1.1
torch                   1.13.1
torchmetrics            0.11.0
torchvision             0.14.1
tqdm                    4.64.1
typing_extensions       4.4.0
urllib3                 1.26.13
Werkzeug                2.2.2
wheel                   0.37.1
wincertstore            0.2
yarl                    1.8.2
zipp                    3.11.0

是否可以使用GPU进行inference

博主你好,感谢你简明的教程,我上手测试很快。
测试程序时,我观察到GPU占用开始升高,你的代码是否默认可以开启GPU进行推理呢?

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