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Cannot install object_detection because these package versions have conflicting dependencies #167

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anariki opened this issue Apr 24, 2024 · 3 comments

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@anariki
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anariki commented Apr 24, 2024

Hey!

Please note I'm running on Jetson Nano JP 4.6.4. Ubuntu 18.04
I have an issue on running:

if os.name=='posix':
!sudo apt-get install protobuf-compiler
!cd Tensorflow/models/research && protoc object_detection/protos/*.proto --python_out=. && cp object_detection/packages/tf2/setup.py . && python3.8 -m pip install .

Error:
INFO: This is taking longer than usual. You might need to provide the dependency resolver with stricter constraints to reduce runtime. See https://pip.pypa.io/warnings/backtracking for guidance. If you want to abort this run, press Ctrl + C.

Downloading tf_models_official-2.11.3-py2.py3-none-any.whl.metadata (1.5 kB)
Downloading tf_models_official-2.11.2-py2.py3-none-any.whl.metadata (1.5 kB)
Downloading tf_models_official-2.11.0-py2.py3-none-any.whl.metadata (1.5 kB)
Downloading tf_models_official-2.10.1-py2.py3-none-any.whl.metadata (1.5 kB)
Downloading tf_models_official-2.10.0-py2.py3-none-any.whl.metadata (1.5 kB)
Downloading tf_models_official-2.9.2-py2.py3-none-any.whl.metadata (1.5 kB)
Downloading tf_models_official-2.9.1-py2.py3-none-any.whl.metadata (1.5 kB)
Downloading tf_models_official-2.9.0-py2.py3-none-any.whl.metadata (1.5 kB)
Downloading tf_models_official-2.8.0-py2.py3-none-any.whl.metadata (1.5 kB)
Downloading tf_models_official-2.7.2-py2.py3-none-any.whl.metadata (1.5 kB)
Downloading tf_models_official-2.7.1-py2.py3-none-any.whl.metadata (1.5 kB)
Downloading tf_models_official-2.7.0-py2.py3-none-any.whl.metadata (1.5 kB)
Downloading tf_models_official-2.6.1-py2.py3-none-any.whl.metadata (1.5 kB)
Downloading tf_models_official-2.6.0-py2.py3-none-any.whl.metadata (1.4 kB)
Downloading tf_models_official-2.5.1-py2.py3-none-any.whl.metadata (1.4 kB)
ERROR: Cannot install object_detection because these package versions have conflicting dependencies.

The conflict is caused by:
tf-models-official 2.16.0 depends on tensorflow-text~=2.16.1
tf-models-official 2.15.0 depends on tensorflow-text~=2.15.0
tf-models-official 2.14.2 depends on tensorflow-text~=2.14.0
tf-models-official 2.14.1 depends on tensorflow-text~=2.14.0
tf-models-official 2.14.0 depends on tensorflow-text~=2.14.0
tf-models-official 2.13.2 depends on tensorflow-text~=2.13.0
tf-models-official 2.13.1 depends on tensorflow-text~=2.13.0
tf-models-official 2.13.0 depends on tensorflow-text~=2.13.0
tf-models-official 2.12.1 depends on tensorflow-addons
tf-models-official 2.12.0 depends on tensorflow-addons
tf-models-official 2.11.6 depends on tensorflow-addons
tf-models-official 2.11.5 depends on tensorflow-addons
tf-models-official 2.11.4 depends on tensorflow-addons
tf-models-official 2.11.3 depends on tensorflow-addons
tf-models-official 2.11.2 depends on tensorflow-addons
tf-models-official 2.11.0 depends on opencv-python-headless==4.5.2.52
tf-models-official 2.10.1 depends on tensorflow-addons
tf-models-official 2.10.0 depends on opencv-python-headless==4.5.2.52
tf-models-official 2.9.2 depends on tensorflow-addons
tf-models-official 2.9.1 depends on tensorflow-addons
tf-models-official 2.9.0 depends on tensorflow-addons
tf-models-official 2.8.0 depends on tensorflow-addons
tf-models-official 2.7.2 depends on tensorflow-addons
tf-models-official 2.7.1 depends on tensorflow-addons
tf-models-official 2.7.0 depends on tensorflow-addons
tf-models-official 2.6.1 depends on tensorflow-addons
tf-models-official 2.6.0 depends on tensorflow-addons
tf-models-official 2.5.1 depends on tensorflow-addons

To fix this you could try to:

  1. loosen the range of package versions you've specified
  2. remove package versions to allow pip attempt to solve the dependency conflict

ERROR: ResolutionImpossible: for help visit https://pip.pypa.io/en/latest/topics/dependency-resolution/#dealing-with-dependency-conflicts
(

@davemaster
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Same thing in my case, but works in an ancient environment with Tensorflow 2.10, with Tensorflow 2.13, NOT with 2.14 or greater... The bad thing, if you're using Windows, can't downgrade Tensorflow, only in Linux; again, Linux rules

@NagbhushanPai
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Same thing in my case, but works in an ancient environment with Tensorflow 2.10, with Tensorflow 2.13, NOT with 2.14 or greater... The bad thing, if you're using Windows, can't downgrade Tensorflow, only in Linux; again, Linux rules

So there's any chance we can move forward or we have to use linux and repeat the entire procedure again?

@davemaster
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do it again

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