2
conda install -c conda-forge opencv
Collecting package metadata (repodata.json): done
Solving environment: failed
Initial quick solve with frozen env failed.  Unfreezing env and trying again.
Solving environment: failed

UnsatisfiableError: The following specifications were found to be incompatible with each other:

Package mkl-service conflicts for:
patsy -> scipy -> mkl-service[version='>=2,<3.0a0']
statsmodels -> patsy[version='>=0.4.0'] -> scipy -> mkl-service[version='>=2,<3.0a0']
scikit-image -> scipy[version='>=0.17,>=0.9'] -> mkl-service[version='>=2,<3.0a0']
scipy -> mkl-service[version='>=2,<3.0a0']
scikit-learn -> scipy -> mkl-service[version='>=2,<3.0a0']
mkl-service
seaborn -> statsmodels[version='>=0.5.0'] -> patsy[version='>=0.4.0'] -> scipy -> mkl-service[version='>=2,<3.0a0']
Package importlib_metadata conflicts for:
importlib_metadata
path.py -> importlib_metadata[version='>=0.5']
anaconda==2019.03=py37_0 -> path.py==11.5.0=py37_0 -> importlib_metadata[version='>=0.5']
Cizzl
  • 324
  • 2
  • 11
karthik
  • 27
  • 1
  • 2

1 Answers1

2

I had the same issue and found this post usefull, specially the comment by merv.

Basically, there seems to be some incompatibilities between the configuration needed for the default packages of anaconda and the one for the opencv package.

In order to solve the problem you need to created a new enviroment for conda. This enviroment will contain the opencv package with the proper configuration without afecting other packages.

conda create --name env_opencv -c conda-forge opencv

This will create the "env" and install opencv in it with the configuration required by the package.

Then activate the enviroment.

conda activate env_opencv

More info about the enviroments on conda can be found here

private_miles
  • 21
  • 1