I've successfully tested pyslam with Anaconda (version 2019.10, build py37_0) and Miniconda (SHA256 hash 957d2f0f0701c3d1335e3b39f235d197837ad69a944fa6f5d8ad2c686b69df3b) under Linux.
Please, follow the instructions below. I assume you already installed Anaconda or Miniconda, and correctly set your conda python environment.
In order to run main_vo.py with conda, get in the root of this repository and run the following command:
$ . pyenv-conda-create.sh
N.B.: do not forget the dot! (without '/' !)
This will create a custom pyslam conda environment and will also activate the created pyslam environment. Now, from the same terminal, you can run:
$ python3 -O main_vo.py
If you want to use a new terminal, you need to activate the pyslam environment as explained in this section.
In order to run main_slam.py with conda, get in the root of this repository and run the following command:
$ . install_all_conda.sh
N.B.: do not forget the dot! (without '/' !)
This will compile the required thirdparty packages and will also activate the created pyslam environment. Now, from the same terminal, you can run:
$ python3 -O main_slam.py
If you want to use a new terminal, you need to activate the pyslam environment as explained in this section.
You already see this above. In order to create a custom pyslam conda environment, get in the root of this repository and run the following command:
$ . pyenv-conda-create.sh
Run the following command (N.B., do not forget the dot!):
$ . pyenv-conda-activate.sh
or
$ conda activate pyslam
Now, you can launch pySLAM scripts.
To deactivate the pyslam environment, run
$ conda deactivate
To delete the pyslam environment, run
$ . pyenv-conda-delete.sh
Below, you can find some useful details. The scripts mentioned above make the work for you.
You can generate a requirements.txt file by running:
$ conda list -e > requirements-conda.txt
You can create and environment from such a file by runnning:
$ conda create --name <env> --file requirements-conda.txt
N.B.: the file requirements.txt generated by conda cannot be used with pip3 (and viceversa)!
Another approach is to use .yml files. In order to create a file requirements-conda.yml run:
$ conda env export > requirements-conda.yml
or
$ conda env export --no-builds > requirements-conda-nobuilds.yml
for generating a requirements file without build numbers.
You can create an environment from it by running:
$ conda env create -f requirements.yml
To delete an environment, in your terminal window or an Anaconda Prompt, run:
$ conda remove --name myenv --all
this command will also return you some conda infos.
You may instead use the simpler command:
$ conda env remove --name myenv
To verify that the environment was removed, in your terminal window or an Anaconda Prompt, run:
$ conda info --envs
The environments list that displays should not show the removed environment.
In order to create a new conda environment opencvenv, activate it and install OpenCV in it, run the following commands:
$ conda create -yn opencvenv python=3.6.9
$ conda activate opencvenv
$ conda install -c menpo opencv3
This should install OpenCV 3.4.1 and everything you need to run SIFT and SURF.
In order to install pytorch and torchvision:
$ conda install pytorch torchvision cudatoolkit=10.1 -c pytorch
or (if you do not have an NVIDIA GPU)
$ conda install -c pytorch torchvision
To deactivate the opencvenv environment, use
$ conda deactivate
This command will bring you back to your default conda environment.
To re-activate the conda opencvenv environment, use
$ conda activate opencvenv