Conda Quickstart Guide for Ultralytics
This guide provides a comprehensive introduction to setting up a Conda environment for your Ultralytics projects. Conda is an open-source package and environment management system that offers an excellent alternative to pip for installing packages and dependencies. Its isolated environments make it particularly well-suited for data science and machine learning endeavors. For more details, visit the Ultralytics Conda package on Anaconda and check out the Ultralytics feedstock repository for package updates on GitHub.
What You Will Learn
- Setting up a Conda environment
- Installing Ultralytics via Conda
- Initializing Ultralytics in your environment
- Using Ultralytics Docker images with Conda
- You should have Anaconda or Miniconda installed on your system. If not, download and install it from Anaconda or Miniconda.
Setting up a Conda Environment
First, let's create a new Conda environment. Open your terminal and run the following command:
Activate the new environment:
You can install the Ultralytics package from the conda-forge channel. Execute the following command:
Note on CUDA Environment
If you're working in a CUDA-enabled environment, it's a good practice to install
pytorch-cuda together to resolve any conflicts:
With Ultralytics installed, you can now start using its robust features for object detection, instance segmentation, and more. For example, to predict an image, you can run:
Ultralytics Conda Docker Image
If you prefer using Docker, Ultralytics offers Docker images with a Conda environment included. You can pull these images from DockerHub.
Pull the latest Ultralytics image:
Run the image:
Certainly, you can include the following section in your Conda guide to inform users about speeding up installation using
Speeding Up Installation with Libmamba
If you're looking to speed up the package installation process in Conda, you can opt to use
libmamba, a fast, cross-platform, and dependency-aware package manager that serves as an alternative solver to Conda's default.
How to Enable Libmamba
libmamba as the solver for Conda, you can perform the following steps:
First, install the
conda-libmamba-solverpackage. This can be skipped if your Conda version is 4.11 or above, as
libmambais included by default.
Next, configure Conda to use
libmambaas the solver:
And that's it! Your Conda installation will now use
libmamba as the solver, which should result in a faster package installation process.
Congratulations! You have successfully set up a Conda environment, installed the Ultralytics package, and are now ready to explore its rich functionalities. Feel free to dive deeper into the Ultralytics documentation for more advanced tutorials and examples.
Created 2023-09-07, Updated 2023-09-07
Authors: glenn-jocher (1)