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Getting Started

Encord Active is an open-source Python library that enables you to improve computer vision models in an active learning fashion by improving your data quality, label quality, and model quality.

Install Encord Active

Install encord-active in your favorite Python environment with the following commands:

python3.9 -m venv ea-venv
source ea-venv/bin/activate
# within venv
pip install encord-active
tip

encord-active requires python3.9 or above. If you have trouble installing encord-active, you can find more detailed instructions on installing it here.

Encord Active Quickstart

Understand Encord Active in 5 minutes by playing!

The script will download a small example project to your current working directory and open the application straight away. This is the fastest way to explore Encord Active.

# within venv
encord-active quickstart

This must be run in the same virtual environment where you installed your package.

The next section will show you how to download larger and more interesting datasets to explore.

Sandbox Dataset

If you have more time, we have pre-built a few sandbox datasets with data, labels, and model predictions for you to start exploring Encord Active.

To get started quickly with a sandbox dataset, you can run the following command:

# within venv
encord-active download

This will allow you to choose a dataset to download. When the download process is complete, you visualize the results by following the printed instructions.

tip

You can follow the COCO sandbox dataset tutorial to learn the features of Encord Active.

Run Encord Active on Google Colab

If you want to quickly explore Encord Active without installing anything into your local machine, we have the following Google Colab notebooks for you:

  1. Explore Encord Active sandbox dataset
  2. Explore Encord Active through your own Encord projects

Import Your Own Data

To import your own data save your data in a directory and run the command:

# within venv
encord-active init /path/to/data/directory

A project will be created using the data (without labels) in the current working directory (unless used with --target).

To visualise the project run:

cd /path/to/project
encord-active visualise

You can find more details on the init command in the CLI section.

Import an Encord Project

If you are an Encord user, you can directly import your own projects into Encord Active easily.

# within venv
encord-active import project

This will import your encord project to a new directory in your current working directory. If you don't have an Encord project ready, you can either

  1. Initialise a project from a local data directory
  2. Migrating data and labels to Encord before calling this command
  3. Download one of our sandbox datasets
info

If you are new to the Encord platform, you can easily sign up for an Encord account.

To be able to import an Encord project, you will need the path to your private ssh-key associated with Encord (see documentation here).

The command will ask you:

  1. Where is your private ssh key stored?: type the path to your private ssh key
  2. What project would you like to import?: here, you can (fuzzy) search for the project title that you would like to import. Hit enter when your desired project is highlighted.

Next, encord-active will fetch your data and labels before computing all the metrics available in encord-active.

Downloading the data and computing the metrics may take a while. Bare with us, it is worth the wait.

When the process is done, follow the printed instructions to open the app or see more details in the Open Encord Active page.

Running the App

To run the Encord Active app, you need to cd into the directory that was created by one of the previous commands and run the following command:

# within venv
cd /path/to/project
encord-active visualise

Now, your browser should open a new window with Encord Active.

caution

If the script just seems to hang and nothing happens in your browser, try visiting http://localhost:8501.

What's Up Next?

We recommend to take a look at one of the tutorials that demonstrate Encord Active's capabilities and the workflows section to learn about importing your model predictions and improving your model performance. A couple of example references are:

  1. Import your model predictions
  2. Find outliers in your data or your labels
  3. Identify metrics that are important for your model performance

You can also have a look at how to write custom metrics and how to use the command line interface.

Need Support?

If you got any issues with Encord Active you are more than welcome to connect with us on Slack or reach out to us at active@encord.com