Welcome to the world of data annotation and management with Labelbox! In this guide, we will walk you through the process of signing up, installing the SDK, and validating your setup so you can begin harnessing the power of Labelbox effectively.

Table of Contents

• Quick Start
• Contribution Guidelines
• Develop with AI Assistance
• Documentation
• Jupyter Notebooks

Quick Start

Sign Up

If you haven’t already, create a free account at Labelbox.

Generate an API Key

Log into Labelbox and navigate to Account & API Keys to generate an API key.

Install the SDK

To install the SDK, run the following command:

pip install labelbox

If you’d like additional functionality surrounding data processing, you can install it with the following command:

pip install labelbox[data]

Please note that if you prefer to build and install your own version of the SDK, remember that only tagged commits have been thoroughly tested. Building from the head of the develop branch carries some level of risk.

Validate Installation and API Key

After installing the SDK and obtaining your API Key, it’s time to validate them. Use the following Python code snippet:

import labelbox as lb

client = lb.Client(API_KEY)  # API_KEY = API Key generated from labelbox.com
dataset = client.create_dataset(name="Test Dataset")
data_rows = [{"row_data": "My First Data Row", "global_key": "first-data-row"}]
task = dataset.create_data_rows(data_rows)
task.wait_till_done()

This snippet will create a dataset named “Test Dataset” containing “My First Data Row.” You can log into Labelbox to verify your dataset.

Contribution Guidelines

We encourage contributions to enhance the SDK. Please refer to the Contributing Guide for detailed information on how to get involved.

Documentation

The SDK is well-documented to facilitate quick start and effective usage. Explore the following links:

• Labelbox Official Documentation
• Jupyter Notebook Examples
• Python SDK Reference

Jupyter Notebooks

Sample notebooks are provided to help you get started with the SDK. Make sure your notebook uses your source code:

1. Run ipython profile create
2. Run ipython locate to find the config file’s location.
3. Open the ipython_config.py file (usually in ~/.ipython/profile_default) and add this line:
4. c.InteractiveShellApp.exec_lines = [ import sys; sys.path.insert(0, labelbox-python root folder)]
5. Go to your project root directory and run jupyter notebook to start the server.

Troubleshooting

If you encounter issues during setup, here are a few troubleshooting tips:

• Ensure that you have Python installed and it’s the correct version compatible with Labelbox.
• Double-check that your API Key is correctly copied and is still valid.
• Refer to the documentation for the specific error message you are seeing.
• If problems persist, consider looking at opened GitHub issues for similar problems.

For more insights, updates, or to collaborate on AI development projects, stay connected with fxis.ai.

At fxis.ai, we believe that such advancements are crucial for the future of AI, as they enable more comprehensive and effective solutions. Our team is continually exploring new methodologies to push the envelope in artificial intelligence, ensuring that our clients benefit from the latest technological innovations.