hub-sdk 0.0.21

Ultralytics HUB Client SDK.

Ultralytics HUB-SDK

Welcome to the Ultralytics HUB-SDK documentation! 📖 This guide will walk you through the installation process and help you get started using the HUB-SDK for your machine learning (ML) projects. The SDK provides tools to interact programmatically with Ultralytics HUB.

🚀 Quickstart: Installing HUB-SDK

Ready to dive into the HUB-SDK? Follow these steps to set it up on your machine.

Prerequisites

Before you begin, ensure your system meets the following requirements:

• Python: The HUB-SDK requires Python 3.8 or later. If you don't have Python installed, download it from the official Python website.
• Git (Optional): If you plan to install the HUB-SDK directly from the GitHub repository or contribute to the project, you'll need Git. Install Git from git-scm.com if necessary.

Installation Methods

You can install the HUB-SDK using either of the following methods:

Install from PyPI

For the latest stable release, install the HUB-SDK from PyPI using pip:

pip install hub-sdk

Install from GitHub

To get the very latest development version, you can clone the repository and install it locally:

git clone https://github.com/ultralytics/hub-sdk.git
cd hub-sdk
pip install -e .

🛠️ Usage

Let's get started using the HUB-SDK to perform Create, Read, Update, and Delete (CRUD) operations for Models, Datasets, and Projects on Ultralytics HUB.

1. Import HUB-SDK

Begin by importing the HUBClient class from the hub_sdk module:

2. Authenticate with Credentials

You need to authenticate your client. Choose one of the following methods:

Using an API Key

You can find or generate your API key in your Ultralytics HUB account settings.

# Authenticate using your API key
credentials = {"api_key": "YOUR_API_KEY"}

Using Email and Password

Alternatively, authenticate using your Ultralytics HUB email and password.

# Authenticate using your email and password
credentials = {"email": "YOUR_EMAIL", "password": "YOUR_PASSWORD"}

3. Initialize the HUBClient

Instantiate the HUBClient with your chosen credentials:

# Initialize the client with your credentials
client = HUBClient(credentials)

Operations

The following code snippets demonstrate how to perform CRUD operations on Projects, Models, and Datasets using the initialized client.

Project Operations

Manage your projects easily:

# Get a specific project by its ID
project = client.project("PROJECT_ID")

# Create a new project (replace "PROJECT_DATA" with actual project details)
# create_project = project.create_project("PROJECT_DATA") # Assuming create_project exists and takes data

# List projects
projects = client.projects()  # Assuming a method to list projects exists

# Update an existing project (replace "UPDATE_DATA" with new data)
# update_project = project.update("UPDATE_DATA") # Assuming update exists and takes data

# Delete the project
# deleted_project = project.delete() # Assuming delete exists

Model Operations

Handle your models efficiently:

# Get a specific model by its ID
model = client.model("MODEL_ID")

# Upload a new model (replace "MODEL_DATA" with actual model details/path)
# create_model = client.upload_model("MODEL_DATA") # Assuming upload_model exists

# List models associated with a project or account
models = client.models()  # Assuming a method to list models exists

# Update model details (replace "UPDATE_DATA" with new data)
# update_model = model.update("UPDATE_DATA") # Assuming update exists

# Delete the model
# deleted_model = model.delete() # Assuming delete exists

Dataset Operations

Dataset management is straightforward:

# Get a specific dataset by its ID
dataset = client.dataset("DATASET_ID")

# Upload a new dataset (replace "DATASET_DATA" with actual dataset details/path)
# create_dataset = client.upload_dataset("DATASET_DATA") # Assuming upload_dataset exists

# List datasets
datasets = client.datasets()  # Assuming a method to list datasets exists

# Update dataset details (replace "UPDATE_DATA" with new information)
# update_dataset = dataset.update("UPDATE_DATA") # Assuming update exists

# Delete the dataset
# deleted_dataset = dataset.delete() # Assuming delete exists

Note: The exact method names (create_project, update, delete, upload_model, upload_dataset, projects, models, datasets) might differ. Please refer to the specific HUB-SDK documentation or source code for the correct API calls.

⭐ Ultralytics HUB

Experience seamless AI development with Ultralytics HUB ⭐, the ultimate platform for building, training, and deploying computer vision models. Visualize your datasets, train Ultralytics YOLO models like YOLO11 🚀, and deploy them to real-world applications without writing any code. Explore our user-friendly Ultralytics App and leverage cutting-edge tools to bring your AI visions to life. Start your journey for Free today!

💡 Contribute

We welcome contributions to our open-source projects! Your support helps us improve and grow. To get involved, please see our Contributing Guide. We also appreciate feedback – let us know your thoughts via our Survey. Thank you 🙏 to all our contributors!

📄 License

Ultralytics offers two licensing options to accommodate different use cases:

• AGPL-3.0 License: This OSI-approved open-source license is ideal for students, researchers, and enthusiasts who wish to share their work and collaborate openly. See the LICENSE file for full details.
• Enterprise License: Designed for commercial use, this license allows for the integration of Ultralytics software and AI models into commercial products and services without the open-source requirements of AGPL-3.0. If your scenario involves commercial deployment, please contact us via Ultralytics Licensing.

🤝 Contact

For bug reports and feature requests related to the HUB-SDK, please use GitHub Issues. For questions, support, and discussions with the Ultralytics team and the wider community, join our Discord!