# Lobe

- Category: Models & resources
- Official site: https://www.lobe.ai/
- HTML: https://www.88z.ai/en/tools/lobe
- Markdown: https://www.88z.ai/en/tools/lobe.md

Machine Learning Made Easy: From desktop training to multi-platform deployment

## What is Lobe?

Lobe is a tool designed to simplify machine learning, originally offered as a free desktop application that helped users train models on Mac and PC and ship them to any platform.While the official team has announced that the Lobe desktop app is no longer under active development, its underlying technology and open-source resources remain valuable to the community.

Through the Lobe organization on GitHub, developers can access a Python toolset for working with Lobe models, starter projects for iOS and Web, and tools for creating image-based datasets.These resources provide a complete path for turning machine learning ideas into reality, including a hardware kit in partnership with Adafruit that lowers the barrier for integrating AI into IoT devices.

For developers looking to maintain or integrate existing Lobe projects, the official lobe-python library and various platform-specific bootstrap projects are essential assets.They ensure that models trained with Lobe can still be effectively utilized and integrated into modern development environments, even as the desktop application transitions to a legacy status.

## Key features

- **Easy Model Train**：The original desktop app provided an intuitive interface for training machine learning models, such as image classifiers, without writing code.
- **Multi-Platform D**：Starter projects (Bootstrap) for iOS, Web, and .NET help developers quickly integrate models into various applications.
- **Python Toolset**：The lobe-python library allows developers to load, run, and manage Lobe-trained models within Python environments.
- **Dataset Creation**：image-tools provides utilities for creating and managing image-based datasets for machine learning tasks.
- **Hardware Integra**：The lobe-adafruit-kit, in partnership with Adafruit, offers comprehensive support for deploying ML models to edge hardware devices.
- **REST API Support**：The flask-server project provides a REST API starter template, facilitating the deployment of models as backend services.

## How to use it

1. 1.Visit the Lobe organization page on GitHub to browse available open-source repositories and resources.
2. 2.Choose the appropriate starter project for your target platform, such as iOS-bootstrap or web-bootstrap.
3. 3.Use the lobe-python library to test and run existing Lobe model files in your local Python environment.
4. 4.Utilize image-tools to prepare and organize image datasets for training or testing purposes.
5. 5.Refer to the flask-server example to encapsulate your model as an API service for remote access.
6. 6.For hardware deployment, consult the lobe-adafruit-kit documentation to connect and configure relevant devices.

## Where it fits

- **Education & Demo**：Teachers and students use Lobe resources to learn ML basics and quickly build visual AI demonstration projects.
- **Prototyping**：Startups leverage ready-made Bootstrap projects to rapidly validate product concepts involving image recognition.
- **IoT Integration**：Developers use the Adafruit kit to deploy lightweight ML models to embedded devices for smart sensing capabilities.

## Pricing and free quota

Pricing and any free quota follow the official site.

## Who it is for

- ML Beginners
- Prototype Developers
- IoT Engineers
- Educators

## FAQ

### Is the Lobe desktop app still being updated?

No.The official README states that the Lobe desktop application is no longer under development, but community members can still use its legacy resources and open-source libraries.

### Can I use Lobe models in Python?

Yes.The public lobe-python repository on GitHub is specifically designed for working with Lobe models in Python environments.

### How do I deploy a Lobe model to the web?

You can use the web-bootstrap project as a starting point, which helps you integrate the model into a TypeScript-based web application.

## Tags

Machine Learning · Open Source Tools · Model Deployment · Computer Vision

Features, pricing and availability follow the official site. Except for 88z.ai’s own API pages, this is a third-party product; 88z.ai only provides a directory introduction.