turicreate README

The project's README from github.com/apple/turicreate. As one markdown file: README.md.

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Turi Create

Turi Create

Turi Create simplifies the development of custom machine learning models. You don't have to be a machine learning expert to add recommendations, object detection, image classification, image similarity or activity classification to your app.

With Turi Create, you can accomplish many common ML tasks:

ML Task Description
Recommender Personalize choices for users
Image Classification Label images
Drawing Classification Recognize Pencil/Touch Drawings and Gestures
Sound Classification Classify sounds
Object Detection Recognize objects within images
One Shot Object Detection Recognize 2D objects within images using a single example
Style Transfer Stylize images
Activity Classification Detect an activity using sensors
Image Similarity Find similar images
Classifiers Predict a label
Regression Predict numeric values
Clustering Group similar datapoints together
Text Classifier Analyze sentiment of messages

Example: Image classifier with a few lines of code

If you want your app to recognize specific objects in images, you can build your own model with just a few lines of code:

import turicreate as tc

# Load data 
data = tc.SFrame('photoLabel.sframe')

# Create a model
model = tc.image_classifier.create(data, target='photoLabel')

# Make predictions
predictions = model.predict(data)

# Export to Core ML
model.export_coreml('MyClassifier.mlmodel')

It's easy to use the resulting model in an iOS application:

Turi Create

Supported Platforms

Turi Create supports:

System Requirements

Turi Create requires:

Installation

For detailed instructions for different varieties of Linux see LINUX_INSTALL.md. For common installation issues see INSTALL_ISSUES.md.

We recommend using virtualenv to use, install, or build Turi Create. 

pip install virtualenv

The method for installing Turi Create follows the standard python package installation steps. To create and activate a Python virtual environment called venv follow these steps:

# Create a Python virtual environment
cd ~
virtualenv venv

# Activate your virtual environment
source ~/venv/bin/activate

Alternatively, if you are using Anaconda, you may use its virtual environment:

conda create -n virtual_environment_name anaconda
conda activate virtual_environment_name

To install Turi Create within your virtual environment:

(venv) pip install -U turicreate

Documentation

The package User Guide and API Docs contain more details on how to use Turi Create.

GPU Support

Turi Create does not require a GPU, but certain models can be accelerated 9-13x by utilizing a GPU.

Linux macOS 10.13+ macOS 10.14+ discrete GPUs, macOS 10.15+ integrated GPUs
Activity Classification Image Classification Activity Classification
Drawing Classification Image Similarity Object Detection
Image Classification Sound Classification One Shot Object Detection
Image Similarity Style Transfer
Object Detection
One Shot Object Detection
Sound Classification
Style Transfer

macOS GPU support is automatic. For Linux GPU support, see LinuxGPU.md.

Building From Source

If you want to build Turi Create from source, see BUILD.md.

Contributing

Prior to contributing, please review CONTRIBUTING.md and do not provide any contributions unless you agree with the terms and conditions set forth in CONTRIBUTING.md.

We want the Turi Create community to be as welcoming and inclusive as possible, and have adopted a Code of Conduct that we expect all community members, including contributors, to read and observe.

turicreate (apple/turicreate)

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11.2K ·GitHub
Turicreate
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What is this?Turi Create is a Python library from Apple that lets you build custom machine learning models for tasks like recommendations, object detection, image classification, image similarity, and activity classification without being an ML expert.
Is it a Python library or a standalone app?It is a Python package (with a C++ core) that you import into your own scripts; you train a model with a few lines of code and then export it.
How do I install and start using it?Create a Python virtual environment (venv or Anaconda), activate it, then install Turi Create inside it as a standard pip package.
What Python version and hardware do I need?It requires Python 2.7 or 3.5-3.8 on x86_64 architecture, with at least 4 GB of RAM; a GPU is optional but speeds up some models 9-13x.
Is this project still maintained?No — the repository is archived, so it no longer receives updates or active support despite its once-wide feature set.
Which operating systems can I run it on?It runs on macOS 10.12+, Linux (glibc 2.10+), and Windows 10 via WSL.
Can I use a trained model in my iOS app?Yes — models export directly to Core ML format for use in iOS, macOS, watchOS, and tvOS apps.
What kinds of data can it handle?Turi Create is flexible and supports text, images, audio, video, and sensor data for training.
Does it scale to large datasets?It's designed to work with large datasets on a single machine efficiently, aiming to be fast and scalable without needing a cluster.
What ML tasks does it cover out of the box?It includes recommenders, image/drawing/sound/activity classification, object detection (including one-shot), style transfer, image similarity, general classifiers, regression, clustering, and text classification.
What are similar projects?albumentations, AFNetworking, opencv_contrib, firebase-ios-sdk, Detectron, X-AnyLabeling, opencv, fiftyone
Which topics is it in?recommendation-system, watchos, tvos, image-classification, object-detection, apple, image-processing, bsd, deprecated, computer-vision, sdk, c++
Creator
apple
Size
313.2 MB
Stars
11.2K
Updated
CommitNov 29Release6.4.1Sep 30
Age
8y
Commits · 90 Days