Pixano vs Prodigy
Pixano
pixano.cea.frProdigy
prodigy.aiSide by side
| Figure | Pixano | Prodigy |
|---|---|---|
| Price from | — | — |
| Free plan | — | — |
| Free trial | — | — |
| Open source | — | — |
| Web | Yes | Yes |
| Windows | Yes | Yes |
| macOS | Yes | Yes |
| Linux | Yes | Yes |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 0 | 2 |
| Spec score · AI Image Annotation Tools | 7.6 (#15) | 8.4 (#6) |
| Deployment | The maker documents installation with pip in a Python virtual environment and official Docker releases. | The standard Python web server and application can be deployed on any cloud provider or entirely on-premise. |
| Founded | 2020 | 2016 |
| Headquarters | Palaiseau, France | Berlin, Germany |
| Installation | The project README describes installation with pip in a Python virtual environment or by running an official Docker image. | Licensed users install through pip using a private download index and license key, or install a downloaded wheel. |
| Intended users | CEA-List describes Pixano as supporting AI developers and applications in areas including manufacturing, security, robotics, and transportation. | Prodigy is designed as a developer tool and assumes basic familiarity with Python and the command line, while its annotation web app can be used without programming experience after setup. |
| Maker | The product pages identify CEA List as Pixano's maker; its About page describes the LIST Institute as one of the three institutes of CEA Tech. | Prodigy is made by ExplosionAI GmbH, whose legal imprint lists its address in Berlin, Germany. |
| Product | Pixano is an open-source tool for exploring and annotating computer vision datasets with AI features. | Prodigy is a downloadable developer tool and Python library for creating training and evaluation data for machine learning models. |
| Storage | Pixano uses the Lance storage format for dataset navigation and storage. | SQLite is the default database, with PostgreSQL, MySQL and custom database implementations also supported. |
| Support | The project README directs users to its Getting Started guide and contributing guide for usage and contribution information. | The product includes documentation and access to a support forum; company licenses also include priority forum and email support. |
Plans
In their own words
Pixano
Pixano is a free, open-source tool for exploring and annotating computer-vision datasets, including collections of text, images, and video. Its annotation tools cover boxes, polygons, pixel masks, keypoints, cuboids, classification, and tracking; video labels can be propagated across time. Smart features include semantic search using models such as CLIP and segmentation using models such as SAM. Dataset formats such as COCO can be imported and exported, and Pixano uses Lance storage for dataset navigation. Its reusable Web Components can be assembled into custom apps. Pixano documents REST and Python APIs, along with Pixano Inference, a Ray Serve-based inference server with a Python client and REST API. Installation options documented by the project are pip in a Python virtual environment or an official Docker image. The supported Python range is 3.10 or later and earlier than 3.14. Pixano is licensed under CeCILL-C and is under active development, so its API may change. Three-dimensional point-cloud support is described as planned.
Prodigy
Prodigy is a downloadable developer tool and Python library for creating training and evaluation data for machine-learning models. Its built-in recipes cover named entity recognition, text classification, computer vision, audio and video annotation, transcription, and model training and evaluation. A customizable web application offers 23 interfaces for work with text, images, audio, video, relations, multiple choice, HTML and conflict resolution. Users can define workflows with Python recipes and create interfaces using HTML, CSS and JavaScript. Prodigy supports spaCy, plugins for Hugging Face models and integrations with major LLM API providers. Data can be stored in SQLite, MySQL or PostgreSQL and exported to JSON. It runs on the user's own machines without connecting to the maker's or third-party servers, including on air-gapped machines. The standard Python web server and app can be deployed in the cloud or on-premise. Personal licensing costs $390, paid once, excluding tax; Company licensing costs $490, paid once per seat in packs of five, excluding tax.