CompreFace Version 1.0 offers more user-friendly UI benefits, no-code REST APIs, CCTV and Home Assistance integrations, AWS deployment, and more
Exadel a global software engineering, business consultancy and solutions company, today announced the release of CompreFace 1.0, the newest version of its free, open-source facial recognition service. CompreFace is easily integrated into an existing system and requires no prior machine learning experience.
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The full list of updates in CompreFace Version 1.0 include:
- Manage Collection: Manage subjects and images with CompreFace’s user-friendly UI. This feature allows users to initialize the facial collection without any scripts or code. It also helps solve recognition problems by enabling users to check for correct images saved in each subject.
- Postman documentation: This feature reduces the time-consuming task of implementing REST API requests in users’ programming languages by generating code snippets in the preferred language of the user. Users can also test CompreFace REST endpoints in real-time with pre-defined methods.
- AWS Deployment Support: To speed up project development, CompreFace added deployment instructions for AWS and CloudFormation scripts for easier installation and use in Amazon AWS.
- Single docker image: Users now have a single docker image version of CompreFace.
- Integrations: New integrations include facial recognition from CCTV in one place, managed by Home Assistant. CompreFace’s community created integrations that allow facial recognition with CCTV without writing any custom code with the open-source library Double Take. It connects Frigate, a Network Video Recorder (NVR) with real-time local object detection, with CompreFace for facial recognition. unRAID, a file server system, can also be integrated using CompreFace and Double Take templates.
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“With the support of the developer community, Exadel has continued to improved the CompreFace user experience,” said Serhii Pospielov, Head of the AI Practice at Exadel. “As AI practices continue to rise, we are seeing more use cases emerge for facial recognition. This open-source service allows anyone to enter the facial recognition market and access highly reliable services without needing deep coding or machine learning experience.”
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