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Alibaba Image Search vs CompreFace

Alibaba Image Search

alibabacloud.com

CompreFace

github.com

Side by side

FigureAlibaba Image SearchCompreFace
Price from$300/moFree
Free plan—Yes
Free trial——
Open source—Yes
WebYesYes
Windows—Yes
macOS—Yes
Linux—Yes
API—Yes
Self-hosted—Yes
Plans published122
Spec score · Image Recognition Software6.8 (#17)8.9 (#2)

Plans

Alibaba Image Search

  • 100,000 images / 1 QPS$300 a month
  • 2,500,000 images / 5 QPS$800 a month
  • 2,500,000 images / 10 QPSPriced on request
  • 5,000,000 images / 5 QPSPriced on request
  • 5,000,000 images / 10 QPSPriced on request
  • 10,000,000 images / 5 QPSPriced on request
  • 10,000,000 images / 10 QPSPriced on request
  • 20,000,000 images / 5 QPSPriced on request
  • 20,000,000 images / 10 QPSPriced on request
  • 30,000,000 images / 5 QPSPriced on request

Alibaba Image Search pricing →

CompreFace

  • CompreFaceFree
  • FreeFree

CompreFace pricing →

In their own words

Alibaba Image Search

Alibaba Image Search has no write-up on Specifiction yet; its figures are above.

Visit alibabacloud.com

CompreFace

CompreFace is a free, open-source face recognition service that provides capabilities through a REST API. It supports face recognition and verification, plus face, landmark and mask detection, head pose detection, age recognition and gender recognition. The project says setup and use do not require prior machine-learning skills. It is packaged as a Docker Compose configuration and can run as a standalone server or in the cloud; listed deployment options also include hybrid use. Setup instructions cover Windows, macOS and Linux and require Docker with Docker Compose or Docker Desktop. The service supports CPU and GPU models, with an x86 processor supporting AVX among the stated requirements. A UI panel and role management let users manage roles and control access to face recognition services. The project names FaceNet and InsightFace among its underlying libraries and links JavaScript, Python and .NET SDK repositories. CompreFace is self-hosted and released under Apache 2.0. The documented quick start uses a release archive and starts the service with docker-compose up -d; the project also points users to GitHub channels and a community chat.

Visit github.com