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Third Party Deep Neural Networks Model Services

A collection of services using third party DNN models.

HTML User's Guide Hub

Getting Started

For more details on how to publish and test a service, select it from the list below:


  • cntk-image-recon (User's Guide) - This service uses ResNet152 model, trained to recognize different types of flowers and dog breeds. [Reference]
  • yolov3-object-detection (User's Guide) - This service uses YOLOv3 model to detect objects on images. [Reference]
          title={YOLOv3: An Incremental Improvement},
          author={Redmon, Joseph and Farhadi, Ali},
          journal = {arXiv},
  • meta-service-example (User's Guide) - This service uses two other services. First it calls yolov3-object-detection and gets all detected objects from an image. Then it calls cntk-image-recon for each object and returns its classification.


  • i3d-video-action-recognition (User's Guide) - This service uses I3D model to recognize actions on videos (with 400 or 600 labels). [Reference]
  • s2vt-video-captioning (User's Guide) - This service uses "Sequence to Sequence - Video to Text" to describe video content with natural language text. [Reference]
          title = {Sequence to Sequence -- Video to Text},
          author = {Venugopalan, Subhashini and Rohrbach, Marcus and Donahue, Jeff 
                    and Mooney, Raymond and Darrell, Trevor and Saenko, Kate},
          booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},
          year = {2015}

Contributing and Reporting Issues

Please read our guidelines before submitting an issue. If your issue is a bug, please use the bug template pre-populated here. For feature requests and queries you can use this template.



This project is licensed under the MIT License - see the LICENSE file for details.

Each service is licensed as followed: