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A collection of SingularityNET services using third party DNN models.

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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:

Audio:

  • real-time-voice-cloning (User's Guide) - This service uses Real-Time-Voice-Cloning to clone a voice from a 5 seconds audio file to generate arbitrary speech in real-time. [Reference]
  • sound-spleeter (User's Guide) - This service uses Deezer's Spleeter to perform source separation on audio files. [Reference]
     @misc{spleeter2019,
       title={Spleeter: A Fast And State-of-the Art Music Source Separation Tool With Pre-trained Models},
       author={Romain Hennequin and Anis Khlif and Felix Voituret and Manuel Moussallam},
       howpublished={Late-Breaking/Demo ISMIR 2019},
       month={November},
       note={Deezer Research},
       year={2019}
     }
    

Images:

  • cntk-image-recon (User's Guide) - This service uses ResNet152 model, trained to recognize different types of flowers and dog breeds. [Reference]
  • deepfakes-faceswap (User's Guide) - This service uses the Deepfakes Faceswap, trained on two input videos A and B, to perform face swapping on videos. [Reference]
  • deoldify-colorizer (User's Guide) - This service colorizes grayscale images using an AI model. [Reference]
  • yolov3-object-detection (User's Guide) - This service uses YOLOv3 model to detect objects on images. [Reference]
      @article{yolov3,
          title={YOLOv3: An Incremental Improvement},
          author={Redmon, Joseph and Farhadi, Ali},
          journal = {arXiv},
          year={2018}
      }
    
  • places365-scene-recognition (User's Guide) - This service uses various convolutional neural networks trained on Places365 to perform scene recognition. [Reference]
      @article{zhou2017places,
           title={Places: A 10 million Image Database for Scene Recognition},
           author={Zhou, Bolei and Lapedriza, Agata and Khosla, Aditya and Oliva, Aude and Torralba, Antonio},
           journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
           year={2017},
           publisher={IEEE}
      }
    
  • pneumonia-diagnosis (User's Guide) - This service uses VGG19 to classify X-ray chest images. Based on Alishba Imran's work.

Videos:

  • 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]
      @inproceedings{venugopalan15iccv,
          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}
      }
    

Games:

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.

Authors

Licenses

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

Each service is licensed as followed:

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