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I3D Video Action Recognition

This service uses I3D to perform action recognition on videos.

It is part of our third party DNN Model Services.

Getting Started

Requirements

Development

Clone this repository:

$ git clone https://github.com/singnet/dnn-model-services.git
$ cd dnn-model-services/services/i3d-video-action-recognition

Running the service:

To get the ORGANIZATION_ID and SERVICE_ID you must have already published a service (check this link).

Create the SNET Daemon's config JSON file (snetd.config.json).

{
   "DAEMON_END_POINT": "DAEMON_HOST:DAEMON_PORT",
   "IPFS_END_POINT": "http://ipfs.singularitynet.io:80",
   "BLOCKCHAIN_NETWORK_SELECTED": "BLOCKCHAIN_NETWORK",
   "PASSTHROUGH_ENDPOINT": "http://SERVICE_GRPC_HOST:SERVICE_GRPC_PORT",  
   "ORGANIZATION_ID": "ORGANIZATION_ID",
   "SERVICE_ID": "SERVICE_ID",
   "LOG": {
       "LEVEL": "debug",
       "OUTPUT": {
            "TYPE": "stdout"
           }
   }
}

For example (using the Ropsten testnet):

$ cat snetd.config.json
{
   "DAEMON_END_POINT": "0.0.0.0:7055",
   "IPFS_END_POINT": "http://ipfs.singularitynet.io:80",
   "BLOCKCHAIN_NETWORK_SELECTED": "ropsten",
   "PASSTHROUGH_ENDPOINT": "http://localhost:7003",
   "ORGANIZATION_ID": "snet",
   "SERVICE_ID": "i3d-video-action-recognition",
   "LOG": {
       "LEVEL": "debug",
       "OUTPUT": {
           "TYPE": "stdout"
           }
   }
}

Note that we set DAEMON_HOST = 0.0.0.0 because this service will run inside a Docker container.

Install all dependencies:

$ pip3 install -r requirements.txt

Generate the gRPC codes:

$ sh buildproto.sh

Start the service and SNET Daemon:

$ python3 run_service.py

Calling the service:

Inputs:

  • model: kinetics-i3d model ("400" or "600").
  • url: A video URL.

Local (testing purpose):

$ python3 test_service.py
Endpoint (localhost:7003):
Method (video_action_recon): 
Model: 400
Url: http://crcv.ucf.edu/THUMOS14/UCF101/UCF101/v_MoppingFloor_g25_c01.avi
{'Action': 'mopping floor\t56.66%\ncleaning floor\t31.83%\nsweeping floor\t11.39%\nsanding floor\t0.02%\nshoveling snow\t0.01%\n'}

$ python3 test_service.py 
Endpoint (localhost:7003): <ENTER>
Method (video_action_recon): <ENTER>
Model: 600
Url: http://crcv.ucf.edu/THUMOS14/UCF101/UCF101/v_MoppingFloor_g25_c01.avi
{'Action': 'mopping floor\t54.51%\nsweeping floor\t41.16%\ncurling (sport)\t4.13%\ngolf driving\t0.05%\nplaying ice hockey\t0.03%\n'}

Through SingularityNET (follow this link to learn how to publish a service and open a payment channel to be able to call it):

Assuming that you have an open channel to this service:

$ snet client call snet i3d-video-action-recognition default_group video_action_recon '{"model": "400", "url": "http://crcv.ucf.edu/THUMOS14/UCF101/UCF101/v_CricketShot_g04_c02.avi"}'
...
Read call params from cmdline...

Calling service...

    response:
        value: '{'Action': 'playing cricket\t97.77%\nskateboarding\t0.71%\nrobot dancing\t0.56%\nroller skating\t0.56%\ngolf putting\t0.13%\n'}'

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