Running Inference

1. Perform a health check on the gRPC endpoint.

   • Install grpcurl from here

     Example commands to run on Ubuntu:

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     $ wget https://github.com/fullstorydev/grpcurl/releases/download/v1.9.1/grpcurl_1.9.1_linux_amd64.deb
     $ sudo dpkg -i grpcurl_1.9.1_linux_amd64.deb
             

   • Download the health checking proto:

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     $ wget https://raw.githubusercontent.com/grpc/grpc/master/src/proto/grpc/health/v1/health.proto
             

   • Run the health check:

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     $ grpcurl --plaintext --proto health.proto localhost:8004 grpc.health.v1.Health/Check
             

   • If the service is ready, you will get a response similar to the following:

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     { "status": "SERVING" }
             

2. Download the Maxine Eye Contact Python client code by cloning the gRPC Client Repository:

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   git clone https://github.com/NVIDIA-Maxine/nim-clients.git
   
   // Go to the 'eye-contact' folder
   
   cd nim-clients/eye-contact/
           

You can use the sample client script in the Maxine Eye Contact GitHub repo to send a gRPC request to the hosted NIM server:

Go to the scripts directory

            

            
cd scripts
        

Run the command to send gRPC request

            

            
python eye-contact.py --target <server_ip:port> --input <input file path> --output <output file path along with file name>
        

To view details of command line arguments run this command

            

            
python eye-contact.py -h
        

You will get a response similar to the following.

            

            
usage: eye-contact.py [-h] [--target TARGET] [--input INPUT] [--output OUTPUT]

Process mp4 video files using gRPC and apply Gaze-redirection.

options:
  -h, --help       show this help message and exit
  --target TARGET  The target gRPC server address.
  --input INPUT    The path to the input video file.
  --output OUTPUT  The path for the output video file.
        

If the command line arguments are not passed, the script will take the following default values:

• target is 127.0.0.1:8004

• input is ../assets/sample_input.mp4

• output will be the current directory with name output.mp4