eyecontact

Generate API Key

Pull and Run the NIM

NVIDIA Maxine Eye Contact NIM uses gRPC APIs for inferencing requests.

A NGC API Key is required to download the appropriate models and resources when starting the NIM. Pass the value of the API Key to the docker run command in the next section as the NGC_API_KEY environment variable as indicated.

If you are not familiar with how to create the NGC_API_KEY environment variable, the simplest way is to export it in your terminal:

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export NGC_API_KEY=<PASTE_API_KEY_HERE>

Run one of the following commands to make the key available at startup:

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# If using bash
echo "export NGC_API_KEY=<value>" >> ~/.bashrc

# If using zsh
echo "export NGC_API_KEY=<value>" >> ~/.zshrc

Other, more secure options include saving the value in a file, so that you can retrieve with cat $NGC_API_KEY_FILE, or using a password manager.

The following command launches a container with the gRPC service.

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docker run -it --rm --name=maxine-eye-contact-nim \
  --runtime=nvidia \
  --gpus all \
  --shm-size=8GB \
  -e NGC_API_KEY=$NGC_API_KEY \
  -e MAXINE_MAX_CONCURRENCY_PER_GPU=1 \
  -e NIM_HTTP_API_PORT=8000 \
  -p 8000:8000 \
  -p 8001:8001 \
  nvcr.io/nim/nvidia/maxine-eye-contact:latest

Please note, the flag --gpus all is used to assign all available GPUs to the docker container. To assign specific GPU to the docker container (in case of multiple GPUs available in your machine) use --gpus '"device=0,1,2..."'

If the command runs successfully, you get a response similar to the following.

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I0903 10:35:41.664874 47 grpc_server.cc:2445] Started GRPCInferenceService at 0.0.0.0:9001
I0903 10:35:41.665204 47 http_server.cc:3555] Started HTTPService at 0.0.0.0:9000
I0903 10:35:41.706437 47 http_server.cc:185] Started Metrics Service at 0.0.0.0:9002
Maxine GRPC Service: Listening to 0.0.0.0:8001

By default Maxine Eye Contact gRPC service is hosted on port 8001. You will have to use this port for inferencing requests.

Test the NIM

We have provided a sample client script file in our GitHub repo. The script could be used to invoke the Docker container using the following instructions.

Download the Maxine Eye Contact Python client code by cloning the NIM Client Repository:

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git clone https://github.com/NVIDIA-Maxine/nim-clients.git
cd nim-clients/eye-contact

Install the dependencies for the Maxine Eye Contact gRPC client:

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sudo apt-get install python3-pip
pip install -r requirements.txt

Go to scripts directory

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cd scripts

Run the command to send gRPC request

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

To view details of command line arguments run this command

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python eye-contact.py -h

You will get a response similar to the following.

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usage: eye-contact.py [-h] [--preview-mode] [--ssl-mode {DISABLED,MTLS,TLS}] [--ssl-key SSL_KEY] [--ssl-cert SSL_CERT] [--ssl-root-cert SSL_ROOT_CERT] [--target TARGET] [--input INPUT] [--output OUTPUT] [--api-key API_KEY] [--function-id FUNCTION_ID]

Process mp4 video files using gRPC and apply eye-contact.

options:
-h, --help                        show this help message and exit
--preview-mode                    Flag to send request to preview NVCF server on https://build.nvidia.com/nvidia/eyecontact/api.
--ssl-mode {DISABLED,MTLS,TLS}    Flag to set SSL mode, default is DISABLED
--ssl-key SSL_KEY                 The path to ssl private key.
--ssl-cert SSL_CERT               The path to ssl certificate chain.
--ssl-root-cert SSL_ROOT_CERT     The path to ssl root certificate.
--target TARGET                   IP:port of gRPC service, when hosted locally. Use grpc.nvcf.nvidia.com:443 when hosted on NVCF.
--input INPUT                     The path to the input video file.
--output OUTPUT                   The path for the output video file.
--api-key API_KEY                 NGC API key required for authentication, utilized when using TRY API ignored otherwise
--function-id FUNCTION_ID         NVCF function ID for the service, utilized when using TRY API ignored otherwise

For more details on getting started with this NIM including configuring using parameters, visit the NVIDIA Maxine Eye Contact NIM Docs.