Contents

• Contents

  • EII Video Profiler

    • EII Video Profiler Prerequisites

    • EII Video Profiler Modes

    • EII Video Profiler Configuration

    • Run Video Profiler

    • Run VideoProfiler in Helm Use Case

    • Benchmarking with Multi-instance Config

EII Video Profiler

This tool can be used to determine the complete metrics involved in the entire video pipeline by measuring the time difference between every component of the pipeline and checking for queue blockages at every component, thereby determining the fast or slow components of the whole pipeline. It can also be used to calculate the FPS of any EII modules based on the stream published by that respective module.

EII Video Profiler Prerequisites

1. VideoProfiler expects a set of config, interfaces, and public private keys to be present in ETCD as a prerequisite.

   To achieve this, ensure an entry for VideoProfiler with its relative path from IEdgeInsights([WORK_DIR]/IEdgeInsights/) directory is set in any of the.yml files present in build/usecases([WORK_DIR]/IEdgeInsights/build/usecases) directory. Following is an example:

   AppContexts:
   - tools/VideoProfiler
   

2. With the previous prerequisite done, run the following command:

   python3 builder.py -f usecases/video-streaming-evam.yml
   

EII Video Profiler Modes

By default, the EII Video Profiler supports the FPS and the Monitor modes. The following are details for these modes:

• FPS mode Enabled by setting the’mode’ key in config([WORK_DIR]/IEdgeInsights/tools/VideoProfiler/config.json) to ‘fps’, this mode calculates the frames per second of any EII module by subscribing to that module’s respective stream.

  "mode": "fps"
  

  Note: For running the Video Profiler in the FPS mode, it is recommended to keep PROFILING_MODE set to false in .env([WORK_DIR]/IEdgeInsights/build/.env) for better performance.

• Monitor mode Enabled by setting the ‘mode’ key in config([WORK_DIR]/IEdgeInsights/tools/VideoProfiler/config.json) to ‘monitor’, this mode calculates average and per-frame stats for every frame while identifying if the frame was blocked at any queue of any module across the video pipeline, thereby determining the fastest and slowest components in the pipeline. To be performant in profiling scenarios, VideoProfiler is enabled to work when subscribing only to a single topic in monitor mode.

Note

VideoProfiler tool doesn’t work in monitor mode with Edge Video Analytics Microservice

"mode": "monitor"

The stats to be displayed by the tool in monitor_mode can be set in the monitor_mode_settings key of config.json([WORK_DIR]/IEdgeInsights/tools/VideoProfiler/config.json).

• ‘display_metadata’: It displays the raw meta-data with timestamps associated with every frame.

• ‘per_frame_stats’: It continuously displays the per-frame metrics of every frame.

• ‘avg_stats’: It continuously displays the average metrics of every frame.

Note

• As a prerequisite for running in profiling or monitor mode, the PROFILING_MODE should be set to true in .env([WORK_DIR]/IEdgeInsights/build/.env)

• It is mandatory to have a UDF to run in monitor mode.

EII Video Profiler Configuration

Following are the EII Video Profiler configurations:

1. dev_mode

   Setting this to false enables secure communication with the EII stack. The user must ensure this switch is in sync with DEV_MODE in .env([WORK_DIR]/IEdgeInsights/build/.env) with PROD mode enabled, the path for the certs mentioned in config([WORK_DIR]/IEdgeInsights/tools/VideoProfiler/config.json) can be changed by the user to point to the required certs.

2. total_number_of_frames

   If mode is set to ‘fps’, the average FPS is calculated for the number of frames set by this variable. If mode is set to “monitor”, the average stats are calculated for the number of frames set by this variable. Setting it to (-1) will run the profiler forever unless terminated by signal interrupts(‘Ctrl+C’).total_number_of_frames should never be set as (-1) for ‘fps’ mode.

3. export_to_csv

   Setting this switch to true exports csv files for the results obtained in VideoProfiler. For monitor_mode, runtime stats printed in the csv are based on the following precdence: avg_stats, per_frame_stats, display_metadata.

Run Video Profiler

Following are the steps to run the video profiler:

1. Set the environment variables accordingly in config.json([WORK_DIR]/IEdgeInsights/tools/VideoProfiler/config.json).

2. Set the required output stream or streams and the appropriate stream config in the config.json([WORK_DIR]/IEdgeInsights/tools/VideoProfiler/config.json) file.

3. If VideoProfiler is subscribing to multiple streams, ensure the AppName of VideoProfiler is added to the Clients list of all the publishers.

4. If using Video Profiler in IPC mode, ensure to set the required permissions to socket file created in SOCKET_DIR in build/.env([WORK_DIR]/IEdgeInsights/build/.env).

   sudo chmod -R 777 /opt/intel/eii/sockets
   

   Note:

   • This step is required every time the publisher is restarted in IPC mode.

   • Caution: This step will make the streams insecure. Do not do it on a production machine.

   • Refer the following VideoProfiler interface example to subscribe to EdgeVideoAnalyticsMicroservice results in the FPS mode:

   "/VideoProfiler/interfaces": {
          "Subscribers": [
              {
                  "EndPoint": "/EII/sockets",
                  "Name": "default",
                  "PublisherAppName": "EdgeVideoAnalyticsMicroservice",
                  "Topics": [
                      "edge_video_analytics_results"
                  ],
                  "Type": "zmq_ipc"
              }
          ]
      },
   

5. If you’re using VideoProfiler with the Helm usecase or trying to subscribe to any external publishers outside the EII network, ensure the correct IP of the publisher is specified in the interfaces section of [config] (config.json) and the correct ETCD host and port are specified in the environment for ETCD_ENDPOINT and ETCD_HOST.

   • For example, for the helm use case, since the ETCD_HOST and ETCD_PORT are different, run the following commands with the required HOST IP:

     export ETCD_HOST="<HOST IP>"
     export ETCD_ENDPOINT="<HOST IP>:32379"
     

6. To provision, build, and run the tool along with the EII video-streaming recipe or stack, see provision/README.md.

7. Ensure the containers VideoProfiler is subscribing to are up and running before trying to bring up VideoProfiler.

   • For example, if VideoProfiler is subcribed to EVAM, use these commands to bring up the entire EII stack and then restart VideoProfiler once the publishing containers are up and running:

     docker-compose up -d
     # Restart VideoProfiler after the publisher is up
     # by checking the logs
     docker restart ia_video_profiler
     

8. Run the following command to see the logs:

   docker logs -f ia_video_profiler
   

9. The runtime stats of Video Profiler, if enabled with the export_to_csv switch, can be found at [video_profiler_runtime_stats]. (video_profiler_runtime_stats.csv)

Run VideoProfiler in Helm Use Case

For running VideoProfiler in the helm use case to subscribe to either EVAM service, the etcd endpoint, volume mount for helm certs, and service endpoints are to be updated.

For connecting to the ETCD server running in the helm environment, the endpoint and required volume mounts should be modified in the following manner in the environment and volumes section of docker-compose.yml([WORK_DIR]/IEdgeInsights/tools/VideoProfiler/docker-compose.yml):

ia_video_profiler:
  ...
  environment:
  ...
    ETCD_HOST: ${ETCD_HOST}
    ETCD_CLIENT_PORT: ${ETCD_CLIENT_PORT}
    # Update this variable referring
    # for helm use case
    ETCD_ENDPOINT: <HOST_IP>:32379
    CONFIGMGR_CERT: "/run/secrets/VideoProfiler/VideoProfiler_client_certificate.pem"
    CONFIGMGR_KEY: "/run/secrets/VideoProfiler/VideoProfiler_client_key.pem"
    CONFIGMGR_CACERT: "/run/secrets/rootca/cacert.pem"
  ...
  volumes:
    - "${EII_INSTALL_PATH}/tools_output:/app/out"
    - "${EII_INSTALL_PATH}/sockets:${SOCKET_DIR}"
    - ./helm-eii/eii-deploy/Certificates/rootca:/run/secrets/rootca
    - ./helm-eii/eii-deploy/Certificates/VideoProfiler:/run/secrets/VideoProfiler

For connecting to any service running in the helm usecase, the container IP associated with the specific service should be updated in the Endpoint section in VideoProfiler config([WORK_DIR]/IEdgeInsights/tools/VideoProfiler/config.json).

The IP associated with the service container can be obtained by checking the container pod IP using docker inspect. Assuming we are connecting to the EVAM service, execute the following command:

docker inspect <VIDEOANALYTICS CONTAINER ID> | grep -i "EdgeVideoAnalytics"

The output of the previous command consists of the IP of the Video Analytics container that can be updated in the VideoProfiler config using EtcdUI:

"VIDEOANALYTICS_SERVICE_HOST=10.99.204.80"

The config can be updated with the obtained container IP in the following way:

{
    "interfaces": {
        "Subscribers": [
            {
               ..
                "EndPoint": "10.99.204.80:65114",
              ..
            }
        ]
    }
}

Benchmarking with Multi-instance Config

1. EII supports multi-instance config generation for benchmarking purposes. This is accomplished by running the builder.py([WORK_DIR]/IEdgeInsights/build/builder.py) with specific parameters, refer to the Multi-instance Config Generation section of EII Pre-requisites in the README for more details.

2. For running VideoProfiler for multiple streams, run the builder with the -v flag provided the pre-requisites mentioned previously are done. The following is an example for generating 6 streams config:

   python3 builder.py -f usecases/video-streaming-evam.yml -v 6
   

Note

• In IPC mode, for accelerators: GPU, and USB 3.0 Vision cameras, add user: root in VideoProfiler-docker-compose.yml([WORK_DIR]/IEdgeInsights/docker-compose.yml) as the subscriber needs to run as root if the publisher is running as root.