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age_gender_recognition

README.md

Faces detection, tracking and age-gender recognition (YoloV8face, Nvidia Tracker, Age-Gender model)

NB: The demo uses YOLOV8-Face model which takes up to 30-40 minutes to compile to TensorRT engine. The first launch takes an enormous time.

A pipeline that uses YOLOV8-Face model to detect faces and 5 face landmarks (eyes, nose, mouth). Landmarks are used to calculate the faces orientation and preprocess face images for age/gender model. Age/gender model estimates age and gender for each face and add this information to the object metadata. The pipeline uses Nvidia Tracker to track faces.

Preview:

Tested on platforms:

  • Nvidia Turing, Ampere
  • Nvidia Jetson Orin family

Demonstrated operational modes:

  • real-time processing: RTSP streams (multiple sources at once);
  • capacity processing: directory of files (FPS).
  • image preprocessing for model input;

Demonstrated adapters:

  • RTSP source adapter;
  • video file source adapter;
  • Always-ON RTSP sink adapter;
  • Video/Metadata sink adapter.

Prerequisites

git clone https://github.com/insight-platform/Savant.git
cd Savant
git lfs pull
./utils/check-environment-compatible

Note: Ubuntu 22.04 runtime configuration guide helps to configure the runtime to run Savant pipelines.

Build Engines

The demo uses models that are compiled into TensorRT engines the first time the demo is run. This takes time. Optionally, you can prepare the engines before running the demo by using the command:

# you are expected to be in Savant/ directory

./scripts/run_module.py --build-engines samples/age_gender_recognition/module.yml

Run Demo

# you are expected to be in Savant/ directory

# if x86
docker compose -f samples/age_gender_recognition/docker-compose.x86.yml up

# if Jetson
docker compose -f samples/age_gender_recognition/docker-compose.l4t.yml up

# open 'rtsp://127.0.0.1:554/stream/video' in your player
# or visit 'http://127.0.0.1:888/stream/video/' (LL-HLS)

# Ctrl+C to stop running the compose bundle

Performance Measurement

Download the video file to the data folder. For example:

# you are expected to be in Savant/ directory

mkdir -p data && curl -o data/elon_musk_perf.mp4 \
   https://eu-central-1.linodeobjects.com/savant-data/demo/elon_musk_perf.mp4

Now you are ready to run the performance benchmark with the following command:

./samples/age_gender_recognition/run_perf.sh

Note: Change the value of the DATA_LOCATION variable in the run_perf.sh script if you changed the video.