A distributed system that detects faces in a video and draws Delaunay triangles over it.
- Easy Setup - Seamless installation process through Docker images.
- Highly Scalable - Easily scale the number of worker nodes to match your desired workload with minimal configuration changes.
- Handles Multiple Tasks - Capable of efficiently handling multiple video requests simultaneously.
- Robust Logging - Incorporates comprehensive logging functionalities to track and monitor activities effectively.
- Python
- IDE of your choice
- Docker
- PostgreSQL
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Pull the repo and open the terminal in the project directory
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Change directory to Kafka folder
cd kafka -
Run the docker compose file with the command
docker compose up -d -
Run the file
initialKafkaConfig.pywith the commandpython initialKafkaConfig.py -
Change the directory to workerNode folder using the command
cd ../workerNode -
Change the IP address in the .env file to the IP address of the machine running Kafka.
-
Build a Docker image with the command:
docker build -t node:1.0 . -
Change the machine ID as required in the .env file and build another docker image with the command:
docker build -t node:1.1 . -
Create a container using the command
docker run --name worker1 -d -p 9090:9093 node:1.0anddocker run --name worker2 -d -p 9099:9093 node:1.1Now the message queue (Kafka) and two workers are ready. -
Change to the machineNode folder using the command
cd ../machineNode, and change the IP address in .env to the IP address of the machine running Kafka. -
Run the
server.pyto host the website inlocalhost:5000, upload the video and click send. -
The resulting video will be displayed after a few seconds with complete statistics.
