https://github.com/ajithvcoder/multivideo_objectdetection_mlops_project
Multi video offline streaming and Yolov8 object detection with Kafka, torch serve, AWS EC2
https://github.com/ajithvcoder/multivideo_objectdetection_mlops_project
aws-ec2 confluent-kafka flask flask-socketio mongodb onnx streaming torchserve yolov8
Last synced: 3 months ago
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Multi video offline streaming and Yolov8 object detection with Kafka, torch serve, AWS EC2
- Host: GitHub
- URL: https://github.com/ajithvcoder/multivideo_objectdetection_mlops_project
- Owner: ajithvcoder
- License: mit
- Created: 2024-02-04T04:26:01.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-02-25T15:26:45.000Z (about 1 year ago)
- Last Synced: 2025-01-12T19:30:43.557Z (4 months ago)
- Topics: aws-ec2, confluent-kafka, flask, flask-socketio, mongodb, onnx, streaming, torchserve, yolov8
- Language: Jupyter Notebook
- Homepage: https://www.youtube.com/playlist?list=PLaiyLZ9Xs1bzsHfMhjTSJD9Jfj2VwBXZU
- Size: 93 MB
- Stars: 2
- Watchers: 1
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Multivideo_Objectdetection_MLOPS_Project
**Youtube Playlist** : [Link here](https://www.youtube.com/playlist?list=PLaiyLZ9Xs1bzsHfMhjTSJD9Jfj2VwBXZU)
**Description**
I am having a set of videos and kafka producer is taking and passing to kafka server then consumer consumes it. The consumer has torchserve part and then objects are detected by it and then stored in mongo db.
**its offline streaming project not real time streaming.** but can be made as real time streaming with modifications in producer part
### Procedure
docker network create kafka-network
docker compose -f kafka/docker-compose.yml build --no-cache
docker compose -f kafka/docker-compose.yml up
docker compose -f docker-compose.yml build --no-cache
docker compose -f docker-compose.yml up
Inference at http://localhost:5000
Check if torchserve is enabled http://localhost:8081/models
To delete the containers
docker compose -f kafka/docker-compose.yml down
docker compose -f docker-compose.yml down
EC2 docker installation
sudo apt-get update -y
sudo apt-get upgrade
curl -fsSL https://get.docker.com -o get-docker.sh
sudo sh get-docker.sh
sudo usermod -aG docker ubuntu
newgrp docker
## Note & Value added
if you use a better model with good dataset it can predict quality will be increased. I worked on integrating following parts in code as its a MLOPs project.
- Confluent Kafka(base) - docker and python based confluent kafka (i didnt use other features of confluent kafka)
- TorchServe(Onnx)
- Flask
- Flask socketio
- From data ingestion to evaluation stage
- dvc pipeline
- docker-compose
- Mongodb
- AWS EC2
- Kindly change the epochs in params.yaml file to 60 and then replace "trained_model_60epoch.onnx" with "detection.onnx" in Dockerfile for using the model training with dvc repro. I dont have a gpu so i trained in colab and placed "trained_model_60epoch.onnx" file in git already.
- Kafka part can also be improved
- In comming days i will try to create and explain part by part example how kafka producer and consumer commincates, how torchserve serves, etc in detail
## Github CI/CD
- it seems that docker compose with github CI/CD is not possible but you can always create more docker containers with [this type](https://github.com/ajithvcoder/Spaceship_Titanic_MLOps_Project/blob/main/.github/workflows/main.yaml) of CI/CD pipeline feel free to explore it
### References
1. https://github.com/wingedrasengan927/Distributed-Multi-Video-Streaming-and-Processing-with-Kafka/tree/master