Skip to content

Latest commit

 

History

History
148 lines (78 loc) · 2.14 KB

README.md

File metadata and controls

148 lines (78 loc) · 2.14 KB

Emergency Detection using Yolov8

Workflows

  1. constants
  2. entity
  3. components
  4. pipelines
  5. app.py

How to run?

STEPS:

Clone the repository

https://github.com/vasalosi/end-to-end-yolov8-detection

STEP 01- Create a conda environment after opening the repository

conda create -n emergency python=3.8 -y
conda activate emergency

STEP 02- install the requirements

pip install -r requirements.txt
# Finally run the following command
python app.py

Now,

open up you local host and port

AWS-CICD-Deployment-with-Github-Actions

1. Login to AWS console.

2. Create IAM user for deployment

#with specific access

1. EC2 access : It is virtual machine

2. ECR: Elastic Container registry to save your docker image in aws


#Description: About the deployment

1. Build docker image of the source code

2. Push your docker image to ECR

3. Launch Your EC2 

4. Pull Your image from ECR in EC2

5. Lauch your docker image in EC2

#Policy:

1. AmazonEC2ContainerRegistryFullAccess

2. AmazonEC2FullAccess

3. Create ECR repo to store/save docker image

- Save the URI: 566373416292.dkr.ecr.ap-south-1.amazonaws.com/waste

4. Create EC2 machine (Ubuntu)

5. Open EC2 and Install docker in EC2 Machine:

#optinal

sudo apt-get update -y

sudo apt-get upgrade

#required

curl -fsSL https://get.docker.com -o get-docker.sh

sudo sh get-docker.sh

sudo usermod -aG docker ubuntu

newgrp docker

6. Configure EC2 as self-hosted runner:

setting>actions>runner>new self hosted runner> choose os> then run command one by one

7. Setup github secrets:

AWS_ACCESS_KEY_ID=

AWS_SECRET_ACCESS_KEY=

AWS_REGION = 

AWS_ECR_LOGIN_URI =

ECR_REPOSITORY_NAME = 

AZURE-CICD-Deployment-with-Github-Actions

Save pass:

Run from terminal:

docker build -t

docker login

docker push

Deployment Steps:

  1. Build the Docker image of the Source Code
  2. Push the Docker image to Container Registry
  3. Launch the Web App Server in Azure
  4. Pull the Docker image from the container registry to Web App server and run