This Deep learning project is all about end to end implementation of Kidney Disease Classification.
It is a complete End to End implementation With MLFLOW,DVC And Deployment.
Clone the repository
https://github.com/krishnaik06/Kidney-Disease-Classification-Deep-Learning-Project
conda create -n cnncls python=3.8 -y
conda activate cnncls
pip install -r requirements.txt
# Finally run the following command
python app.py
Now,
open up you local host and port
#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
- Save the URI: 566373416292.dkr.ecr.us-east-1.amazonaws.com/chicken
#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
setting>actions>runner>new self hosted runner> choose os> then run command one by one
AWS_ACCESS_KEY_ID=
AWS_SECRET_ACCESS_KEY=
AWS_REGION = us-east-1
AWS_ECR_LOGIN_URI = demo>> 566373416292.dkr.ecr.ap-south-1.amazonaws.com
ECR_REPOSITORY_NAME = simple-app