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https://github.com/saritaphd/chicken-disease-classification-deep-learning-project-with-deployment-using-aws
Chicken disease classification project end to end with deployment at AWS
https://github.com/saritaphd/chicken-disease-classification-deep-learning-project-with-deployment-using-aws
aws deeplearning yolov8
Last synced: 3 days ago
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Chicken disease classification project end to end with deployment at AWS
- Host: GitHub
- URL: https://github.com/saritaphd/chicken-disease-classification-deep-learning-project-with-deployment-using-aws
- Owner: SaritaPhD
- License: mit
- Created: 2023-10-14T08:50:04.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2024-11-08T10:52:33.000Z (11 days ago)
- Last Synced: 2024-11-08T11:34:31.701Z (11 days ago)
- Topics: aws, deeplearning, yolov8
- Language: Jupyter Notebook
- Homepage:
- Size: 11 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# Chicken-Disease-Classification--Project
The Chicken Disease Classification Project utilizes deep learning to identify and classify diseases in chickens from images. By employing advanced image processing and deep learning techniques, the project aims to assist poultry farmers in early diagnosis, promoting timely interventions for better flock health. Ultimately, it enhances decision-making and contributes to improved animal welfare and productivity in the poultry industry.
## Workflows
1. Update config.yaml
2. Update secrets.yaml [Optional]
3. Update params.yaml
4. Update the entity
5. Update the configuration manager in src config
6. Update the components
7. Update the pipeline
8. Update the main.py
9. Update the dvc.yaml
# How to run?
### STEPS:
Clone the repository
```bash
[email protected]:SaritaPhD/Chicken-Disease-Classification-Deep-Learning-Project-with-Deployment-using-AWS.git
```
### STEP 01- Create a conda environment after opening the repository
```bash
conda create -n cnncls python=3.8 -y
```
```bash
conda activate cnncls
```
### STEP 02- install the requirements
```bash
pip install -r requirements.txt
```
```bash
# Finally run the following command
python app.py
```
Now,
```bash
open up you local host and port
```
### DVC cmd
1. dvc init
2. dvc repro
3. dvc dag
# 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.us-east-1.amazonaws.com/chicken
## 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 = us-east-1
AWS_ECR_LOGIN_URI = demo>> 566373416292.dkr.ecr.ap-south-1.amazonaws.com
ECR_REPOSITORY_NAME = simple-app
# AZURE-CICD-Deployment-with-Github-Actions
## Save pass:
s3cEZKH5yytiVnJ3h+eI3qhhzf9q1vNwEi6+q+WGdd+ACRCZ7JD6
## Run from terminal:
docker build -t chickenapp.azurecr.io/chicken:latest .
docker login chickenapp.azurecr.io
docker push chickenapp.azurecr.io/chicken:latest
## 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