The primary goal is to develop a model that can accurately classify chicken fecal samples as either indicative of disease or healthy.
Collect fecal samples from chickens, ensuring a diverse set that includes both healthy samples and samples from chickens affected by various diseases.
- Update config.yaml
- Update secrets.yaml [Optional]
- Update params.yaml
- Update the entity
- Update the configuration manager in src config
- Update the components
- Update the pipeline
- Update the main.py
- Update the dvc.yaml
Clone the repository
https://github.com/NimraAslamkhan/Chicken-Disease-classification.git
conda create -n cnncls python=3.12.1 -y
conda activate cnncls
### STEP 02- install the requirements
```bash
pip install -r requirements.txt
# Finally run the following command
python app.py
Now,
open up you local host and port
- dvc init
- dvc repro
- dvc dag
#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
#optinal
sudo apt-get update -y
sudo apt-get upgrade
#required
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 =
AWS_ECR_LOGIN_URI =
ECR_REPOSITORY_NAME = simple-app
docker build -t chickenapp.azurecr.io/chicken:latest .
docker login chickenapp.azurecr.io docker push chickenapp.azurecr.io/chicken:latest
- Build the Docker image of the Source Code
- Push the Docker image to Container Registry
- Launch the Web App Server in Azure
- Pull the Docker image from the container registry to Web App server and run