CVProject-Chest-Disease-Classification

Computer Vision - Chest Disease Classification from CT Scan Images

Workflows

1. Update config/config.yaml
2. Update params.yaml
3. Update the entity - config_entity.py
4. Update the configuration manager in src config - configuration.py
5. Update the components
6. Update the pipeline
7. Update the main.py/app.py
8. Update the dvc.yaml

Git commands

git add .

git commit -m "Updated"

git push origin main

How to run?

conda create -n chest python=3.8 -y

conda activate chest

pip install -r requirements.txt

python app.py

MLFlow Dagshub Connection URI

MLFLOW_TRACKING_URI=https://dagshub.com/sudhanshusinghaiml/MLFlow-with-Dagshub-Experiment.mlflow \
MLFLOW_TRACKING_USERNAME=sudhanshusinghaiml \
MLFLOW_TRACKING_PASSWORD=<password> \
python script.py

Run from bash terminal

export MLFLOW_TRACKING_URI=https://dagshub.com/sudhanshusinghaiml/MLFlow-with-Dagshub-Experiment.mlflow

export MLFLOW_TRACKING_USERNAME=sudhanshusinghaiml

export MLFLOW_TRACKING_PASSWORD=<password>

python script.py

DVC commands

dvc init

dvc repro

dvc dag

To track the changes with git, run:

git add dvc.lock

To enable auto staging, run:

dvc config core.autostage true

Use dvc push to send your updates to remote storage.