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Guardian AI Training Pipeline - Setup Guide
=============================================
🚀 Quick Setup (Recommended)
-----------------------------
1. Run the automated setup script:
python setup.py
2. Configure ClearML:
clearml-init
3. Run the pipeline:
python Guardian_pipeline.py
📋 Manual Setup
---------------
1. Install Python 3.8+ and pip
2. Install dependencies:
pip install -r requirements.txt
3. Configure ClearML:
- Create account at https://app.clear.ml
- Run: clearml-init
- Enter your credentials when prompted
4. Prepare your dataset:
- Upload pose keypoint data to ClearML
- Ensure data format matches expected structure
- Update dataset_name and dataset_project in Guardian_pipeline.py
5. Run the training pipeline:
python Guardian_pipeline.py
🔧 Configuration Options
------------------------
Edit Guardian_pipeline.py to customize:
- Dataset name and project
- Model hyperparameters
- Training epochs and batch size
- HPO search space
🧹 Cleanup
----------
To remove training artifacts:
python cleanup.py
📊 Monitoring
-------------
- View experiments: https://app.clear.ml
- Check pipeline progress in ClearML dashboard
- Monitor GPU usage with nvidia-smi (if using CUDA)
🐛 Troubleshooting
------------------
- Check ClearML connection: clearml-agent list
- Verify dataset upload: Check ClearML web interface
- GPU issues: Ensure CUDA drivers are installed
- Memory errors: Reduce batch size in pipeline
For detailed information, see README.md
pip install clearml
clearml-init
api {
# Shudarshan Singh Kongkham's workspace
web_server: https://app.clear.ml/
api_server: https://api.clear.ml
files_server: https://files.clear.ml
# ClearGuardian
credentials {
"access_key" = "NRB3PGE4Y606OUK6MV6GN52NHR6PE7"
"secret_key" = "n-gt0zAo8mTHnVCMK2Z4oI9Oal2mfl-SomvnIfLByfUhygnsKMaQ-Sh87trGT-dfQ7g"
}
}
pip install --upgrade clearml
pip install optuna
# testing github actions locally
winget install nektos.act
# MongoDB Setup
python mongodb_setup.py
python -m pip install "pymongo[srv]"