local_venv.md

Local Simulation with Python venv

Python venv

Check FedYOLO/config.py to see the default configurations

1. Make a custom environment: python -m venv ultravenv
2. Activate the custom environment: source ultravenv/bin/activate
3. Clone the repository
4. cd into the repository: cd UltraFlwr
5. pip install the requirements: pip install -e .

Prepare Datasets

6. cd into the datasets folder: cd datasets
7. Make a directory for a specific dataset: mkdir pills
8. cd into the dataset folder: cd pills
9. Get data-set from Roboflow
10. Create a directory for the client specific datasets: mkdir partitions
11. Create the partitions
    • Go to the base of the clone: cd ../../
    • Create the splits: python FedYOLO/data_partitioner/fed_split.py
      • To choose the dataset, change the DATASET_NAME parameter in the FedYOLO/config.py file

To Build Custom Dataset

Follow the style of roboflow downloads as mentioned in above steps.

Training

12. For one-off: ./scripts/run.sh
    • For multiple Runs, reference: bash scripts/federated_train_and_test/benchmark.sh
    • For normal YOLO training on entire server dataset and client data partitions: bash scripts/central_train_and_test/run_local_train_and_test.sh