22a's Perceptions Library

Setup

1. Clone the Repository:

   git clone [repository-link]
   cd PerceptionsLibrary22a

2. Setup Virtual Environment: Ensure you have Python 3.8 installed, then create a virtual environment:

   python3.8 -m venv env
   source env/bin/activate

3. Install Dependencies:

   pip install -r requirements.txt

4. Set PYTHONPATH: To ensure import perc22a works in any script, add the absolute path of the PerceptionsLibrary22a to your PYTHONPATH:

   echo "export PYTHONPATH=\"$(pwd):$PYTHONPATH\"" >> ~/.zshrc # or ~/.bashrc
   source ~/.zshrc # or ~/.bashrc

5. Verify Setup: Confirm the path was correctly added by echoing the $PYTHONPATH:

   echo $PYTHONPATH

   Test the setup:

   python scripts/test_setup.py

   Successful output: "Running 'import perc22a' successful".

Loading Data

1. Download Data: Fetch the data from this Google Drive Link and place the <name>.tar.gz files in the data/raw/ directory. Note: The files are large and can expand to more than 10GB when extracted.

2. Extract Data:

   tar -zxvf data/raw/<name>.tar.gz

   This creates a data/raw/<name> directory containing numerous instance-<n>.npz files, which represent snapshots of sensor data during track testing.

3. Use DataLoader: The DataLoader class, found in data/utils/dataloader.py, provides a convenient method for data access.

   To demonstrate its use:

   python3 scripts/load_data.py

   This displays a cv2 window. Click on the image and press any key to navigate through the data. To exit, either hit <Ctrl-C> in the terminal and press a key in the cv2 window or continue pressing keys until all images are cycled through.