22a's Perceptions Library

Setup

Clone the Repository:

git clone [repository-link]
cd PerceptionsLibrary22a

Setup Virtual Environment: Ensure you have Python 3.8 installed, then create a virtual environment:
```
python3.8 -m venv env
source env/bin/activate
```
Install Dependencies:
```
pip install -r requirements.txt
```
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
```
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".

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.
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.
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.