Parking Capacity

[JohnnyD1]

Task Test

We need to find the parking capacity for each parking lot at UB as this upper-bound will be essential later on when computing the number of vacant spots for each lot.

This test verifies that, given an input image of a parking lot and a template-matching image of a parking space, you can call countSpots() to obtain a count of the number of parking spaces in that parking lot.

Steps

1. Checkout ParkingLotCapacity.

2. If you do not yet have OpenCV installed, click the following links to obtain instructions for Windows
   and UNIX-based systems, respectively:
   https://www.learnopencv.com/install-opencv3-on-windows/
   https://docs.opencv.org/master/d2/de6/tutorial_py_setup_in_ubuntu.html.

3. If you want to specify the dataset from which you are obtaining the lot names from, change the input
   to the df = pd.read_csv("lot_data_with_capacity.csv") call in Line 34 to the filepath of your dataset.
   count_sum.py assumes that your dataset has a column named Parking Lots with each row in that
   column being a name of a parking lot. Be sure to modify this call to your dataset if necessary, or you
   can adapt your dataset to adhere to the call.

4. Run count_spots.py. A dataframe of your new dataset will be returned, and your original CSV file's
   Parking Lots column will be updated with the counts for each lot.