PyTrack for dummies

Setup of the environment on M1 processor

Step 1 Install Miniforge (minimal installer for Conda specific to conda-forge) using this Link.

Step 1.1.1 install xcode:

xcode-select –install

Step 1.1.2 install MiniForge by terminal:

Miniforge3-MacOSX-arm64.sh

Select no to conda init

Note

Follow this guide for a more detailed description of the various steps.

Step 2 Install Python 3.9.13 (if you don’t have any other version later than 3.X) from this link by downloading macOS 64-bit universal2 installer.

Step 3 Set a project in PyCharm using the New project button.

Step 4 Install Pytrack, from terminal in PyCharm, using the following command:

conda install pytrack

Perform map-matching process

Step 1 Download the dataset.xlsx file and the notebook file map-matching.ipynb from the official GitHub repository of this library. This Jupyter file permits you to test the map matching, whilst, the dataset.xlsx file lists a set of gps positions.

Step 2 Double click on the Jupyter file directly in PyCharm, and then Run all (double green arrows)

Note

The openpyxl library is required to execute the code. If it is not already installed, it can be installed with the following terminal command:

conda install openpyxl

The results can be inspected directly in the jupyter notebook.

Make a video of the reconstructed path

Step 1 Go to the official GitHub repository of this library, download the code and pick the Jupyter file create_video_path.ipynb located in the examples folder.

Step 2 Open the same project of Perform map-matching process tutorial and paste create_video_path.ipynb in the working directory. Please check to have there the same dataset.xlsx used in the previous tutorial.

Step 3 Go to this link and click on Get started button (upper right corner) and log in. You can use the free credit offered by Google, which usually consists of 200$ each month free of charge for Google Maps API. At the end of the registration please save your key for API Google Maps Platform. In Google Cloud resume, clink on the API menu in the left and check that the Street View Static API has been enabled.

Step 4 Open the create_video_path.ipynb file and insert your key for API Google Maps Platform in line 2 of cell 3.

Step 5 Check if you already have the libraries needed to run this example, but not needed to run pytrack. To this end, check the libraries listed from rows 4 to 19 of cell 1. In the example below, I need to install natsort, tqdm, cv2 (i.e. OpenCV) . I can do that from PyCharm terminal, typing:

conda install natsort
conda install tqdm
pip install opencv-contrib-python

Step 6 Run the code, and you will find the following results: a) in the working directory, in the new created folder SV_panoramas: you will have a folder for each Street View Image, each containing the image and the metadata. In this example you have 346 folders, from 0 to 345; b) the output video, concatenating the images in SV_panoramas, is located in the working directory.