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DataScienceWorkshop

Identification of the density of incorrectly parked vehicles from satellite images (e.g. on a lawn, garage driveway, etc.) - i.e. image analysis and classification. Objective: assessment of the difficulty of finding a parking space

1. Define and prepare the area you want to analyse

Using GPS coordinates (latitude and longitude) define tuples in src/scraper/get_images.py and run the code. The screenshots from Google Maps and Openstreet Map will then appear in the data/ directory.

2. Align photos

If the image data needs to be aligned, this should be done using the prepared application src/scraper/app.py.

3. Generate masks

The prepared method for calculating metrics uses masks that we generate on the aligned images using an src/preprocessing/parking_extractor.py script.

4.

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Identification of the density of incorrectly parked vehicles from satellite images (e.g. on a lawn, garage driveway, etc.) - i.e. image analysis and classification. Objective: assessment of the difficulty of finding a parking space

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