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The objective of Car Detector is to grant a tool able to capture a pic of a car and recognize its model and maker (among the 23 present in this prototype), and consult those already scanned. The application is divided in three sections, or fragment, directly accessibile by the user through a navigation bar at the bottom of the screen.

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English Version at the bottom.

Lo scopo di Car Detector è quello di fornire uno strumento che permetta di fotografare 
un’auto e riconoscerne marca e modello (tra i 23 attualmente presenti nel prototipo), ed 
eventualmente consultare quelli già scannerizzati in precedenza. L’applicazione è 
suddivisa quindi in tre sezioni, o fragment, direttamente accessibili dall’utente tramite una 
barra di navigazione nella parte inferiore dello schermo.

Il modello allenato è di Image Classification sul framework Tensorflow 2.0 e basato su un Convolutional Neural Network.
Il data set utilizzato è stato realizzato da Nicolas Gervais (https://github.com/nicolas-gervais).



The objective of Car Detector is to grant a tool able to capture a pic of a car and recognize its model
and maker (among the 23 present in this prototype), and consult those already scanned. The application is 
divided in three sections, or fragment, directly accessibile by the user through a navigation bar at the bottom of
the screen.

The trained model is Image Classification on the Tensorflow 2.0 framework, based on a CNN.
The dataset is has been realized by Nicolas Gervais (https://github.com/nicolas-gervais).

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The objective of Car Detector is to grant a tool able to capture a pic of a car and recognize its model and maker (among the 23 present in this prototype), and consult those already scanned. The application is divided in three sections, or fragment, directly accessibile by the user through a navigation bar at the bottom of the screen.

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