This Model uses Images of car’s tyre to predict whether the tyre is Full or Flat or if no tyre is detected.
The Dataset contains 3 classes — :
1. Full Tyre
It contains Images of car Tyres who have proper air pressure and hence they are considered full. Here is an example of how a full tyre looks -:
2. Flat Tyre
These tyres don’t have enough air pressure so they are flat i.e. they need to be filled again and checked or else it may become the very reason of an accident. Here is an example of how a flat tyre looks -:
3. No- Tyre
These images represent the scenario when the image contains something else other than a tyre or it may not contain proper image of tyre. Here is an example of no- tyre class :-
Here is a demonstration of how to build this model using Tensorflow and Keras using Python.
Loading the Dataset
Plotting Accuracy of Model
Plotting Loss of Model
We can see that our Model is performing well which the Predictions are verifying also. Now we will save our Model.
Saving and deepCC
deepCC is a framework which converts the Deep Learning Models into an executable file which can be used in IOT devices like Arduino, MCU’s, etc.
Here is the link for the Notebook — Click Here
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Credit: Tanmay Mishra
Also Read: Driver Drowsiness Detection using CNN