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A Gauge reading model based on image classification, giving 3 levels of output-High,medium,low

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GaugeReader

GaugeReader is an image classification model that provides three levels of output - High, Medium, and Low - based on the readings from a specific gauge. The model is trained using Keras and can be run on a PC connected to an Arduino board.

Requirements

To use GaugeReader, you will need the following:

Python 3.6 or later Keras 2.2.5 or later TensorFlow 1.14 or later PySerial 3.4 or later An Arduino board An LED connected to Digital Pin 11 (positive) and ground (negative)

Usage

To use GaugeReader, you need to follow these steps:

Connect your Arduino board to your PC using a USB cable.

Choose the correct COM port for the Arduino using device manager.

Make sure that the keras_model.h5 file and labels are in the open folder or change their path accordingly.

Set up an LED on digital pin 11 of the Arduino board for the positive connection and ground for the negative connection.

Run the code

This will open the camera and start capturing images of the gauge.

Place the gauge in front of the camera and wait for the LED to light up with the corresponding reading level.

Contributing

If you want to contribute to GaugeReader, feel free to submit a pull request. We welcome any contributions that can help improve the accuracy and efficiency of the model.

License

GaugeReader is licensed under the MIT license. You are free to use, modify, and distribute the code as long as you include the original license in your distribution.

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A Gauge reading model based on image classification, giving 3 levels of output-High,medium,low

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