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footstep-app's Issues

Automatic Text to Audio (Without a button)

Till now what we have done is when text is displayed we press a button then it converts to speech. In this issue you have to make it automatic. As soon as text is displayed, it should be converted into speech

Implement: (topic name)

Type: (UI XML or Java)

Context: (explain what the issue is that is what and how to implement the above mentioned topic)

Put On screen audio reader

Implement: On Screen Text to Audio Reader

Type: UI XML Java

Context: The text displayed after detecting the object using tensorflow should be read out loud by the phone using an on-screen text-to-speech audio reader.

Create a splash screen

What is to be done -
Create a splash/opening screen which takes 3-4 secs to open the first activity.

Add a button for changing into object detection activity

Implement: a button for going into 'object detection' activity

Type: UI XML & Java

Context: You need to create a button on the main activity screen which takes us into an empty activity named 'ObjectDetection' where we will apply object detection.

Create a computer generated audio which gives certain instructions

What is to be done -
On the first activity/screen ( after the splash screen ) add text and an audio file which gives instruction to the user of how to use the app. The audio can be your own recorded or a computer one which speaks in english and tell user what to do.

Add Vibration functionality

What is to be done -
In the same proximity sensor add the functionality of vibration. The phone Vibrates on detecting object.

Add Audio output

What is to be done -
Audio comes from the app after detecting object - display text and then text to speech or a recorded audio which plays on after detecting the object.

Apply Object Detection

Implement: Object Detection activity using tensorflow

Type: UI XML & Java

Context: In the 'ObjectDetection' activity created during the past issue implementation you need to apply Object Detection using pre trained models of tensorflow/tensorflow lite which returns a text on recognizing the object .

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