Written by George Soloupis ML GDE

This is part 1 of a tutorial on how to classify sound that is recorded with a phone’s microphone in 500 and more classes using the extraordinary YAMNet Machine Learning model.

The tutorial is divided into two parts and feel free to follow along or skip to the part that is most interesting or relevant for you:

  • Part 1: Architecture of ML model, conversion to TensorFlow Lite (TFLite), benchmarking of the model
  • Part 2: Android implementation

Architecture of ML model

YAMNet is a pretrained deep net that predicts 521 audio event classes based on the AudioSet-YouTube corpus, and employing the Mobilenet_v1 depthwise-separable convolution architecture. …


Written by George Soloupis ML GDE

This is part 2 of a tutorial on how to classify sound that is recorded with a phone’s microphone in 500 and more classes using the extraordinary YAMNet Machine Learning model. (Part 1)

Now that we have explained the architecture of the model and after benchmarking it we have a tflite file that can be downloaded from TensorFlow Hub and used inside a mobile phone. This model file has no metadata so application uses interpreter for inference.

The procedure is as follows:

  1. Mobile’s microphone records the sound that is converted into an array of floats. …

Written by George Soloupis

This is part 3 of an end-to-end TensorFlow Lite tutorial written with team effort, on how to combine multiple ML models to create artistic effects by segmenting an image and then stylizing the image background with neural style transfer. (Part 1 | Part 2 | Part 3)

Now that we have the models from the previous post, we are ready to implement the models in an Android app. We will go over the scenario of how to combine multiple ML models to create artistic effects by segmenting an image and then stylize the image background with neural style transfer. …


Written by George Soloupis

Τhe objectives with this tutorial are to:

  • Load an image file inside android, resize it and do inference with a .tflite model.
  • Use different libraries to load and resize images inside colab notebook, do inference with the same .tflite file.
  • Compare results and find the optimum method.

For part 1 of this tutorial we will use a square image file of a plant and a .tflite model. For rectangle images view part 2.

Exploring first the android side of our research we will find straightforward methods of loading and resizing bitmaps. …


Written by George Soloupis and reviewed by Khanh LeViet, Sayak Paul and Luis Gustavo Martins.

Τhe objectives with this tutorial are to:

  • Understand what is pitch attribute and historical info how machines used to detect it in songs
  • Visualize songs data and the result after model execution
  • Provide information about the techniques that are used to collect sound with phone’s microphone
  • Deploy ML model inside android application
  • Transform song’s data and make inference with SPICE model
  • Render results on android phone’s screen

Pitch is a perceptual property of sounds that allows their ordering on a frequency-related scale, or more commonly, pitch is the quality that makes it possible to judge sounds as “higher” and “lower” in the sense associated with musical melodies. Pitch is a major auditory attribute of musical tones, along with duration, loudness, and timbre, is quantified by frequency and measured in Hertz (Hz), where one Hz corresponds to one cycle per second. …


Written by George Soloupis and reviewed by Khanh LeViet and Sayak Paul

Here are the objectives with this tutorial:

  • Provide information about the techniques that are used to extract style from reference images (paintings for example)
  • How to deploy ML models inside android application
  • Blend the extracted style from the ML model with the video images

Neural Style Transfer

Artistic style transfer is an optimization technique used to take two images: a content image and a style reference image (such as an artwork by a famous painter) and blend them together so the output image looks like the content image, but “painted” in the style of the style reference image. This is a technique outlined in Leon A. …

About

George Soloupis

I'am a pharmacist turned android developer engineer. Right now I am a member of Google's Tensorflow Lite Machine Learning on Mobile OS Working Group

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