In this challenge, I attempt to create a Ukulele tuner in JavaScript using p5.js, ml5.js and the pre-trained machine learning model CREPE: A Convolutional REpresentation for Pitch Estimation. Can you make one with a more elegant and creative interface? Code: [ Ссылка ]
🕹️ p5.js Web Editor Sketch: [ Ссылка ]
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References:
📝 ml5.js: [ Ссылка ]
🧠 CREPE: A Convolutional REpresentation for Pitch Estimation: [ Ссылка ]
🎨 Hannah Davis: [ Ссылка ]
📂 How to turn any GitHub repo into a CDN: [ Ссылка ]
🔊 Online Tone Generator: [ Ссылка ]
🔴 Coding Train Live 183: [ Ссылка ]
Related Coding Challenges:
🚂 #41 Clappy Bird: [ Ссылка ]
🚂 #147 Chrome Dinosaur Game: [ Ссылка ]
🚂 #153 Interactive Drawing with SketchRNN: [ Ссылка ]
Timestamps:
00:00 Introduction
01:04 Import the ml5 library
01:34 Pitch detection using ml5
02:24 The CREPE model
05:07 Using the CREPE model in the web editor
07:19 Create a pitch detector with ml5
11:57 The new keyword: constructors vs functions
13:26 Get a frequency value from the microphone
14:48 Make sure the microphone is ready first
15:33 ml5 callbacks are error-first
17:12 Checking the frequency continuously
18:05 Drawing the frequency in the canvas
19:46 Tuning the A string of the ukulele
25:08 Improving the graphical interface
27:06 Tuning the other strings of the ukulele
28:44 Figure out which note is the closest one
31:51 Debugging and fixing the code
34:51 Wrapping up this coding challenge
Editing by Mathieu Blanchette
Animations by Jason Heglund
Music from Epidemic Sound
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This description was auto-generated. If you see a problem, please open an issue: [ Ссылка ]
#machinelearning #pitchdetection #sound #tuner #p5js #ml5js #javascript
