I thought you guys might find this interesting. I slightly modified an image classifier to take audio, then recorded myself sticking keys and picks into locks for 45 minutes respectively. This was in order to create my dataset. I broke those long clips into 5 second segments, which left me with about 1000 clips for training. After 5 minutes of training and 15 epochs, I achieved a little more than 90% accuracy on my training and validation set, which is good enough for a fun project like this.

What this means is that I can put my microphone next to a lock, then detect in live time whether that lock is being picked or if a key is being inserted. I can then record the time the event happened and save the audio clip that triggered the event.

Here is a video demonstration of the project.

Here is an article I wrote where you can see the code.

For anyone that’s into lock picking, I created my training data on Sargent, Corbin Russwin, and Schlage mortise cylinders. I used both single pin picking and raking. I might play around with bumping in the future, if I come back to the project.