vision health challenge, audio crow classifier challenge for Vision Health
Main project:
Solution.ipynb
Trainin Data is stored in:
./Data/dataset/audio
A cvs explaining the dataset can be found in:
./Data/dataset/esc50
Open solutions notebook run all cells up to Train header:
Prediction:
- Check the rooster_competition.wav files is located in main working project './'
- Change final_model_path to desired .hdf
Prediction should return a batch of 10ms samples check if samples is rooster add samples if rooster crowing.length = Sum(samples)*.01 seconds
Count rooster length:
https://medium.com/analytics-vidhya/understanding-the-mel-spectrogram-fca2afa2ce53 https://towardsdatascience.com/getting-to-know-the-mel-spectrogram-31bca3e2d9d0
Environmental Sound Classification on Microcontrollers using Convolutional Neural Networks https://github.com/jonnor/ESC-CNN-microcontroller/blob/f7a02189e18cc845dd4e912654a2509215475410/microesc/urbansound8k.py#L91 Audio Classification with Machine Learning (EuroPython 2019) https://www.youtube.com/watch?v=uCGROOUO_wY&ab_channel=JonNordby
Deep Learning for Audio Classification (kapre version)(https://www.youtube.com/playlist?list=PLhA3b2k8R3t0SYW_MhWkWS5fWg-BlYqWn)