def chromas_from_midi(midi):
chromas = []
for i in range(0, len(midi), 16):
chromas.append(chroma_from_slice(midi[i:i + 16]))
return chromas
#%%
#%%
start_probs, transition_matrix = get_hmm_parameters()
markov_model = GaussianHMM(n_components=24,
covariance_type="full",
init_params="stmc")
markov_model.startprob_ = start_probs
markov_model.transmat_ = transition_matrix
markov_model.n_features = 12
markov_model.means_ = Chroma_Templates
markov_model.covars_ = covariance_matrix
path = markov_model.predict(emissions, [len(emissions)])
chords = [index_to_chord(chord) for chord in path]
probable_chords = most_likely_from_midi(notes)
#%%
