| import joblib | |
| import numpy as np | |
| import re | |
| import os | |
| NAME_TO_PC = { | |
| "C":0,"C#":1,"Db":1,"D":2,"D#":3,"Eb":3,"E":4,"F":5,"F#":6,"Gb":6, | |
| "G":7,"G#":8,"Ab":8,"A":9,"A#":10,"Bb":10,"B":11 | |
| } | |
| NOTE_TOKEN_RE = re.compile(r"[A-Ga-g](?:#|b)?") | |
| MODEL_PATH = os.path.join(os.path.dirname(__file__), "chord_classifier.pkl") | |
| clf = joblib.load(MODEL_PATH) | |
| def notes_to_vector(notes_str: str): | |
| tokens = NOTE_TOKEN_RE.findall(notes_str) | |
| pcs = [NAME_TO_PC.get(t.upper(), None) for t in tokens] | |
| pcs = [p for p in pcs if p is not None] | |
| vec = np.zeros(12) | |
| for p in pcs: | |
| vec[p] = 1 | |
| return vec | |
| def predict(inputs: str): | |
| vec = notes_to_vector(inputs) | |
| if np.sum(vec) < 2: | |
| return {"label": "Invalid input (need 2+ notes)"} | |
| label = clf.predict([vec])[0] | |
| return {"label": label} | |