import jams import tqdm import glob import numpy as np import mir_eval def quantise(beats): return [int(round(b * 25)) / 25 for b in beats] # simplify annotation to sevenths_inv new_key = [] for tmp in tqdm.tqdm(glob.glob("/work/fast_data_yinghao/jjy_chord/references_v2/*.jams")): file = jams.load(tmp) for idx, data in enumerate(file["annotations"][0]["data"]): # key.add(data.value.split(":")[-1]) if ":" in data.value: new_key.append(data.value.split(":")[-1]) # else: # new_key.append(data.value) new_key = list(set(new_key)) map = {} # partition = [[new_key[0]]] target = ['maj','maj/3','maj/5', 'min' ,'min/b3','min/5', '7' ,'7/3' ,'7/5' ,'7/b7', 'maj7', 'maj7/3','maj7/7', 'min7', 'min7/b3','min7/5' ,'min7/b7' ] for idx, i in tqdm.tqdm(enumerate(new_key)): for j in target: if mir_eval.chord.sevenths_inv(["C:" + i],["C:" + j])==1: map[i] = j break else: map[i] = i # # for j in new_key[idx+1:]: # for j in partition: # if mir_eval.chord.sevenths_inv([i],[j[0]])==1: # j.append(i) # break # else: # partition.append([i]) # key = set() # ['C#:min11', 'C#:5', 'C#:5(b13)', 'C#:(1,b3)/b3', 'C#:min7', 'C#:min(*b3,9)', 'C#:5(b7)', 'C#:maj6', 'C#:maj7(*b5)', 'C#:dim', 'C#:min(*b3,*5)', 'C#:min11/b3', 'C#:min7(4)/4', 'C#:min7/4', # 'C#:7(b9)/3', 'C#:sus4(b7)', 'C#:maj6(4)', 'C#:sus4', 'C#:min7(9)', 'C#/3', 'C#:maj', 'C#:7(b9)', 'C#:7/4', 'C#', 'C#:maj/3', 'C#:min9/b7', 'C#:min(9)', 'C#:maj(*3)', 'C#:1/1', 'C#:13', 'C#:7(#9)', # 'C#:dim/b3', 'C#:sus2(4)', 'C#:maj/b4', 'C#:min(*b3)', 'C#:7/3', 'C#:maj7/3', 'C#:min/b7', 'C#:min7/b7', 'C#:7', 'C#:min(b13)', 'C#:7(b9,#9)', 'C#:(1,b3,b5,6)', 'C#:min9', 'C#:min7/5', 'C#:sus4(b7,9)', # 'C#:min7/b3', 'C#:maj/5', 'C#:min/4', 'C#:dim7', 'C#:min/5', 'C#:hdim7/4', 'C#:min/3', 'C#:maj6/3', 'C#:min(11)', 'C#:hdim7', 'C#:dim7/b3', 'C#:9', 'C#:sus2(b7)', 'C#:aug', 'C#:(b3,b7,11,9)', # 'C#:(1,b3,b5,6)/b3', 'C#:maj6(4)/3', 'C#:7(b2)', 'C#:sus2', 'C#:min', 'C#:(1,b3)'] # count = 0 for tmp in tqdm.tqdm(glob.glob("/work/fast_data_yinghao/jjy_chord/references_v2/*.jams")): file = jams.load(tmp) ref_intervals = np.zeros((len(file["annotations"][0]["data"]),2)) ref_labels = [] # all annotations start at 0s # count += (file["annotations"][0]["data"][0].time==0) annotation = "" for idx, data in enumerate(file["annotations"][0]["data"]): # key.add(data.value.split(":")[-1]) # key.add(data.value) ref_intervals[idx] = [data.time, data.time + data.duration] ref_labels.append(data.value) if ":" in data.value: chord = data.value.split(":")[0] + ":" + map[data.value.split(":")[-1]] annotation +=f"{chord} {quantise(data.time + data.duration)}s," # break # (est_intervals, est_labels) = (ref_intervals, ref_labels) # est_intervals, est_labels = mir_eval.util.adjust_intervals( # est_intervals, est_labels, ref_intervals.min(), # ref_intervals.max(), mir_eval.chord.NO_CHORD, # mir_eval.chord.NO_CHORD) # (intervals, ref_labels, est_labels) = mir_eval.util.merge_labeled_intervals( # ref_intervals, ref_labels, est_intervals, est_labels) # durations = mir_eval.util.intervals_to_durations(intervals) # comparisons = mir_eval.chord.sevenths_inv(ref_labels, est_labels) # score = mir_eval.chord.weighted_accuracy(comparisons, durations)