| import os |
| import csv |
| import pickle |
| import numpy as np |
| import fire |
| from collections import Counter |
|
|
| class Split: |
| def read_tsv(self, fn): |
| r = [] |
| with open(fn) as tsv: |
| reader = csv.reader(tsv, delimiter='\t') |
| for row in reader: |
| r.append(row) |
| return r[1:] |
|
|
| def get_tag_list(self, option): |
| if option == 'top50tags': |
| tag_list = np.load('dataset/jamendo/meta/tag_list_50.npy') |
| else: |
| tag_list = np.load('dataset/jamendo/meta/tag_list.npy') |
| if option == 'genre': |
| tag_list = tag_list[:87] |
| elif option == 'instrument': |
| tag_list = tag_list[87:127] |
| elif option == 'moodtheme': |
| tag_list = tag_list[127:] |
| return list(tag_list) |
|
|
| def get_npy_array(self, path, tag_list, option, type_='train'): |
| if option=='all': |
| tsv_fn = os.path.join(path, 'autotagging-%s.tsv'%type_) |
| else: |
| tsv_fn = os.path.join(path, 'autotagging_%s-%s.tsv'%(option, type_)) |
| rows = self.read_tsv(tsv_fn) |
| dictionary = {} |
| i = 0 |
| for row in rows: |
| temp_dict = {} |
| temp_dict['path'] = row[3] |
| temp_dict['duration'] = (float(row[4]) * 12000 - 512) // 256 |
| if option == 'all': |
| temp_dict['tags'] = np.zeros(183) |
| elif option == 'genre': |
| temp_dict['tags'] = np.zeros(87) |
| elif option == 'instrument': |
| temp_dict['tags'] = np.zeros(40) |
| elif option == 'moodtheme': |
| temp_dict['tags'] = np.zeros(56) |
| elif option == 'top50tags': |
| temp_dict['tags'] = np.zeros(50) |
| tags = row[5:] |
| for tag in tags: |
| try: |
| temp_dict['tags'][tag_list.index(tag)] = 1 |
| except: |
| continue |
| if temp_dict['tags'].sum() > 0 and os.path.exists(os.path.join(self.npy_path, row[3][:-3])+'npy'): |
| dictionary[i] = temp_dict |
| i += 1 |
| dict_fn = os.path.join(path, '%s_%s_dict.pickle'%(option, type_)) |
| with open(dict_fn, 'wb') as pf: |
| pickle.dump(dictionary, pf) |
|
|
| def run_iter(self, split, option='all'): |
| tag_list = self.get_tag_list(option) |
| path = 'dataset/jamendo/splits/split-%d/' % split |
| self.get_npy_array(path, tag_list, option, type_='train') |
| self.get_npy_array(path, tag_list, option, type_='validation') |
| self.get_npy_array(path, tag_list, option, type_='test') |
|
|
| def run(self, path): |
| self.npy_path = path |
| for i in range(5): |
| |
| self.run_iter(i, 'genre') |
| self.run_iter(i, 'instrument') |
| self.run_iter(i, 'moodtheme') |
| |
|
|
| if __name__ == '__main__': |
| s = Split() |
| fire.Fire({'run': s.run}) |
|
|
