def test_randomness():
rand_dir = os.path.join(absolute_dir_path, "generated", "random")
rand_dir_rep = os.path.join(absolute_dir_path, "generated", "random_rep")
sgr = SoundscapesGenerator(1, fg_folder, bg_folder)
sgr.generate(2,
rand_dir,
min_events=2,
max_events=2,
events_start=('uniform', 0, 1),
sources_time=[("const", 0), ("const", 0)])
sgr_rep = SoundscapesGenerator(1, fg_folder, bg_folder)
sgr_rep.generate(2,
rand_dir_rep,
min_events=2,
max_events=2,
events_start=('uniform', 0, 1),
sources_time=[0, 0])
list_files = [
os.path.join(rand_dir, "00.wav"),
os.path.join(rand_dir, "01.wav")
]
list_files_rep = [
os.path.join(rand_dir_rep, "00.wav"),
os.path.join(rand_dir_rep, "01.wav")
]
for i in range(len(list_files)):
aud, sr = sf.read(list_files[i])
aud_r, sr_r = sf.read(list_files_rep[i])
assert (aud != aud_r).any()
assert sr == sr_r
def generate_multiproc(start_from, number, rand_state):
# We need to give a different random state to each object otherwise we just replicate X times the same data
# except if it is None
sg = SoundscapesGenerator(duration=clip_duration,
fg_folder=fg_folder,
bg_folder=bg_folder,
ref_db=ref_db,
samplerate=sample_rate,
random_state=rand_state,
logger=logger)
sg.generate_by_label_occurence(label_occurences=co_occur_dict,
number=number,
out_folder=full_out_folder,
save_isolated_events=True,
start_from=start_from,
pitch_shift=pitch_shift)
def generate_training(n_soundscapes,
fg_folder,
bg_folder,
param_file,
outfolder,
duration=10.0,
ref_db=-50):
create_folder(outfolder)
with open(param_file) as json_file:
params = json.load(json_file)
sg = SoundscapesGenerator(duration, fg_folder, bg_folder, ref_db=ref_db)
sg.generate_by_label_occurence(params,
n_soundscapes,
outfolder,
min_events=1,
max_events=1,
pitch_shift=('uniform', -3, 3))
def test_random_state():
rand_dir = os.path.join(absolute_dir_path, "generated", "random_state")
rand_dir_rep = os.path.join(absolute_dir_path, "generated",
"random_state_rep")
sgrs = SoundscapesGenerator(10, fg_folder, bg_folder, random_state=2020)
sgrs.generate(2, rand_dir)
sgrs_rep = SoundscapesGenerator(10,
fg_folder,
bg_folder,
random_state=2020)
sgrs_rep.generate(2, rand_dir_rep)
list_files = [
os.path.join(rand_dir, "00.wav"),
os.path.join(rand_dir, "01.wav")
]
list_files_rep = [
os.path.join(rand_dir_rep, "00.wav"),
os.path.join(rand_dir_rep, "01.wav")
]
for i in range(len(list_files)):
aud, sr = sf.read(list_files[i])
aud_r, sr_r = sf.read(list_files_rep[i])
assert (aud == aud_r).all()
assert sr == sr_r
pformat(vars(args))
# General output folder, in args
base_out_folder = args.out_folder
create_folder(base_out_folder)
out_tsv_folder = args.out_tsv_folder
create_folder(out_tsv_folder)
# ################
# Varying onset of a single event
# ###########
# SCAPER SETTINGS
clip_duration = 10.0
sg = SoundscapesGenerator(duration=clip_duration,
fg_folder=args.fg_folder,
bg_folder=args.bg_folder)
n_soundscapes = args.number
source_time_dist = "const"
source_time = 0.0
event_duration_dist = "uniform"
event_duration_min = 0.25
event_duration_max = 10.0
snr_dist = "uniform"
snr_min = 6
snr_max = 30
pitch_dist = "uniform"
pitch_min = -3.0
parser.add_argument('--bg_folder', type=str, default=osp.join(cfg.audio_path_eval, "soundbank", "background_long"))
args = parser.parse_args()
pformat(vars(args))
# General output folder, in args
out_folder = args.out_folder
create_folder(out_folder)
create_folder(osp.dirname(args.out_tsv))
# ################
# Long event as background, short events as foreground
# ###########
duration = 10.0
sg = SoundscapesGenerator(duration=duration,
fg_folder=args.fg_folder,
bg_folder=args.bg_folder,
ref_db=cfg.ref_db,
samplerate=cfg.samplerate)
n_soundscapes = args.number
# Distribution of events
min_events = 1
max_events = 5
evt_time_dist = 'truncnorm'
evt_time_mean = 5.0
evt_time_std = 2.0
evt_time_min = 0.0
evt_time_max = 10.0
source_time_dist = 'const'
import json
import os
import pandas as pd
import soundfile as sf
from desed.generate_synthetic import SoundscapesGenerator, generate_tsv_from_jams, generate_files_from_jams
absolute_dir_path = os.path.abspath(os.path.dirname(__file__))
fg_folder = os.path.join(absolute_dir_path, "material", "soundbank",
"foreground")
bg_folder = os.path.join(absolute_dir_path, "material", "soundbank",
"background")
sg = SoundscapesGenerator(1, fg_folder, bg_folder, random_state=2020)
def test_generate_simple():
out_dir = os.path.join(absolute_dir_path, "generated", "soundgenerator",
"simple")
os.makedirs(out_dir, exist_ok=True)
sg.generate(2, out_dir, txt_file=False)
def test_generate_balance():
out_dir = os.path.join(absolute_dir_path, "generated", "soundgenerator",
"simple")
os.makedirs(out_dir, exist_ok=True)
sg.generate_balance(2,
out_dir,
min_events=1,
max_events=1,
bg_labels=["label"])
# General output folder, in args
out_folder = args.out_folder
create_folder(out_folder)
out_tsv = args.out_tsv
if out_tsv is not None:
create_folder(osp.dirname(args.out_tsv))
# Default parameters
clip_duration = 10.0
ref_db = -55
samplerate = 16000
sg = SoundscapesGenerator(
duration=clip_duration,
fg_folder=args.fg_folder,
bg_folder=args.bg_folder,
ref_db=ref_db,
samplerate=samplerate,
)
# Generate events same way as the training set
out_folder_30 = osp.join(out_folder, "30dB")
create_folder(out_folder_30)
param_json = osp.join("event_occurences", "event_occurences_eval.json")
with open(param_json) as json_file:
co_occur_dict = json.load(json_file)
sg.generate_by_label_occurence(label_occurences=co_occur_dict,
number=args.number,
out_folder=out_folder_30)
# Remove files that have polyphony greater than 3
parser.add_argument('--bg_folder', type=str, default=osp.join(cfg.audio_path_train, "soundbank", "background"))
parser.add_argument('--json_params', type=str, default=osp.join("event_occurences", 'event_occurences_train.json'))
args = parser.parse_args()
pformat(vars(args))
# General output folder, in args
out_folder = args.out_folder
create_folder(out_folder)
create_folder(osp.dirname(args.out_tsv))
# Default parameters
clip_duration = 10.0
sg = SoundscapesGenerator(duration=clip_duration,
fg_folder=args.fg_folder,
bg_folder=args.bg_folder,
ref_db=cfg.ref_db,
samplerate=cfg.samplerate)
# Generate events same way as the training set
out_folder_30 = osp.join(out_folder, "30dB")
create_folder(out_folder_30)
param_json = args.json_params
with open(param_json) as json_file:
co_occur_dict = json.load(json_file)
sg.generate_by_label_occurence(label_occurences=co_occur_dict,
number=args.number,
out_folder=out_folder_30,
save_isolated_events=True)
# Remove files that have polyphony greater than 3
start_from=start_from,
pitch_shift=pitch_shift)
if random_state is None:
random_states = [None for i in range(nproc)]
else:
random_states = [random_state + i for i in range(nproc)]
print(random_states)
with multiprocessing.Pool(nproc) as p:
p.starmap(generate_multiproc,
zip(list_start, numbers, random_states))
# Single process
else:
sg = SoundscapesGenerator(duration=clip_duration,
fg_folder=fg_folder,
bg_folder=bg_folder,
ref_db=ref_db,
samplerate=sample_rate,
random_state=random_state)
sg.generate_by_label_occurence(label_occurences=co_occur_dict,
number=n_soundscapes,
out_folder=full_out_folder,
save_isolated_events=True,
pitch_shift=pitch_shift)
# ##
# Post processing
rm_high_polyphony(full_out_folder, max_polyphony=2)
# concat same labels overlapping
post_process_txt_labels(full_out_folder,
output_folder=full_out_folder,
output_tsv=out_tsv,
