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import argparse
import os
import pickle
import matplotlib.pyplot as plt
import numpy as np
def load_sdrs(workspace, task_name, filename, config, gpus, source_type):
stat_path = os.path.join(
workspace,
"statistics",
task_name,
filename,
"config={},gpus={}".format(config, gpus),
"statistics.pkl",
)
stat_dict = pickle.load(open(stat_path, 'rb'))
median_sdrs = [e['median_sdr_dict'][source_type] for e in stat_dict['test']]
return median_sdrs
def plot_statistics(args):
# arguments & parameters
workspace = args.workspace
select = args.select
task_name = "musdb18"
filename = "train"
# paths
fig_path = os.path.join('results', task_name, "sdr_{}.pdf".format(select))
os.makedirs(os.path.dirname(fig_path), exist_ok=True)
linewidth = 1
lines = []
fig, ax = plt.subplots(1, 1, figsize=(8, 6))
if select == '1a':
sdrs = load_sdrs(
workspace,
task_name,
filename,
config='vocals-accompaniment,unet',
gpus=1,
source_type="vocals",
)
(line,) = ax.plot(sdrs, label='UNet,l1_wav', linewidth=linewidth)
lines.append(line)
ylim = 15
elif select == '1b':
sdrs = load_sdrs(
workspace,
task_name,
filename,
config='accompaniment-vocals,unet',
gpus=1,
source_type="accompaniment",
)
(line,) = ax.plot(sdrs, label='UNet,l1_wav', linewidth=linewidth)
lines.append(line)
ylim = 20
if select == '1c':
sdrs = load_sdrs(
workspace,
task_name,
filename,
config='vocals-accompaniment,unet',
gpus=1,
source_type="vocals",
)
(line,) = ax.plot(sdrs, label='UNet,l1_wav', linewidth=linewidth)
lines.append(line)
sdrs = load_sdrs(
workspace,
task_name,
filename,
config='vocals-accompaniment,resunet',
gpus=2,
source_type="vocals",
)
(line,) = ax.plot(sdrs, label='ResUNet_ISMIR2021,l1_wav', linewidth=linewidth)
lines.append(line)
sdrs = load_sdrs(
workspace,
task_name,
filename,
config='vocals-accompaniment,unet_subbandtime',
gpus=1,
source_type="vocals",
)
(line,) = ax.plot(sdrs, label='unet_subband,l1_wav', linewidth=linewidth)
lines.append(line)
sdrs = load_sdrs(
workspace,
task_name,
filename,
config='vocals-accompaniment,resunet_subbandtime',
gpus=1,
source_type="vocals",
)
(line,) = ax.plot(sdrs, label='resunet_subband,l1_wav', linewidth=linewidth)
lines.append(line)
ylim = 15
elif select == '1d':
sdrs = load_sdrs(
workspace,
task_name,
filename,
config='accompaniment-vocals,unet',
gpus=1,
source_type="accompaniment",
)
(line,) = ax.plot(sdrs, label='UNet,l1_wav', linewidth=linewidth)
lines.append(line)
sdrs = load_sdrs(
workspace,
task_name,
filename,
config='accompaniment-vocals,resunet',
gpus=2,
source_type="accompaniment",
)
(line,) = ax.plot(sdrs, label='ResUNet_ISMIR2021,l1_wav', linewidth=linewidth)
lines.append(line)
# sdrs = load_sdrs(
# workspace,
# task_name,
# filename,
# config='accompaniment-vocals,unet_subbandtime',
# gpus=1,
# source_type="accompaniment",
# )
# (line,) = ax.plot(sdrs, label='UNet_subbtandtime,l1_wav', linewidth=linewidth)
# lines.append(line)
sdrs = load_sdrs(
workspace,
task_name,
filename,
config='accompaniment-vocals,resunet_subbandtime',
gpus=1,
source_type="accompaniment",
)
(line,) = ax.plot(
sdrs, label='ResUNet_subbtandtime,l1_wav', linewidth=linewidth
)
lines.append(line)
ylim = 20
else:
raise Exception('Error!')
eval_every_iterations = 10000
total_ticks = 50
ticks_freq = 10
ax.set_ylim(0, ylim)
ax.set_xlim(0, total_ticks)
ax.xaxis.set_ticks(np.arange(0, total_ticks + 1, ticks_freq))
ax.xaxis.set_ticklabels(
np.arange(
0,
total_ticks * eval_every_iterations + 1,
ticks_freq * eval_every_iterations,
)
)
ax.yaxis.set_ticks(np.arange(ylim + 1))
ax.yaxis.set_ticklabels(np.arange(ylim + 1))
ax.grid(color='b', linestyle='solid', linewidth=0.3)
plt.legend(handles=lines, loc=4)
plt.savefig(fig_path)
print('Save figure to {}'.format(fig_path))
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument('--workspace', type=str, required=True)
parser.add_argument('--select', type=str, required=True)
args = parser.parse_args()
plot_statistics(args)
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