ExampleΒΆ
Header (YAML):
>>> import audformat.testing
>>> db = audformat.testing.create_db()
>>> db
name: unittest
description: A database for unit testing.
source: internal
usage: unrestricted
languages: [deu, eng]
author: J. Wagner, H. Wierstorf
organization: audEERING GmbH
license: CC0-1.0
attachments:
file: {path: extra/file.txt}
folder: {path: extra/folder}
media:
microphone: {type: other, format: wav, channels: 1, bit_depth: 16, sampling_rate: 16000}
webcam:
type: other
format: avi
video_fps: 25
video_resolution: [800, 600]
video_channels: 3
video_depth: 8
raters:
gold: {description: Gold standard by taking the average ratings., type: human}
machine: {description: Predictions made by the machine., type: machine, classifier: LibSVM,
features: ComParE_2016}
schemes:
bool: {dtype: bool}
date: {dtype: date}
float: {dtype: float, minimum: -1.0, maximum: 1.0}
int: {dtype: int, minimum: 0, maximum: 100}
label:
dtype: str
labels: [label1, label2, label3]
label_map_int:
dtype: int
labels: {1: a, 2: b, 3: c}
label_map_misc: {dtype: str, labels: misc}
label_map_str:
dtype: str
labels:
label1: {prop1: 1, prop2: a}
label2: {prop1: 2, prop2: b}
label3: {prop1: 3, prop2: c}
string: {dtype: str}
time: {dtype: time}
splits:
dev: {type: dev}
test: {type: test}
train: {type: train}
tables:
files:
type: filewise
split_id: train
media_id: microphone
columns:
bool: {scheme_id: bool, rater_id: gold}
date: {scheme_id: date, rater_id: gold}
float: {scheme_id: float, rater_id: gold}
int: {scheme_id: int, rater_id: gold}
label: {scheme_id: label, rater_id: gold}
label_map_int: {scheme_id: label_map_int, rater_id: gold}
label_map_misc: {scheme_id: label_map_misc, rater_id: gold}
label_map_str: {scheme_id: label_map_str, rater_id: gold}
string: {scheme_id: string, rater_id: gold}
time: {scheme_id: time, rater_id: gold}
no_scheme: {}
segments:
type: segmented
split_id: dev
media_id: microphone
columns:
bool: {scheme_id: bool, rater_id: gold}
date: {scheme_id: date, rater_id: gold}
float: {scheme_id: float, rater_id: gold}
int: {scheme_id: int, rater_id: gold}
label: {scheme_id: label, rater_id: gold}
label_map_int: {scheme_id: label_map_int, rater_id: gold}
label_map_misc: {scheme_id: label_map_misc, rater_id: gold}
label_map_str: {scheme_id: label_map_str, rater_id: gold}
string: {scheme_id: string, rater_id: gold}
time: {scheme_id: time, rater_id: gold}
no_scheme: {}
misc_tables:
misc:
levels: {labels: str}
columns:
int: {scheme_id: int}
label: {scheme_id: label}
audformat: https://github.com/audeering/audformat
Filewise table as pd.DataFrame:
>>> db["files"].get()
bool date ... time no_scheme
file ...
audio/001.wav False NaT ... 0 days 00:00:00.280000 nOqgBuJRkn
audio/002.wav <NA> NaT ... 0 days 00:00:00.960000 iMKa6qC99q
audio/003.wav False 1970-01-01 00:00:00.640 ... 0 days 00:00:00.520000 MgqdWkARaq
audio/004.wav False 1970-01-01 00:00:00.090 ... 0 days 00:00:00.060000 None
audio/005.wav False NaT ... 0 days 00:00:00.540000 l8x3NmGtNB
... ... ... ... ... ...
audio/096.wav True 1970-01-01 00:00:00.160 ... 0 days 00:00:00.180000 Vgv37YqafU
audio/097.wav <NA> 1970-01-01 00:00:00.780 ... 0 days 00:00:00.210000 Nr3hn17JSB
audio/098.wav True 1970-01-01 00:00:00.750 ... 0 days 00:00:00.620000 FFSFTcMjMu
audio/099.wav False 1970-01-01 00:00:00.470 ... 0 days 00:00:00.920000 V49rd5YUQW
audio/100.wav <NA> 1970-01-01 00:00:00.610 ... 0 days 00:00:00.280000 zeTXeIT7wb
[100 rows x 11 columns]
Segmented table as pd.DataFrame:
>>> db["segments"].get()
bool ... no_scheme
file start end ...
audio/001.wav 0 days 00:00:00.082561829 0 days 00:00:04.832983387 True ... None
0 days 00:00:09.907641513 0 days 00:00:13.087561565 <NA> ... None
0 days 00:00:13.422086186 0 days 00:00:16.376171043 True ... ZYixPedAyB
0 days 00:00:19.276700122 0 days 00:00:25.737048646 True ... None
0 days 00:00:30.918073408 0 days 00:00:35.168424756 <NA> ... s5pS1eh4k7
... ... ... ...
audio/010.wav 0 days 00:00:18.786962756 0 days 00:00:29.510792049 False ... None
0 days 00:00:30.691782517 0 days 00:00:33.635262781 False ... jWjGWGeIYX
0 days 00:00:34.058263452 0 days 00:00:34.149017810 False ... None
0 days 00:00:45.930182929 0 days 00:00:49.444541600 False ... Zz7W7ZlYXJ
0 days 00:00:51.577189767 0 days 00:00:56.646463227 True ... None
[100 rows x 11 columns]
Misc table as pd.DataFrame:
>>> db["misc"].get()
int label
labels
label1 26 label2
label2 0 label3
label3 56 label3