Update README.md
Browse files
README.md
CHANGED
@@ -16,6 +16,8 @@ tags:
|
|
16 |
We present the BirdSet benchmark that covers a comprehensive range of classification datasets in avian bioacoustics.
|
17 |
We offer a static set of evaluation datasets and a varied collection of training datasets, enabling the application of diverse methodologies.
|
18 |
|
|
|
|
|
19 |
| | train | test | test_5s | size (GB) | #classes |
|
20 |
|--------------------------------|--------:|-----------:|--------:|-----------:|-------------:|
|
21 |
| [PER][1] (Amazon Basin) | 16,802 | 14,798 | 15,120 | 10.5 | 132 |
|
@@ -73,13 +75,13 @@ We offer a static set of evaluation datasets and a varied collection of training
|
|
73 |
|
74 |
#### Metadata
|
75 |
|
76 |
-
| | format
|
77 |
|------------------------|-------------------------------------------------------:|-------------------------:|
|
78 |
-
| audio | Audio(sampling_rate=32_000, mono=True, decode=True) |
|
79 |
-
| filepath | Value("string") |
|
80 |
-
| start_time | Value("float64") |
|
81 |
-
| end_time | Value("float64") |
|
82 |
-
| low_freq | Value("int64") |
|
83 |
| high_freq | Value("int64") | |
|
84 |
| ebird_code | ClassLabel(names=class_list) | |
|
85 |
| ebird_code_multilabel | Sequence(datasets.ClassLabel(names=class_list)) | |
|
@@ -101,7 +103,6 @@ We offer a static set of evaluation datasets and a varied collection of training
|
|
101 |
#### Example Metadata Train
|
102 |
|
103 |
```python
|
104 |
-
EXAMPLE TRAIN
|
105 |
{'audio': {'path': '.ogg',
|
106 |
'array': array([ 0.0008485 , 0.00128899, -0.00317163, ..., 0.00228528,
|
107 |
0.00270796, -0.00120562]),
|
|
|
16 |
We present the BirdSet benchmark that covers a comprehensive range of classification datasets in avian bioacoustics.
|
17 |
We offer a static set of evaluation datasets and a varied collection of training datasets, enabling the application of diverse methodologies.
|
18 |
|
19 |
+
We have a complementary code base: https://github.com/DBD-research-group/BirdSet
|
20 |
+
|
21 |
| | train | test | test_5s | size (GB) | #classes |
|
22 |
|--------------------------------|--------:|-----------:|--------:|-----------:|-------------:|
|
23 |
| [PER][1] (Amazon Basin) | 16,802 | 14,798 | 15,120 | 10.5 | 132 |
|
|
|
75 |
|
76 |
#### Metadata
|
77 |
|
78 |
+
| | format | description |
|
79 |
|------------------------|-------------------------------------------------------:|-------------------------:|
|
80 |
+
| audio | Audio(sampling_rate=32_000, mono=True, decode=True) | audio object from hf |
|
81 |
+
| filepath | Value("string") | path where the recording is saved |
|
82 |
+
| start_time | Value("float64") | only testdata:start time of a vocalization if the ground truth label is given |
|
83 |
+
| end_time | Value("float64") | only testdata: end time of a vocalzation if the ground truth label is given |
|
84 |
+
| low_freq | Value("int64") | |
|
85 |
| high_freq | Value("int64") | |
|
86 |
| ebird_code | ClassLabel(names=class_list) | |
|
87 |
| ebird_code_multilabel | Sequence(datasets.ClassLabel(names=class_list)) | |
|
|
|
103 |
#### Example Metadata Train
|
104 |
|
105 |
```python
|
|
|
106 |
{'audio': {'path': '.ogg',
|
107 |
'array': array([ 0.0008485 , 0.00128899, -0.00317163, ..., 0.00228528,
|
108 |
0.00270796, -0.00120562]),
|