upd md

.gitignore

@@ -1,3 +1,2 @@
-rename.sh
 test.*
 *__pycache__*

README.md

@@ -114,7 +114,7 @@ This dataset was created and has been utilized for Erhu playing technique detect
 ## Integration
 We first perform label cleaning to abandon the labels for the four and seven categories, since there are also missing data problems. This process leaves us with only the labels for the 11 categories. Then, we add Chinese character label and Chinese pinyin label to enhance comprehensibility. The 11 labels are: Detache (分弓), Diangong (垫弓), Harmonic (泛音), Legato\slide\glissando (连弓\滑音\连音), Percussive (击弓), Pizzicato (拨弦), Ricochet (抛弓), Staccato (断弓), Tremolo (震音), Trill (颤音), and Vibrato (揉弦). After integration, the data structure contains six columns: audio (with a sampling rate of 44,100 Hz), mel spectrograms, numeric label, Italian label, Chinese character label, and Chinese pinyin label. The total number of audio clips remains at 1,253, with a total duration of 25.81 minutes. The average duration is 1.24 seconds.
 
-We constructed the [default subset](#default-subset) of the current integrated version dataset based on its 11 classification data and optimized the names of the 11 categories. The data structure can be seen in the [viewer](https://huggingface.co/datasets/ccmusic-database/erhu_playing_tech/viewer). Although the original dataset has been cited in some articles, the experiments in those articles lack reproducibility. In order to demonstrate the effectiveness of the default subset, we further processed the data and constructed the [eval subset](#eval-subset) to supplement the evaluation of this integrated version dataset. The results of the evaluation can be viewed in [[2]](https://huggingface.co/ccmusic-database/erhu_playing_tech).
+We constructed the [default subset](#usage) of the current integrated version dataset based on its 11 classification data and optimized the names of the 11 categories. The data structure can be seen in the [viewer](https://huggingface.co/datasets/ccmusic-database/erhu_playing_tech/viewer). Although the original dataset has been cited in some articles, the experiments in those articles lack reproducibility. In order to demonstrate the effectiveness of the default subset, we further processed the data and constructed the [eval subset](#usage) to supplement the evaluation of this integrated version dataset. The results of the evaluation can be viewed in [[2]](https://huggingface.co/ccmusic-database/erhu_playing_tech).
 
 ## Statistics
 | ![](https://www.modelscope.cn/datasets/ccmusic-database/erhu_playing_tech/resolve/master/data/erhu_pie.jpg) | ![](https://www.modelscope.cn/datasets/ccmusic-database/erhu_playing_tech/resolve/master/data/erhu.jpg) | ![](https://www.modelscope.cn/datasets/ccmusic-database/erhu_playing_tech/resolve/master/data/erhu_bar.jpg) |
@@ -208,34 +208,17 @@ Erhu Playing Technique Classification
 Chinese, English
 
 ## Usage
-### Default Subset
 ```python
 from datasets import load_dataset
 
-ds = load_dataset("ccmusic-database/erhu_playing_tech", name="default")
-for item in ds["train"]:
-    print(item)
-
-for item in ds["validation"]:
-    print(item)
-
-for item in ds["test"]:
-    print(item)
-```
-
-### Eval Subset
-```python
-from datasets import load_dataset
-
-dataset = load_dataset("ccmusic-database/erhu_playing_tech", name="eval")
-for item in ds["train"]:
-    print(item)
-
-for item in ds["validation"]:
-    print(item)
-
-for item in ds["test"]:
-    print(item)
+ds = load_dataset(
+    "ccmusic-database/erhu_playing_tech",
+    name="default",  # default / eval
+    split="train",  # train / validation / test
+    cache_dir="./__pycache__",
+)
+for i in ds:
+    print(i)
 ```
 
 ## Maintenance