Update README.md

README.md

@@ -1,33 +1,34 @@
----
-license: mit
----
-
-Our evaluation methodology adopted the approach for structural segmentation evaluation outlined in the Harmonix set, which employed Structural Features for boundary identification, and 2D-Fourier Magnitude Coefficients (2D-FMC) for segment labeling based on acoustic similarity. CQT features serve as input features for the algorithm. The algorithm is implemented using Music Structure Analysis Framework (MSAF). For evaluation metrics, the F-measure is reported for the following metrics: Hit Rate with 0.5 and 3-second windows for boundary retrieval, Pairwise Frame Clustering and Entropy Scores for segment labeling. The evaluation is implemented using mir_eval.
-
-## Evaluation result
-<img src="./segment_results.jpg">
-
-## Download
-```
-# By API
-pip install modelscope
-from modelscope import snapshot_download
-model_dir = snapshot_download('ccmusic-database/song_structure')
-
-# By Git
-git clone https://www.modelscope.cn/ccmusic-database/song_structure.git
-cd song_structure
-```
-
-## Cite
-```bibtex
-@dataset{zhaorui_liu_2021_5676893,
-  author       = {Monan Zhou, Shenyang Xu, Zhaorui Liu, Zhaowen Wang, Feng Yu, Wei Li and Baoqiang Han},
-  title        = {CCMusic: an Open and Diverse Database for Chinese and General Music Information Retrieval Research},
-  month        = {mar},
-  year         = {2024},
-  publisher    = {HuggingFace},
-  version      = {1.2},
-  url          = {https://huggingface.co/ccmusic-database}
-}
+---
+license: mit
+---
+
+Our evaluation methodology adopted the approach for structural segmentation evaluation outlined in the Harmonix set, which employed Structural Features for boundary identification, and 2D-Fourier Magnitude Coefficients (2D-FMC) for segment labeling based on acoustic similarity. CQT features serve as input features for the algorithm. The algorithm is implemented using Music Structure Analysis Framework (MSAF). For evaluation metrics, the F-measure is reported for the following metrics: Hit Rate with 0.5 and 3-second windows for boundary retrieval, Pairwise Frame Clustering and Entropy Scores for segment labeling. The evaluation is implemented using mir_eval.
+
+## Evaluation result
+<img src="./segment_results.jpg">
+
+## Download
+### By Git
+```bash
+git clone https://www.modelscope.cn/ccmusic-database/song_structure.git
+pip install modelscope
+```
+
+### By API
+```python
+from modelscope import snapshot_download
+model_dir = snapshot_download('ccmusic-database/song_structure')
+```
+
+## Cite
+```bibtex
+@dataset{zhaorui_liu_2021_5676893,
+  author       = {Monan Zhou, Shenyang Xu, Zhaorui Liu, Zhaowen Wang, Feng Yu, Wei Li and Baoqiang Han},
+  title        = {CCMusic: an Open and Diverse Database for Chinese and General Music Information Retrieval Research},
+  month        = {mar},
+  year         = {2024},
+  publisher    = {HuggingFace},
+  version      = {1.2},
+  url          = {https://huggingface.co/ccmusic-database}
+}
 ```