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README.md

@@ -10,7 +10,7 @@ language:
 tags:
 - art
 - music
-pretty_name: Dataset of Genshin Impact Songs in Piano Version
+pretty_name: Dataset of mihoyo game songs in piano version
 size_categories:
 - n<1K
 viewer: false
@@ -31,10 +31,11 @@ pip install -e .
 ```
 from datasets import load_dataset
 
-dataset = load_dataset("MuGeminorum/genshin_piano", split="train")
+genshin_data = load_dataset("MuGeminorum/hoyo_pianos", split="genshin")
+starail_data = load_dataset("MuGeminorum/hoyo_pianos", split="starail")
 ```
 
 ## Maintainence
 ```
-git clone git@hf.co:datasets/MuGeminorum/genshin_piano
+git clone git@hf.co:datasets/MuGeminorum/hoyo_pianos
 ```

data/genshin.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:46831e0ca0bfee86ca6cd4193bcbe2080b06bb808b0a7d5b57518e08c810369a
+size 172143

data/starail.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:79bdd889fbe73e1e36d317711455776fd2e97450d1708eab2f332d058df1dd6d
+size 36949

hoyo_pianos.py

@@ -0,0 +1,110 @@
+import os
+import shutil
+import random
+import hashlib
+import datasets
+from midi2abc import midi2abc
+
+
+_HOMEPAGE = f"https://huggingface.co/datasets/MuGeminorum/{os.path.basename(__file__).split('.')[0]}"
+
+_CITATION = """\
+@dataset{mihoyo_pianos,
+  author       = {MuGeminorum Studio},
+  title        = {mihoyo game piano songs},
+  month        = {nov},
+  year         = {2023},
+  publisher    = {HF},
+  version      = {1.1},
+  url          = {https://huggingface.co/datasets/MuGeminorum/hoyo_pianos}
+}
+"""
+
+_DESCRIPTION = """\
+This database contains mihoyo game piano songs downloaded from musescore
+"""
+
+_URLS = {
+    "genshin": f"{_HOMEPAGE}/resolve/main/data/genshin.zip",
+    "starail": f"{_HOMEPAGE}/resolve/main/data/starail.zip"
+}
+
+
+class hoyo_pianos(datasets.GeneratorBasedBuilder):
+    def _info(self):
+        return datasets.DatasetInfo(
+            features=datasets.Features(
+                {
+                    "midi": datasets.Value("string"),
+                    "abc": datasets.Value("string"),
+                    "tag": datasets.Value("string")
+                }
+            ),
+            supervised_keys=("abc", "tags"),
+            homepage=_HOMEPAGE,
+            license="mit",
+            citation=_CITATION,
+            description=_DESCRIPTION
+        )
+
+    def _calculate_hash(self, file_path):
+        # 计算文件的哈希值
+        with open(file_path, 'rb') as midi_file:
+            content = midi_file.read()
+            return hashlib.md5(content).hexdigest()
+
+    def _rm_duplicates_in_folder(self, input_folder):
+        # 用于存储文件哈希值的字典
+        hash_dict = {}
+        duplist = []
+        # 遍历输入文件夹
+        for root, _, files in os.walk(input_folder):
+            for file in files:
+                file_path = os.path.join(root, file)
+                file_hash = self._calculate_hash(file_path)
+
+                # 检查文件哈希值是否已存在
+                if file_hash in hash_dict:
+                    print(f"Duplicates found: {file}")
+                    # 将重复文件直接删除
+                    duplist.append(file_path)
+                    shutil.rmtree(file_path)
+                else:
+                    # 存储文件哈希值
+                    hash_dict[file_hash] = file_path
+
+        return duplist
+
+    def _split_generators(self, dl_manager):
+        dataset = []
+        for key in _URLS.keys():
+            data_files = dl_manager.download_and_extract(_URLS[key])
+            files = dl_manager.iter_files([data_files])
+            subset = []
+
+            extract_dir = f'{data_files}\\{key}'
+            duplist = self._rm_duplicates_in_folder(extract_dir)
+
+            for path in files:
+                if (not path in duplist) and (os.path.basename(path).endswith(".mid")):
+                    subset.append(path)
+
+            random.shuffle(subset)
+            dataset.append(
+                datasets.SplitGenerator(
+                    name=key,
+                    gen_kwargs={
+                        "files": subset
+                    }
+                )
+            )
+
+        return dataset
+
+    def _generate_examples(self, files):
+        for i, path in enumerate(files):
+            yield i, {
+                "midi": path,
+                "abc": midi2abc(path),
+                "tag": os.path.basename(path)[:-4].encode('cp437').decode('gbk')
+            }