Delete genshin_piano.py

genshin_piano.py

@@ -1,130 +0,0 @@
-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{genshin_piano,
-  author       = {MuGeminorum Studio},
-  title        = {Genshin Piano Songs},
-  month        = {nov},
-  year         = {2023},
-  publisher    = {HF},
-  version      = {1.1},
-  url          = {https://huggingface.co/datasets/MuGeminorum/genshin_piano}
-}
-"""
-
-_DESCRIPTION = """\
-This database contains genshin piano songs downloaded from musescore
-"""
-
-_URL = f"{_HOMEPAGE}/resolve/main/data/dataset.zip"
-
-
-def calculate_hash(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(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 = 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
-
-
-class genshin_piano(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 _split_generators(self, dl_manager):
-        data_files = dl_manager.download_and_extract(_URL)
-        files = dl_manager.iter_files([data_files])
-        dataset = []
-
-        extract_dir = data_files + '\\dataset'
-        duplist = rm_duplicates_in_folder(extract_dir)
-
-        for path in files:
-            if (not path in duplist) and (os.path.basename(path).endswith(".mid")):
-                dataset.append(path)
-
-        random.shuffle(dataset)
-        # data_count = len(dataset)
-        # p80 = int(data_count * 0.8)
-        # p90 = int(data_count * 0.9)
-
-        # return [
-        #     datasets.SplitGenerator(
-        #         name=datasets.Split.TRAIN,
-        #         gen_kwargs={
-        #             "files": dataset[:p80]
-        #         }
-        #     ),
-        #     datasets.SplitGenerator(
-        #         name=datasets.Split.VALIDATION,
-        #         gen_kwargs={
-        #             "files": dataset[p80:p90]
-        #         }
-        #     ),
-        #     datasets.SplitGenerator(
-        #         name=datasets.Split.TEST,
-        #         gen_kwargs={
-        #             "files": dataset[p90:]
-        #         }
-        #     )
-        # ]
-
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                gen_kwargs={
-                    "files": 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')
-            }