upl all

.gitignore

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+rename.sh
+test.py

README.md

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 ---
 license: mit
 ---
+
+# Dataset Card for "george-chou/pianos_wav"
+## Requirements
+```
+python 3.8-3.10
+soundfile
+librosa
+```
+
+## Usage
+```
+from datasets import load_dataset
+
+data = load_dataset("george-chou/pianos_wav", split="train")
+labels = data.features['label'].names
+
+for item in data:
+    print('audio info: ', item['audio'])
+    print('label name: ' + labels[item['label']])
+```
+
+## Maintenance
+```
+git clone git@hf.co:datasets/george-chou/pianos_wav
+```
+
+## Cite
+```
+@dataset{zhaorui_liu_2021_5676893,
+  author       = {Zhaorui Liu and Zijin Li},
+  title        = {{Music Data Sharing Platform for Computational Musicology Research (CCMUSIC DATASET)}},
+  month        = nov,
+  year         = 2021,
+  publisher    = {Zenodo},
+  version      = {1.1},
+  doi          = {10.5281/zenodo.5676893},
+  url          = {https://doi.org/10.5281/zenodo.5676893}
+}
+```

data/1_PearlRiver.zip

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+oid sha256:ec84513e69aa983dd60665d6e355ab3417802c4968de03a59bc5fd4f9edffea2
+size 16001626

data/2_YoungChang.zip

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+size 99240728

data/3_Steinway-T.zip

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+size 61769871

data/4_Hsinghai.zip

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+size 35421121

data/5_Kawai.zip

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+size 38260629

data/6_Steinway.zip

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+size 35046320

data/7_Kawai-G.zip

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+oid sha256:8a51c08b58868d57a2aef708580507a63d16302133afa314472d72470fc25139
+size 19742382

data/8_Yamaha.zip

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+oid sha256:3a2ff74144de97c169edcacc77288fdc77fed2dc75a509899bb7b744be734332
+size 46875645

piano_sound_quality.py

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+import io
+import os
+import wave
+import zipfile
+import datasets
+import requests
+from datasets.tasks import AudioClassification
+
+
+# Once upload a new piano brand, please register its name here
+_NAMES = [
+    "1_PearlRiver",
+    "2_YoungChang",
+    "3_Steinway-T",
+    "4_Hsinghai",
+    "5_Kawai",
+    "6_Steinway",
+    "7_Kawai-G",
+    "8_Yamaha",
+]
+
+_DBNAME = os.path.basename(__file__).split('.')[0]
+
+_HOMEPAGE = "https://huggingface.co/datasets/ccmusic-database/" + _DBNAME
+
+_CITATION = """\
+@dataset{zhaorui_liu_2021_5676893,
+  author       = {Zhaorui Liu and Zijin Li},
+  title        = {{Music Data Sharing Platform for Computational Musicology Research (CCMUSIC DATASET)}},
+  month        = nov,
+  year         = 2021,
+  publisher    = {Zenodo},
+  version      = {1.1},
+  doi          = {10.5281/zenodo.5676893},
+  url          = {https://doi.org/10.5281/zenodo.5676893}
+}
+"""
+
+_DESCRIPTION = """\
+Piano-Sound-Quality-Database is a dataset of piano sound. 
+It consists of 8 kinds of pianos including
+PearlRiver, YoungChang, Steinway-T, Hsinghai, Kawai, Steinway, Kawai-G, Yamaha. 
+Data was annotated by students from the China Conservatory of Music (CCMUSIC) in Beijing
+and collected by George Chou.
+"""
+
+_URLS = {piano: _HOMEPAGE + "/resolve/main/data/" +
+         piano + ".zip" for piano in _NAMES}
+
+
+_PITCHES = {"009": "A2", "010": "A2#/B2b", "011": "B2", "100": "C1", "101": "C1#/D1b", "102": "D1", "103": "D1#/E1b",
+            "104": "E1", "105": "F1", "106": "F1#/G1b", "107": "G1", "108": "G1#/A1b", "109": "A1", "110": "A1#/B1b",
+            "111": "B1", "200": "C", "201": "C#/Db", "202": "D", "203": "D#/Eb", "204": "E", "205": "F", "206": "F#/Gb",
+            "207": "G", "208": "G#/Ab", "209": "A", "210": "A#/Bb", "211": "B", "300": "c", "301": "c#/db", "302": "d",
+            "303": "d#/eb", "304": "e", "305": "f", "306": "f#/gb", "307": "g", "308": "g#/ab", "309": "a", "310": "a#/bb",
+            "311": "b", "400": "c1", "401": "c1#/d1b", "402": "d1", "403": "d1#/e1b", "404": "e1", "405": "f1",
+            "406": "f1#/g1b", "407": "g1", "408": "g1#/a1b", "409": "a1", "410": "a1#/b1b", "411": "b1", "500": "c2",
+            "501": "c2#/d2b", "502": "d2", "503": "d2#/e2b", "504": "e2", "505": "f2", "506": "f2#/g2b", "507": "g2",
+            "508": "g2#/a2b", "509": "a2", "510": "a2#/b2b", "511": "b2", "600": "c3", "601": "c3#/d3b", "602": "d3",
+            "603": "d3#/e3b", "604": "e3", "605": "f3", "606": "f3#/g3b", "607": "g3", "608": "g3#/a3b", "609": "a3",
+            "610": "a3#/b3b", "611": "b3", "700": "c4", "701": "c4#/d4b", "702": "d4", "703": "d4#/e4b", "704": "e4",
+            "705": "f4", "706": "f4#/g4b", "707": "g4", "708": "g4#/a4b", "709": "a4", "710": "a4#/b4b", "711": "b4",
+            "800": "c5"}
+
+
+class piano_sound_quality(datasets.GeneratorBasedBuilder):
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    "audio": datasets.Audio(sampling_rate=44_100),
+                    "label": datasets.features.ClassLabel(names=_NAMES),
+                    "pitch": datasets.Value("string"),
+                    "duration": datasets.Value("float64"),
+                }
+            ),
+            supervised_keys=("audio", "label"),
+            homepage=_HOMEPAGE,
+            license="mit",
+            citation=_CITATION,
+            task_templates=[
+                AudioClassification(
+                    task="audio-classification",
+                    audio_column="audio",
+                    label_column="label",
+                )
+            ],
+        )
+
+    def _get_wav_duration(self, file_bytes):
+        with wave.open(io.BytesIO(file_bytes), 'r') as wav_file:
+            frames = wav_file.getnframes()
+            rate = wav_file.getframerate()
+            duration = frames / float(rate)
+        return round(duration, 3)
+
+    def _read_zip(self, zip_url, wav_file_path):
+        resp = requests.get(zip_url)
+        with zipfile.ZipFile(io.BytesIO(resp.content)) as zip_file:
+            with zip_file.open(wav_file_path) as file:
+                file_data = file.read()
+                return self._get_wav_duration(file_data)
+
+    def _split_generators(self, dl_manager):
+        data_files = dl_manager.download_and_extract(_URLS)
+        split_generator = []
+
+        for index in _URLS.keys():
+            split_generator.append(
+                datasets.SplitGenerator(
+                    name=index.replace('-', '_'),
+                    gen_kwargs={
+                        "files": dl_manager.iter_files([data_files[index]]),
+                    },
+                )
+            )
+
+        return split_generator
+
+    def _generate_examples(self, files):
+        for i, path in enumerate(files):
+            file_name = os.path.basename(path)
+            if file_name.endswith(".wav"):
+                yield i, {
+                    "audio": path,
+                    "label": os.path.basename(os.path.dirname(path)),
+                    "pitch": _PITCHES[file_name[1:4]],
+                    "duration": self._read_zip(path.split('::')[1], path.split('::')[0].split('//')[1]),
+                }