refine code

pianos.py

@@ -13,10 +13,10 @@ _NAMES = [
     "Kawai",
     "Steinway",
     "Kawai-G",
-    "Yamaha"
+    "Yamaha",
 ]
 
-_NAME = os.path.basename(__file__).split('.')[0]
+_NAME = os.path.basename(__file__).split(".")[0]
 
 _HOMEPAGE = f"https://huggingface.co/datasets/ccmusic-database/{_NAME}"
 
@@ -38,18 +38,94 @@ Piano-Sound-Quality is a dataset of piano sound. It consists of 8 kinds of piano
 """
 
 _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"
+    "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",
 }
 
 
@@ -61,7 +137,9 @@ class pianos(datasets.GeneratorBasedBuilder):
                 {
                     "mel": datasets.Image(),
                     "label": datasets.features.ClassLabel(names=_NAMES),
-                    "pitch": datasets.features.ClassLabel(names=list(_PITCHES.values()))
+                    "pitch": datasets.features.ClassLabel(
+                        names=list(_PITCHES.values())
+                    ),
                 }
             ),
             supervised_keys=("mel", "label"),
@@ -72,16 +150,16 @@ class pianos(datasets.GeneratorBasedBuilder):
                 ImageClassification(
                     task="image-classification",
                     image_column="mel",
-                    label_column="label"
+                    label_column="label",
                 )
-            ]
+            ],
         )
 
-    def _cdn_url(self, ip='127.0.0.1', port=80):
+    def _cdn_url(self, ip="127.0.0.1", port=80):
         try:
             # easy for local test
             with socket.create_connection((ip, port), timeout=5):
-                return f'http://{ip}/{_NAME}/data/pianos_data.zip'
+                return f"http://{ip}/hf/{_NAME}/data/pianos_data.zip"
 
         except (socket.timeout, socket.error):
             return f"{_HOMEPAGE}/resolve/main/data/pianos_data.zip"
@@ -93,11 +171,13 @@ class pianos(datasets.GeneratorBasedBuilder):
         for path in dl_manager.iter_files([data_files]):
             fname = os.path.basename(path)
             if fname.endswith(".jpg"):
-                dataset.append({
-                    'mel': path,
-                    'label': os.path.basename(os.path.dirname(path)),
-                    'pitch': _PITCHES[fname.split('_')[0]]
-                })
+                dataset.append(
+                    {
+                        "mel": path,
+                        "label": os.path.basename(os.path.dirname(path)),
+                        "pitch": _PITCHES[fname.split("_")[0]],
+                    }
+                )
 
         random.shuffle(dataset)
         count = len(dataset)
@@ -106,29 +186,20 @@ class pianos(datasets.GeneratorBasedBuilder):
 
         return [
             datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                gen_kwargs={
-                    "files": dataset[:p80]
-                }
+                name=datasets.Split.TRAIN, gen_kwargs={"files": dataset[:p80]}
             ),
             datasets.SplitGenerator(
-                name=datasets.Split.VALIDATION,
-                gen_kwargs={
-                    "files": dataset[p80:p90]
-                }
+                name=datasets.Split.VALIDATION, gen_kwargs={"files": dataset[p80:p90]}
             ),
             datasets.SplitGenerator(
-                name=datasets.Split.TEST,
-                gen_kwargs={
-                    "files": dataset[p90:]
-                }
-            )
+                name=datasets.Split.TEST, gen_kwargs={"files": dataset[p90:]}
+            ),
         ]
 
     def _generate_examples(self, files):
         for i, path in enumerate(files):
             yield i, {
-                "mel": path['mel'],
-                "label": path['label'],
-                "pitch": path['pitch']
+                "mel": path["mel"],
+                "label": path["label"],
+                "pitch": path["pitch"],
             }