add 2 spects

data/chroma.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:eb6bb316d1fd7cd43737f30fba0aeaa81475daaa8f0b0e2c56b341e69465209b
+size 1424507306

data/cqt.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:eb6bb316d1fd7cd43737f30fba0aeaa81475daaa8f0b0e2c56b341e69465209b
+size 1424507306

music_genre.py

@@ -55,7 +55,11 @@ This database contains about 1700 musical pieces (.mp3 format)
 with lengths of 270-300s that are divided into 17 genres in total. 
 """
 
-_URL = _HOMEPAGE + "/resolve/main/data/mel.zip"
+_URLS = {
+    "mel": _HOMEPAGE + "/resolve/main/data/mel.zip",
+    "cqt": _HOMEPAGE + "/resolve/main/data/cqt.zip",
+    "chroma": _HOMEPAGE + "/resolve/main/data/chroma.zip"
+}
 
 
 class music_genre(datasets.GeneratorBasedBuilder):
@@ -84,49 +88,39 @@ class music_genre(datasets.GeneratorBasedBuilder):
         )
 
     def _split_generators(self, dl_manager):
-        data_files = dl_manager.download_and_extract(_URL)
-        files = dl_manager.iter_files([data_files])
-
-        dataset = []
-        for path in files:
-            if os.path.basename(path).endswith(".jpg"):
-                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:]
-                },
-            ),
-        ]
+        splits = []
+        for spect in _URLS.keys():
+            data_files = dl_manager.download_and_extract(_URLS[spect])
+            files = dl_manager.iter_files([data_files])
+
+            dataset = []
+            for path in files:
+                if os.path.basename(path).endswith(".jpg"):
+                    dataset.append(path)
+
+            random.shuffle(dataset)
+
+            splits.append(
+                datasets.SplitGenerator(
+                    name=spect,
+                    gen_kwargs={
+                        "files": dataset,
+                        "spect": f"/{spect}/"
+                    }
+                )
+            )
+
+        return splits
 
     def _calc_label(self, path, depth, substr='/mel/'):
-        mel = substr
+        spect = substr
         dirpath = os.path.dirname(path)
-        substr_index = dirpath.find(mel)
+        substr_index = dirpath.find(spect)
         if substr_index < 0:
-            mel = '\\mel\\'
-            substr_index = dirpath.find(mel)
+            spect = spect.replace('/', '\\')
+            substr_index = dirpath.find(spect)
 
-        labstr = dirpath[substr_index + len(mel):]
+        labstr = dirpath[substr_index + len(spect):]
         labs = labstr.split('/')
         if len(labs) < 2:
             labs = labstr.split('\\')
@@ -136,11 +130,11 @@ class music_genre(datasets.GeneratorBasedBuilder):
         else:
             return 0
 
-    def _generate_examples(self, files):
+    def _generate_examples(self, files, spect):
         for i, path in enumerate(files):
             yield i, {
                 "mel": path,
-                "fst_level_label": _NAMES_1[self._calc_label(path, 1)],
-                "sec_level_label": _NAMES_2[self._calc_label(path, 2)],
-                "thr_level_label": _NAMES_3[self._calc_label(path, 3)]
+                "fst_level_label": _NAMES_1[self._calc_label(path, 1, spect)],
+                "sec_level_label": _NAMES_2[self._calc_label(path, 2, spect)],
+                "thr_level_label": _NAMES_3[self._calc_label(path, 3, spect)]
             }