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Datasets:
pianistprogrammer
/
meter2800

Tasks:
Audio Classification
Modalities:
Audio
Languages:
English
Tags:
audio
music-classification
meter-classification
multi-class-classification
multi-label-classification
License:
Dataset card Files Community
pianistprogrammer commited on
Commit
8b77150
·
verified ·
1 Parent(s): e8119c9

Delete .ipynb_checkpoints

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Files changed (9) hide show
  1. .ipynb_checkpoints/Data_cleaning-checkpoint.ipynb +0 -531
  2. .ipynb_checkpoints/HF-UPLOAD-checkpoint.ipynb +0 -6
  3. .ipynb_checkpoints/data_test_2_classes-checkpoint.csv +0 -601
  4. .ipynb_checkpoints/data_test_4_classes-checkpoint.csv +0 -701
  5. .ipynb_checkpoints/data_train_2_classes-checkpoint.csv +0 -1441
  6. .ipynb_checkpoints/data_train_4_classes-checkpoint.csv +0 -1681
  7. .ipynb_checkpoints/data_val_4_classes-checkpoint.csv +0 -421
  8. .ipynb_checkpoints/mp3-to-wav-checkpoint.ipynb +0 -6
  9. .ipynb_checkpoints/testing_dataset_on _hf-checkpoint.ipynb +0 -127
.ipynb_checkpoints/Data_cleaning-checkpoint.ipynb DELETED
@@ -1,531 +0,0 @@
1
- {
2
- "cells": [
3
- {
4
- "cell_type": "code",
5
- "execution_count": null,
6
- "id": "d88426e1-fa5b-416a-8af0-e5bfec7450c3",
7
- "metadata": {},
8
- "outputs": [],
9
- "source": [
10
- "# import os\n",
11
- "# import shutil\n",
12
- "\n",
13
- "# def move_audio_files_to_root(gtzan_root_path):\n",
14
- "# \"\"\"\n",
15
- "# Moves all .wav (or .mp3) files from genre subfolders to the root GTZAN folder.\n",
16
- "\n",
17
- "# Args:\n",
18
- "# gtzan_root_path (str): The path to the GTZAN root directory.\n",
19
- "# \"\"\"\n",
20
- "# print(f\"Starting to move audio files from subfolders to: {gtzan_root_path}\")\n",
21
- "\n",
22
- "# if not os.path.isdir(gtzan_root_path):\n",
23
- "# print(f\"Error: The specified path '{gtzan_root_path}' does not exist or is not a directory.\")\n",
24
- "# return\n",
25
- "\n",
26
- "# # Iterate through each item in the GTZAN root directory\n",
27
- "# for item_name in os.listdir(gtzan_root_path):\n",
28
- "# item_path = os.path.join(gtzan_root_path, item_name)\n",
29
- "\n",
30
- "# # Check if it's a directory (assuming genre folders are directories)\n",
31
- "# if os.path.isdir(item_path):\n",
32
- "# genre_folder_path = item_path\n",
33
- "# print(f\"\\nEntering genre folder: {genre_folder_path}\")\n",
34
- "\n",
35
- "# # Iterate through files in the genre folder\n",
36
- "# for file_name in os.listdir(genre_folder_path):\n",
37
- "# file_path = os.path.join(genre_folder_path, file_name)\n",
38
- "\n",
39
- "# # Check if it's a file and has a .wav or .mp3 extension\n",
40
- "# # The user mentioned .wav in the path example and .mp3 in the request.\n",
41
- "# # This script will handle both, prioritizing .wav as per the example.\n",
42
- "# if os.path.isfile(file_path) and (file_name.endswith('.wav') or file_name.endswith('.mp3')):\n",
43
- "# destination_path = os.path.join(gtzan_root_path, file_name)\n",
44
- "\n",
45
- "# # Handle potential file name collisions\n",
46
- "# if os.path.exists(destination_path):\n",
47
- "# print(f\"Warning: File '{file_name}' already exists in the root folder. Skipping move for this file.\")\n",
48
- "# else:\n",
49
- "# try:\n",
50
- "# shutil.move(file_path, destination_path)\n",
51
- "# print(f\"Moved: '{file_path}' -> '{destination_path}'\")\n",
52
- "# except Exception as e:\n",
53
- "# print(f\"Error moving file '{file_name}': {e}\")\n",
54
- " \n",
55
- "# # Optional: Remove the empty genre folder after moving files\n",
56
- "# # This is commented out by default to be safe. Uncomment if desired.\n",
57
- "# # try:\n",
58
- "# # if not os.listdir(genre_folder_path): # Check if folder is empty\n",
59
- "# # os.rmdir(genre_folder_path)\n",
60
- "# # print(f\"Removed empty folder: {genre_folder_path}\")\n",
61
- "# # except OSError as e:\n",
62
- "# # print(f\"Error removing folder {genre_folder_path}: {e}\")\n",
63
- "\n",
64
- "# print(\"\\nScript execution finished.\")\n",
65
- "\n",
66
- "# # --- How to use this script ---\n",
67
- "# # 1. Save this code as a Python file (e.g., move_gtzan_files.py).\n",
68
- "# # 2. Replace 'path/to/your/GTZAN' with the actual path to your GTZAN folder.\n",
69
- "# # Example: If your GTZAN folder is at /Users/YourName/Music/GTZAN,\n",
70
- "# # then set gtzan_folder = '/Users/YourName/Music/GTZAN'\n",
71
- "# # 3. Run the script from your terminal: python move_gtzan_files.py\n",
72
- "\n",
73
- "# # IMPORTANT: Before running, it is highly recommended to back up your GTZAN folder\n",
74
- "# # or test this script on a copy of your data to prevent accidental data loss.\n",
75
- "\n",
76
- "# # Set the path to your GTZAN root folder here:\n",
77
- "# # For example:\n",
78
- "# # gtzan_folder_path = \"/Users/youruser/Documents/GTZAN\"\n",
79
- "# # Or if it's in the same directory as the script:\n",
80
- "# # gtzan_folder_path = \"GTZAN\"\n",
81
- "\n",
82
- "# # !!! IMPORTANT: Replace 'YOUR_GTZAN_ROOT_PATH_HERE' with the actual path !!!\n",
83
- "# gtzan_folder_path = 'GTZAN' \n",
84
- "\n",
85
- "# # Call the function to move the files\n",
86
- "# move_audio_files_to_root(gtzan_folder_path)\n",
87
- "\n"
88
- ]
89
- },
90
- {
91
- "cell_type": "code",
92
- "execution_count": null,
93
- "id": "02c0a633-987d-41ac-b36f-c275321cf06c",
94
- "metadata": {},
95
- "outputs": [],
96
- "source": [
97
- "# import os\n",
98
- "# import csv\n",
99
- "\n",
100
- "# def check_wav_files_against_csvs(gtzan_root_path, csv_file_paths):\n",
101
- "# \"\"\"\n",
102
- "# Checks which WAV files in the GTZAN root folder are not listed in any of the provided CSV files.\n",
103
- "# Also reports which CSV files a WAV file is found in, if it exists.\n",
104
- "\n",
105
- "# Args:\n",
106
- "# gtzan_root_path (str): The path to the GTZAN root directory where WAV files are expected.\n",
107
- "# csv_file_paths (list): A list of full paths to the CSV files to check against.\n",
108
- "# \"\"\"\n",
109
- "# print(f\"Starting check for WAV files in '{gtzan_root_path}' against {len(csv_file_paths)} CSVs.\")\n",
110
- "\n",
111
- "# # Validate GTZAN root path\n",
112
- "# if not os.path.isdir(gtzan_root_path):\n",
113
- "# print(f\"Error: The specified GTZAN path '{gtzan_root_path}' does not exist or is not a directory.\")\n",
114
- "# return\n",
115
- "\n",
116
- "# # 1. Get all WAV files directly in the GTZAN root folder\n",
117
- "# gtzan_wav_files_found = set()\n",
118
- "# try:\n",
119
- "# # Iterate through items in the specified GTZAN root directory\n",
120
- "# for item_name in os.listdir(gtzan_root_path):\n",
121
- "# item_path = os.path.join(gtzan_root_path, item_name)\n",
122
- "# # Check if it's a file and ends with '.wav'\n",
123
- "# if os.path.isfile(item_path) and item_name.endswith('.wav'):\n",
124
- "# gtzan_wav_files_found.add(item_name) # Add just the filename (basename)\n",
125
- "# except Exception as e:\n",
126
- "# print(f\"Error reading GTZAN directory '{gtzan_root_path}': {e}\")\n",
127
- "# return\n",
128
- "\n",
129
- "# if not gtzan_wav_files_found:\n",
130
- "# print(f\"No .wav files found directly in '{gtzan_root_path}'. Please ensure files are in the root as expected.\")\n",
131
- "# return\n",
132
- "\n",
133
- "# # 2. Process CSVs: Store contents and map WAVs to CSVs\n",
134
- "# # A dictionary to store which CSV files each WAV basename is found in\n",
135
- "# # Format: {wav_basename: [csv_filename1, csv_filename2, ...]}\n",
136
- "# wav_to_csv_map = {}\n",
137
- "# # A combined set of all WAV basenames found across ALL CSVs for quick lookup\n",
138
- "# all_csv_files_combined = set()\n",
139
- "\n",
140
- "# for csv_path in csv_file_paths:\n",
141
- "# csv_base_name = os.path.basename(csv_path) # Get just the filename of the CSV\n",
142
- "\n",
143
- "# print(f\"Processing CSV: {csv_base_name}\")\n",
144
- "\n",
145
- "# # Validate CSV file path\n",
146
- "# if not os.path.isfile(csv_path):\n",
147
- "# print(f\"Warning: CSV file '{csv_path}' not found. Skipping this CSV.\")\n",
148
- "# continue\n",
149
- "\n",
150
- "# try:\n",
151
- "# with open(csv_path, mode='r', newline='', encoding='utf-8') as file:\n",
152
- "# reader = csv.reader(file)\n",
153
- "# header = next(reader, None) # Read the header row\n",
154
- "\n",
155
- "# if header is None:\n",
156
- "# print(f\"Warning: CSV file '{csv_base_name}' is empty or has no header. Skipping.\")\n",
157
- "# continue\n",
158
- "\n",
159
- "# # Find the index of the 'filename' column (case-insensitive for robustness)\n",
160
- "# filename_col_index = -1\n",
161
- "# for i, col_name in enumerate(header):\n",
162
- "# if col_name.strip().lower() == 'filename':\n",
163
- "# filename_col_index = i\n",
164
- "# break\n",
165
- "\n",
166
- "# if filename_col_index == -1:\n",
167
- "# print(f\"Error: 'filename' column not found in '{csv_base_name}'. Skipping this CSV.\")\n",
168
- "# continue\n",
169
- "\n",
170
- "# # Read through each row in the CSV\n",
171
- "# for row in reader:\n",
172
- "# if len(row) > filename_col_index:\n",
173
- "# full_filename_from_csv = row[filename_col_index].strip()\n",
174
- "# # Extract basename: e.g., '/GTZAN/country.00056.wav' -> 'country.00056.wav'\n",
175
- "# wav_basename = os.path.basename(full_filename_from_csv)\n",
176
- " \n",
177
- "# all_csv_files_combined.add(wav_basename) # Add to the combined set\n",
178
- "\n",
179
- "# # Update the map indicating which CSV this WAV file is in\n",
180
- "# if wav_basename not in wav_to_csv_map:\n",
181
- "# wav_to_csv_map[wav_basename] = []\n",
182
- "# if csv_base_name not in wav_to_csv_map[wav_basename]: # Avoid duplicate CSV entries for a WAV file\n",
183
- "# wav_to_csv_map[wav_basename].append(csv_base_name)\n",
184
- "\n",
185
- "# except Exception as e:\n",
186
- "# print(f\"Error reading CSV file '{csv_path}': {e}\")\n",
187
- "# continue\n",
188
- "\n",
189
- "# # 3. Cross-reference and report results\n",
190
- "# print(\"\\n--- Consistency Check Results ---\")\n",
191
- "\n",
192
- "# files_not_in_any_csv = [] # List to hold WAV files found in GTZAN but missing from all CSVs\n",
193
- "\n",
194
- "# # Iterate through all WAV files found in the GTZAN folder\n",
195
- "# for wav_file_basename in sorted(list(gtzan_wav_files_found)): # Sort for consistent output\n",
196
- "# if wav_file_basename not in all_csv_files_combined:\n",
197
- "# # If the WAV file is not in our combined set of all CSV filenames\n",
198
- "# files_not_in_any_csv.append(wav_file_basename)\n",
199
- " \n",
200
- "# # Report files that are NOT in any CSV\n",
201
- "# if files_not_in_any_csv:\n",
202
- "# print(\"\\n--- WAV files found in GTZAN folder but NOT listed in any CSV file: ---\")\n",
203
- "# for f in files_not_in_any_csv:\n",
204
- "# print(f\"- {f}\")\n",
205
- "# print(len(files_not_in_any_csv))\n",
206
- "# else:\n",
207
- "# print(\"\\nAll WAV files found in the GTZAN folder are listed in at least one CSV file.\")\n",
208
- " \n",
209
- "\n",
210
- "# print(\"\\nScript execution finished.\")\n",
211
- "\n",
212
- "\n",
213
- "# # --- How to use this script ---\n",
214
- "# # 1. Save this code as a Python file (e.g., check_gtzan_data.py).\n",
215
- "# # 2. Replace 'YOUR_GTZAN_ROOT_PATH_HERE' with the actual path to your GTZAN folder.\n",
216
- "# # 3. Replace 'YOUR_CSV_FOLDER_PATH_HERE' with the actual path to the folder containing your CSV files.\n",
217
- "# # If your CSVs are in the same directory as this script, you can use '.' for csv_folder_path.\n",
218
- "# # 4. Ensure the list 'csv_filenames' matches the exact names of your CSV files.\n",
219
- "# # 5. Uncomment the last line to run the function.\n",
220
- "# # 6. Run the script from your terminal: python check_gtzan_data.py\n",
221
- "\n",
222
- "# # Set the path to your GTZAN root folder here:\n",
223
- "# # Example: gtzan_folder_path = \"/Users/youruser/Documents/GTZAN\"\n",
224
- "# gtzan_folder_path = 'GTZAN'\n",
225
- "\n",
226
- "# # Set the path to the folder containing your CSV files.\n",
227
- "# # Example: csv_folder_path = \"/Users/youruser/Documents/MyData\"\n",
228
- "# # Or if CSVs are in the same directory as the script: csv_folder_path = \".\"\n",
229
- "# csv_folder_path = '.'\n",
230
- "\n",
231
- "# # List of your CSV file names\n",
232
- "# csv_filenames = [\n",
233
- "# 'data_test_4_classes.csv',\n",
234
- "# 'data_test_2_classes.csv',\n",
235
- "# 'data_train_4_classes.csv',\n",
236
- "# 'data_train_2_classes.csv',\n",
237
- "# 'data_val_4_classes.csv',\n",
238
- "# 'data_val_2_classes.csv',\n",
239
- "# ]\n",
240
- "\n",
241
- "# # Create full paths for the CSV files\n",
242
- "# csv_file_paths = [os.path.join(csv_folder_path, f_name) for f_name in csv_filenames]\n",
243
- "\n",
244
- "# # Call the function to check the files\n",
245
- "# # Uncomment the line below to execute the script:\n",
246
- "# check_wav_files_against_csvs(gtzan_folder_path, csv_file_paths)\n",
247
- "\n"
248
- ]
249
- },
250
- {
251
- "cell_type": "code",
252
- "execution_count": 7,
253
- "id": "9053eb78-c757-4f7b-ad0e-85d306955ddd",
254
- "metadata": {},
255
- "outputs": [
256
- {
257
- "name": "stdout",
258
- "output_type": "stream",
259
- "text": [
260
- "--- Starting Data Integrity Check ---\n",
261
- "Root data path: .\n",
262
- "CSV folder path: .\n",
263
- "Target CSVs: data_test_2_classes.csv, data_train_2_classes.csv, data_val_2_classes.csv\n",
264
- "Audio folders to check: GTZAN, MAG, OWN, FMA\n",
265
- "\n",
266
- "--- Checking for duplicate WAV files within audio folders ---\n",
267
- " No duplicate WAV files found in 'GTZAN'.\n",
268
- " No duplicate WAV files found in 'MAG'.\n",
269
- " No duplicate WAV files found in 'OWN'.\n",
270
- " No duplicate WAV files found in 'FMA'.\n",
271
- "------------------------------------------------------------\n",
272
- "\n",
273
- "--- Checking CSVs for duplicate filenames and total count ---\n",
274
- " No duplicate filenames found in CSV 'data_test_2_classes.csv'.\n",
275
- " Duplicate filenames found in CSV 'data_train_2_classes.csv':\n",
276
- " - /FMA/014576.wav\n",
277
- " - /FMA/021587.wav\n",
278
- " No duplicate filenames found in CSV 'data_val_2_classes.csv'.\n",
279
- "\n",
280
- " Total entries across data_test_2_classes.csv, data_train_2_classes.csv, data_val_2_classes.csv: 2398\n",
281
- " Warning: Total CSV entries (2398) do NOT match the expected 2800.\n",
282
- "------------------------------------------------------------\n",
283
- "\n",
284
- "--- Checking if CSV-listed files are present in their respective folders ---\n",
285
- " All files listed in the target CSVs were found in their respective audio folders.\n",
286
- "\n",
287
- " Total files listed in target CSVs: 2398\n",
288
- " Total CSV-listed files found on disk: 2398\n",
289
- "\n",
290
- "--- Data Integrity Check Finished ---\n"
291
- ]
292
- }
293
- ],
294
- "source": [
295
- "import os\n",
296
- "import csv\n",
297
- "\n",
298
- "def check_data_integrity(root_data_path, csv_folder_path, target_csv_filenames, audio_folders):\n",
299
- " \"\"\"\n",
300
- " Performs data integrity checks on audio files and CSV entries.\n",
301
- "\n",
302
- " Checks include:\n",
303
- " 1. Total file count from specific CSVs.\n",
304
- " 2. Duplicate WAV files within specified audio folders.\n",
305
- " 3. Duplicate filenames within specified CSV files.\n",
306
- " 4. Presence of CSV-listed files in their respective folders.\n",
307
- "\n",
308
- " Args:\n",
309
- " root_data_path (str): The parent directory containing audio folders (e.g., GTZAN, MAG).\n",
310
- " csv_folder_path (str): The path to the directory containing the CSV files.\n",
311
- " target_csv_filenames (list): A list of CSV filenames to check for total count and content.\n",
312
- " audio_folders (list): A list of audio folder names (e.g., ['GTZAN', 'MAG', 'OWN', 'FMA']).\n",
313
- " \"\"\"\n",
314
- " print(f\"--- Starting Data Integrity Check ---\")\n",
315
- " print(f\"Root data path: {root_data_path}\")\n",
316
- " print(f\"CSV folder path: {csv_folder_path}\")\n",
317
- " print(f\"Target CSVs: {', '.join(target_csv_filenames)}\")\n",
318
- " print(f\"Audio folders to check: {', '.join(audio_folders)}\\n\")\n",
319
- "\n",
320
- " # --- 1. Check for duplicate WAV files within audio folders ---\n",
321
- " print(\"--- Checking for duplicate WAV files within audio folders ---\")\n",
322
- " folder_wav_files = {} # Stores {folder_name: set_of_wav_basenames}\n",
323
- " \n",
324
- " for folder_name in audio_folders:\n",
325
- " folder_path = os.path.join(root_data_path, folder_name)\n",
326
- " if not os.path.isdir(folder_path):\n",
327
- " print(f\" Warning: Audio folder '{folder_path}' not found. Skipping duplicate check for this folder.\")\n",
328
- " continue\n",
329
- " \n",
330
- " current_folder_files = []\n",
331
- " duplicates_in_folder = set()\n",
332
- " seen_files = set()\n",
333
- "\n",
334
- " for file_name in os.listdir(folder_path):\n",
335
- " if file_name.lower().endswith(\".wav\"): # Case-insensitive check for .wav\n",
336
- " if file_name in seen_files:\n",
337
- " duplicates_in_folder.add(file_name)\n",
338
- " else:\n",
339
- " seen_files.add(file_name)\n",
340
- " current_folder_files.append(file_name) # Store for later path lookup\n",
341
- "\n",
342
- " folder_wav_files[folder_name] = set(current_folder_files) # Store unique basenames for cross-ref\n",
343
- "\n",
344
- " if duplicates_in_folder:\n",
345
- " print(f\" Duplicate WAV files found in '{folder_name}':\")\n",
346
- " for dup_file in sorted(list(duplicates_in_folder)):\n",
347
- " print(f\" - {dup_file}\")\n",
348
- " else:\n",
349
- " print(f\" No duplicate WAV files found in '{folder_name}'.\")\n",
350
- " print(\"-\" * 60 + \"\\n\")\n",
351
- "\n",
352
- " # --- 2. Check for duplicate filenames in CSVs and total count ---\n",
353
- " print(\"--- Checking CSVs for duplicate filenames and total count ---\")\n",
354
- " total_csv_entries = 0\n",
355
- " csv_file_contents = {} # Stores {csv_filename: [list_of_full_filenames_from_csv]}\n",
356
- "\n",
357
- " for csv_name in target_csv_filenames:\n",
358
- " csv_path = os.path.join(csv_folder_path, csv_name)\n",
359
- " if not os.path.isfile(csv_path):\n",
360
- " print(f\" Warning: CSV file '{csv_path}' not found. Skipping this CSV.\")\n",
361
- " continue\n",
362
- "\n",
363
- " current_csv_filenames = []\n",
364
- " duplicates_in_csv = set()\n",
365
- " seen_csv_filenames = set()\n",
366
- "\n",
367
- " try:\n",
368
- " with open(csv_path, mode='r', newline='', encoding='utf-8') as file:\n",
369
- " reader = csv.reader(file)\n",
370
- " header = next(reader, None) # Read the header row\n",
371
- "\n",
372
- " if header is None:\n",
373
- " print(f\" Warning: CSV file '{csv_name}' is empty or has no header. Skipping.\")\n",
374
- " continue\n",
375
- "\n",
376
- " filename_col_index = -1\n",
377
- " for i, col_name in enumerate(header):\n",
378
- " if col_name.strip().lower() == 'filename':\n",
379
- " filename_col_index = i\n",
380
- " break\n",
381
- " \n",
382
- " if filename_col_index == -1:\n",
383
- " print(f\" Error: 'filename' column not found in '{csv_name}'. Skipping this CSV.\")\n",
384
- " continue\n",
385
- "\n",
386
- " for row_num, row in enumerate(reader, 2): # Start row_num from 2 for data rows\n",
387
- " if len(row) > filename_col_index:\n",
388
- " full_filename_from_csv = row[filename_col_index].strip()\n",
389
- " if full_filename_from_csv in seen_csv_filenames:\n",
390
- " duplicates_in_csv.add(full_filename_from_csv)\n",
391
- " else:\n",
392
- " seen_csv_filenames.add(full_filename_from_csv)\n",
393
- " current_csv_filenames.append(full_filename_from_csv)\n",
394
- " total_csv_entries += 1\n",
395
- " else:\n",
396
- " print(f\" Warning: Row {row_num} in '{csv_name}' is malformed (missing filename column).\")\n",
397
- "\n",
398
- " csv_file_contents[csv_name] = current_csv_filenames\n",
399
- "\n",
400
- " if duplicates_in_csv:\n",
401
- " print(f\" Duplicate filenames found in CSV '{csv_name}':\")\n",
402
- " for dup_entry in sorted(list(duplicates_in_csv)):\n",
403
- " print(f\" - {dup_entry}\")\n",
404
- " else:\n",
405
- " print(f\" No duplicate filenames found in CSV '{csv_name}'.\")\n",
406
- "\n",
407
- " except Exception as e:\n",
408
- " print(f\" Error reading CSV file '{csv_path}': {e}\")\n",
409
- " \n",
410
- " print(f\"\\n Total entries across {', '.join(target_csv_filenames)}: {total_csv_entries}\")\n",
411
- " if total_csv_entries == 2800:\n",
412
- " print(\" Total CSV entries match the expected 2800. Great!\")\n",
413
- " else:\n",
414
- " print(f\" Warning: Total CSV entries ({total_csv_entries}) do NOT match the expected 2800.\")\n",
415
- " print(\"-\" * 60 + \"\\n\")\n",
416
- "\n",
417
- " # --- 3. Check if all files in CSVs are present in folders ---\n",
418
- " print(\"--- Checking if CSV-listed files are present in their respective folders ---\")\n",
419
- " all_csv_listed_files = [] # Store all (full_filename, csv_source) for cross-ref\n",
420
- " for csv_name, filenames in csv_file_contents.items():\n",
421
- " for filename_entry in filenames:\n",
422
- " all_csv_listed_files.append((filename_entry, csv_name))\n",
423
- "\n",
424
- " # Create a lookup for actual files on disk, using full normalized paths\n",
425
- " existing_audio_files_on_disk = set()\n",
426
- " for folder_name in audio_folders:\n",
427
- " folder_path = os.path.join(root_data_path, folder_name)\n",
428
- " if os.path.isdir(folder_path):\n",
429
- " for file_name in os.listdir(folder_path):\n",
430
- " if file_name.lower().endswith(\".wav\"):\n",
431
- " # Create the expected path string, matching CSV format (e.g., /GTZAN/file.wav)\n",
432
- " expected_csv_format_path = f\"/{folder_name}/{file_name}\"\n",
433
- " existing_audio_files_on_disk.add(expected_csv_format_path)\n",
434
- " \n",
435
- " missing_files_from_csvs = []\n",
436
- " found_files_count = 0\n",
437
- " \n",
438
- " for full_csv_filename, source_csv in all_csv_listed_files:\n",
439
- " # Normalize the CSV filename path to match our disk lookup (e.g., /GTZAN/file.wav)\n",
440
- " normalized_csv_path = os.path.normpath(full_csv_filename).replace(os.sep, '/') # Use forward slashes\n",
441
- " \n",
442
- " if normalized_csv_path in existing_audio_files_on_disk:\n",
443
- " found_files_count += 1\n",
444
- " # print(f\" Found: {full_csv_filename} (from {source_csv})\") # Uncomment for verbose output\n",
445
- " else:\n",
446
- " missing_files_from_csvs.append((full_csv_filename, source_csv))\n",
447
- "\n",
448
- " if missing_files_from_csvs:\n",
449
- " print(\"\\n The following files are listed in CSVs but NOT found in their expected audio folders:\")\n",
450
- " for missing_file, source_csv in sorted(missing_files_from_csvs):\n",
451
- " print(f\" - {missing_file} (listed in {source_csv})\")\n",
452
- " else:\n",
453
- " print(\" All files listed in the target CSVs were found in their respective audio folders.\")\n",
454
- " \n",
455
- " print(f\"\\n Total files listed in target CSVs: {len(all_csv_listed_files)}\")\n",
456
- " print(f\" Total CSV-listed files found on disk: {found_files_count}\")\n",
457
- "\n",
458
- " print(\"\\n--- Data Integrity Check Finished ---\")\n",
459
- "\n",
460
- "\n",
461
- "# --- How to use this script ---\n",
462
- "# 1. Save this code as a Python file (e.g., data_checker.py).\n",
463
- "# 2. **Replace 'YOUR_PARENT_DIRECTORY_PATH_HERE'** with the actual path to the directory\n",
464
- "# that contains your GTZAN, MAG, OWN, FMA folders. This is the 'root_data_path'.\n",
465
- "# Example: If your GTZAN, MAG, OWN, FMA are all directly under `/Users/YourName/AudioData/`,\n",
466
- "# then set `root_data_path = '/Users/YourName/AudioData/'`\n",
467
- "# 3. **Replace 'YOUR_CSV_FOLDER_PATH_HERE'** with the actual path to the folder\n",
468
- "# containing your CSV files.\n",
469
- "# Example: If your CSVs are in `/Users/YourName/MyCSVs/`, set `csv_folder_path = '/Users/YourName/MyCSVs/'`\n",
470
- "# If CSVs are in the same directory as this script, you can use `csv_folder_path = \".\"`\n",
471
- "# 4. The `target_csv_filenames` list is pre-filled with the ones you specified.\n",
472
- "# 5. The `audio_folders_to_check` list is pre-filled.\n",
473
- "# 6. Uncomment the last line to run the function.\n",
474
- "# 7. Run the script from your terminal: `python data_checker.py`\n",
475
- "\n",
476
- "# !!! IMPORTANT: Ensure your GTZAN folder has its WAV files in the root as per your previous script's output.\n",
477
- "\n",
478
- "# Set the parent directory path here (where GTZAN, MAG, OWN, FMA are located)\n",
479
- "root_data_path = '.'\n",
480
- "\n",
481
- "# Set the path to the folder containing your CSV files\n",
482
- "csv_folder_path = '.'\n",
483
- "\n",
484
- "# Define the CSV files to check\n",
485
- "target_csv_filenames = [\n",
486
- " 'data_test_2_classes.csv',\n",
487
- " 'data_train_2_classes.csv',\n",
488
- " 'data_val_2_classes.csv',\n",
489
- "]\n",
490
- "\n",
491
- "# Define the audio data folders to check for presence of files\n",
492
- "audio_folders_to_check = ['GTZAN', 'MAG', 'OWN', 'FMA']\n",
493
- "\n",
494
- "# Call the function to perform the integrity checks\n",
495
- "# Uncomment the line below to execute the script:\n",
496
- "check_data_integrity(root_data_path, csv_folder_path, target_csv_filenames, audio_folders_to_check)\n",
497
- "# print(\"\\nTo run the script, uncomment the last line and replace 'YOUR_PARENT_DIRECTORY_PATH_HERE' and 'YOUR_CSV_FOLDER_PATH_HERE' with your actual folder paths.\")\n",
498
- "# print(\"This script will help you verify the consistency of your dataset.\")\n"
499
- ]
500
- },
501
- {
502
- "cell_type": "code",
503
- "execution_count": null,
504
- "id": "8ed3c1ea-ca8f-4973-9642-9dfd3a6eb1e7",
505
- "metadata": {},
506
- "outputs": [],
507
- "source": []
508
- }
509
- ],
510
- "metadata": {
511
- "kernelspec": {
512
- "display_name": "Python 3 (ipykernel)",
513
- "language": "python",
514
- "name": "python3"
515
- },
516
- "language_info": {
517
- "codemirror_mode": {
518
- "name": "ipython",
519
- "version": 3
520
- },
521
- "file_extension": ".py",
522
- "mimetype": "text/x-python",
523
- "name": "python",
524
- "nbconvert_exporter": "python",
525
- "pygments_lexer": "ipython3",
526
- "version": "3.11.9"
527
- }
528
- },
529
- "nbformat": 4,
530
- "nbformat_minor": 5
531
- }
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
.ipynb_checkpoints/HF-UPLOAD-checkpoint.ipynb DELETED
@@ -1,6 +0,0 @@
1
- {
2
- "cells": [],
3
- "metadata": {},
4
- "nbformat": 4,
5
- "nbformat_minor": 5
6
- }
 
 
 
 
 
 
 
.ipynb_checkpoints/data_test_2_classes-checkpoint.csv DELETED
@@ -1,601 +0,0 @@
1
- filename,label,meter,alt_meter
2
- /GTZAN/country.00056.wav,three,3,6
3
- /MAG/00717.wav,three,3,6
4
- /GTZAN/metal.00003.wav,four,4,2
5
- /FMA/003263.wav,three,3,6
6
- /MAG/00780.wav,three,3,6
7
- /FMA/006593.wav,four,4,2
8
- /GTZAN/reggae.00059.wav,four,4,2
9
- /MAG/00265.wav,three,3,6
10
- /GTZAN/blues.00034.wav,four,4,2
11
- /GTZAN/blues.00048.wav,four,4,2
12
- /GTZAN/blues.00072.wav,three,3,6
13
- /FMA/001644.wav,four,4,2
14
- /GTZAN/rock.00078.wav,four,4,2
15
- /GTZAN/metal.00055.wav,four,4,2
16
- /MAG/00127.wav,three,3,6
17
- /MAG/00477.wav,three,3,6
18
- /GTZAN/rock.00037.wav,four,4,2
19
- /MAG/00020.wav,three,3,6
20
- /GTZAN/country.00085.wav,four,4,2
21
- /MAG/00835.wav,three,3,6
22
- /FMA/005268.wav,four,4,2
23
- /FMA/023161.wav,three,3,6
24
- /GTZAN/rock.00066.wav,four,4,2
25
- /MAG/00615.wav,three,3,6
26
- /FMA/008455.wav,four,4,2
27
- /MAG/00587.wav,three,3,6
28
- /FMA/005341.wav,four,4,2
29
- /MAG/00030.wav,three,3,6
30
- /GTZAN/rock.00050.wav,four,4,2
31
- /MAG/00484.wav,three,3,6
32
- /MAG/00445.wav,three,3,6
33
- /GTZAN/blues.00096.wav,four,4,2
34
- /MAG/00418.wav,three,3,6
35
- /GTZAN/reggae.00033.wav,four,4,2
36
- /GTZAN/reggae.00002.wav,four,4,2
37
- /FMA/060364.wav,three,3,6
38
- /GTZAN/reggae.00031.wav,four,4,2
39
- /FMA/027547.wav,three,3,6
40
- /MAG/00834.wav,three,3,6
41
- /GTZAN/country.00083.wav,four,4,2
42
- /MAG/00729.wav,three,3,6
43
- /GTZAN/pop.00027.wav,four,4,2
44
- /GTZAN/jazz.00067.wav,four,4,2
45
- /FMA/092540.wav,three,3,6
46
- /FMA/005244.wav,four,4,2
47
- /GTZAN/jazz.00069.wav,four,4,2
48
- /FMA/117867.wav,three,3,6
49
- /FMA/072731.wav,three,3,6
50
- /MAG/00796.wav,three,3,6
51
- /FMA/004836.wav,four,4,2
52
- /GTZAN/rock.00040.wav,four,4,2
53
- /FMA/090584.wav,three,3,6
54
- /FMA/075200.wav,three,3,6
55
- /MAG/00090.wav,three,3,6
56
- /MAG/00720.wav,three,3,6
57
- /FMA/005002.wav,three,3,6
58
- /MAG/00037.wav,three,3,6
59
- /GTZAN/metal.00031.wav,four,4,2
60
- /GTZAN/disco.00085.wav,four,4,2
61
- /MAG/00098.wav,three,3,6
62
- /MAG/00529.wav,three,3,6
63
- /GTZAN/metal.00051.wav,four,4,2
64
- /MAG/00493.wav,three,3,6
65
- /GTZAN/blues.00079.wav,four,4,2
66
- /FMA/128476.wav,three,3,6
67
- /GTZAN/rock.00070.wav,three,3,6
68
- /GTZAN/disco.00013.wav,four,4,2
69
- /MAG/00833.wav,three,3,6
70
- /MAG/00029.wav,three,3,6
71
- /GTZAN/jazz.00050.wav,four,4,2
72
- /GTZAN/jazz.00012.wav,four,4,2
73
- /MAG/00607.wav,three,3,6
74
- /MAG/00021.wav,three,3,6
75
- /MAG/00011.wav,three,3,6
76
- /FMA/001153.wav,four,4,2
77
- /GTZAN/hiphop.00087.wav,four,4,2
78
- /FMA/045521.wav,three,3,6
79
- /GTZAN/hiphop.00021.wav,four,4,2
80
- /GTZAN/disco.00062.wav,four,4,2
81
- /GTZAN/reggae.00032.wav,four,4,2
82
- /GTZAN/metal.00089.wav,four,4,2
83
- /GTZAN/country.00051.wav,four,4,2
84
- /FMA/116873.wav,three,3,6
85
- /GTZAN/blues.00090.wav,four,4,2
86
- /FMA/073921.wav,three,3,6
87
- /FMA/006533.wav,four,4,2
88
- /GTZAN/disco.00059.wav,four,4,2
89
- /MAG/00912.wav,three,3,6
90
- /GTZAN/pop.00030.wav,four,4,2
91
- /FMA/004777.wav,four,4,2
92
- /FMA/001687.wav,four,4,2
93
- /MAG/00791.wav,three,3,6
94
- /FMA/003910.wav,four,4,2
95
- /FMA/071362.wav,three,3,6
96
- /GTZAN/disco.00075.wav,four,4,2
97
- /MAG/00805.wav,three,3,6
98
- /MAG/00107.wav,three,3,6
99
- /FMA/001162.wav,four,4,2
100
- /GTZAN/rock.00001.wav,four,4,2
101
- /GTZAN/blues.00092.wav,three,3,6
102
- /GTZAN/rock.00047.wav,four,4,2
103
- /GTZAN/reggae.00098.wav,four,4,2
104
- /GTZAN/hiphop.00097.wav,four,4,2
105
- /FMA/008259.wav,four,4,2
106
- /MAG/00601.wav,three,3,6
107
- /MAG/00016.wav,three,3,6
108
- /GTZAN/disco.00068.wav,four,4,2
109
- /GTZAN/blues.00005.wav,four,4,2
110
- /MAG/00154.wav,three,3,6
111
- /GTZAN/jazz.00027.wav,four,4,2
112
- /GTZAN/reggae.00064.wav,four,4,2
113
- /FMA/081944.wav,three,3,6
114
- /MAG/00698.wav,three,3,6
115
- /FMA/068226.wav,three,3,6
116
- /GTZAN/blues.00074.wav,four,4,2
117
- /MAG/00881.wav,three,3,6
118
- /FMA/108149.wav,three,3,6
119
- /MAG/0004.wav,three,3,6
120
- /GTZAN/country.00014.wav,four,4,2
121
- /FMA/148635.wav,three,3,6
122
- /MAG/00903.wav,three,3,6
123
- /MAG/00536.wav,three,3,6
124
- /GTZAN/metal.00052.wav,four,4,2
125
- /MAG/00569.wav,three,3,6
126
- /FMA/127054.wav,three,3,6
127
- /MAG/00735.wav,three,3,6
128
- /GTZAN/metal.00092.wav,four,4,2
129
- /FMA/127205.wav,three,3,6
130
- /GTZAN/country.00088.wav,four,4,2
131
- /GTZAN/disco.00098.wav,four,4,2
132
- /MAG/00687.wav,three,3,6
133
- /GTZAN/rock.00035.wav,four,4,2
134
- /MAG/00494.wav,three,3,6
135
- /GTZAN/disco.00079.wav,four,4,2
136
- /GTZAN/metal.00034.wav,four,4,2
137
- /GTZAN/disco.00069.wav,four,4,2
138
- /FMA/113698.wav,three,3,6
139
- /GTZAN/rock.00039.wav,four,4,2
140
- /FMA/097586.wav,three,3,6
141
- /GTZAN/disco.00044.wav,four,4,2
142
- /GTZAN/rock.00057.wav,four,4,2
143
- /FMA/143095.wav,three,3,6
144
- /GTZAN/reggae.00000.wav,four,4,2
145
- /FMA/007123.wav,four,4,2
146
- /GTZAN/rock.00023.wav,four,4,2
147
- /MAG/00168.wav,three,3,6
148
- /FMA/121720.wav,three,3,6
149
- /MAG/00848.wav,three,3,6
150
- /MAG/00040.wav,three,3,6
151
- /FMA/043457.wav,three,3,6
152
- /FMA/075706.wav,three,3,6
153
- /FMA/081153.wav,three,3,6
154
- /GTZAN/jazz.00011.wav,four,4,2
155
- /GTZAN/metal.00041.wav,four,4,2
156
- /MAG/00747.wav,three,3,6
157
- /GTZAN/metal.00088.wav,four,4,2
158
- /FMA/001126.wav,four,4,2
159
- /GTZAN/disco.00034.wav,four,4,2
160
- /GTZAN/blues.00067.wav,four,4,2
161
- /GTZAN/reggae.00093.wav,four,4,2
162
- /MAG/00711.wav,three,3,6
163
- /GTZAN/jazz.00040.wav,four,4,2
164
- /MAG/00043.wav,three,3,6
165
- /GTZAN/pop.00046.wav,four,4,2
166
- /GTZAN/blues.00047.wav,three,3,6
167
- /FMA/112313.wav,three,3,6
168
- /FMA/004785.wav,four,4,2
169
- /GTZAN/pop.00069.wav,four,4,2
170
- /FMA/133639.wav,three,3,6
171
- /GTZAN/jazz.00064.wav,four,4,2
172
- /GTZAN/classical.00058.wav,three,3,6
173
- /MAG/00554.wav,three,3,6
174
- /MAG/00670.wav,three,3,6
175
- /FMA/009798.wav,four,4,2
176
- /FMA/050621.wav,three,3,6
177
- /MAG/00142.wav,three,3,6
178
- /FMA/009558.wav,four,4,2
179
- /FMA/014589.wav,three,3,6
180
- /MAG/00719.wav,three,3,6
181
- /GTZAN/hiphop.00035.wav,four,4,2
182
- /MAG/00874.wav,three,3,6
183
- /GTZAN/country.00050.wav,four,4,2
184
- /GTZAN/disco.00041.wav,three,3,6
185
- /MAG/00846.wav,three,3,6
186
- /FMA/027548.wav,three,3,6
187
- /FMA/001161.wav,four,4,2
188
- /GTZAN/disco.00019.wav,four,4,2
189
- /MAG/00864.wav,three,3,6
190
- /GTZAN/metal.00037.wav,four,4,2
191
- /MAG/00842.wav,three,3,6
192
- /GTZAN/metal.00056.wav,four,4,2
193
- /MAG/00644.wav,three,3,6
194
- /FMA/009748.wav,four,4,2
195
- /GTZAN/country.00020.wav,four,4,2
196
- /MAG/00560.wav,three,3,6
197
- /GTZAN/metal.00081.wav,four,4,2
198
- /GTZAN/blues.00003.wav,four,4,2
199
- /MAG/00128.wav,three,3,6
200
- /MAG/00915.wav,three,3,6
201
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- /GTZAN/blues.00022.wav,four,4,2
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- /MAG/00700.wav,three,3,6
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- /FMA/050620.wav,three,3,6
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- /MAG/00630.wav,three,3,6
313
- /MAG/00245.wav,three,3,6
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- /GTZAN/reggae.00091.wav,four,4,2
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319
- /FMA/005241.wav,four,4,2
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- /MAG/00475.wav,three,3,6
321
- /GTZAN/country.00000.wav,four,4,2
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- /GTZAN/classical.00094.wav,three,3,6
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- /GTZAN/reggae.00038.wav,four,4,2
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- /FMA/001201.wav,four,4,2
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- /MAG/00780.wav,three,3,6
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- /MAG/00167.wav,three,3,6
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- /MAG/00817.wav,three,3,6
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- /GTZAN/metal.00069.wav,four,4,2
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- /GTZAN/rock.00088.wav,four,4,2
331
- /OWN/0002.wav,five,5,7
332
- /GTZAN/disco.00039.wav,four,4,2
333
- /MAG/00024.wav,three,3,6
334
- /OWN/0129.wav,seven,7,5
335
- /GTZAN/country.00092.wav,four,4,2
336
- /FMA/146701.wav,three,3,6
337
- /GTZAN/hiphop.00060.wav,four,4,2
338
- /OWN/0132.wav,seven,7,5
339
- /MAG/00605.wav,five,5,7
340
- /GTZAN/disco.00081.wav,four,4,2
341
- /MAG/00062.wav,five,5,7
342
- /GTZAN/classical.00095.wav,five,5,7
343
- /FMA/068221.wav,seven,7,5
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- /OWN/0102.wav,seven,7,5
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- /MAG/00750.wav,three,3,6
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- /GTZAN/jazz.00002.wav,four,4,2
347
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- /GTZAN/pop.00019.wav,four,4,2
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- /MAG/00097.wav,three,3,6
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- /FMA/062665.wav,seven,7,5
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- /FMA/026681.wav,five,5,7
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- /GTZAN/classical.00028.wav,three,3,6
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- /GTZAN/disco.00093.wav,four,4,2
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- /FMA/016436.wav,three,3,6
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- /GTZAN/pop.00078.wav,four,4,2
364
- /FMA/131938.wav,five,5,7
365
- /MAG/00875.wav,three,3,6
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- /MAG/00168.wav,three,3,6
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- /FMA/003535.wav,three,3,6
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- /GTZAN/blues.00068.wav,four,4,2
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- /GTZAN/blues.00034.wav,four,4,2
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- /GTZAN/disco.00009.wav,four,4,2
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- /FMA/005245.wav,four,4,2
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- /FMA/004688.wav,four,4,2
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- /MAG/00103.wav,three,3,6
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- /MAG/00106.wav,three,3,6
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- /GTZAN/rock.00062.wav,four,4,2
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- /FMA/044095.wav,three,3,6
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- /FMA/006607.wav,four,4,2
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- /MAG/00029.wav,three,3,6
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- /FMA/049029.wav,three,3,6
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- /FMA/008204.wav,four,4,2
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- {
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- "cells": [
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- {
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- "cell_type": "markdown",
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- "id": "ac18fe04-6056-4a82-9cf8-f530aca2559c",
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- "metadata": {},
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- "source": [
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- "How to Use Your pianistprogrammer/Meter2800 Dataset\n",
9
- "Since your dataset contains both metadata in CSVs and raw audio files, the datasets library can intelligently load them. The key is how you organize your README.md on Hugging Face (or how the load_dataset function infers it).\n",
10
- "\n",
11
- "1. Install Necessary Libraries\n",
12
- "First, make sure you have the datasets and pandas (for easier data handling if needed) libraries installed. Also, soundfile and librosa are often useful for audio processing, and ffmpeg is required by datasets to process audio files.\n",
13
- "\n",
14
- "pip install datasets pandas soundfile librosa\n",
15
- "# Ensure ffmpeg is installed on your system (see previous script for instructions)\n",
16
- "\n",
17
- "2. Loading the Dataset\n",
18
- "You can load your dataset using load_dataset. The data_files argument is crucial here to tell datasets which CSVs correspond to which splits. The audio files will be loaded alongside if they are correctly referenced in the CSVs and available in the same repository.\n"
19
- ]
20
- },
21
- {
22
- "cell_type": "code",
23
- "execution_count": null,
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- "id": "d2e55e10-0fe7-4645-a529-7ad0b52053d3",
25
- "metadata": {},
26
- "outputs": [],
27
- "source": [
28
- "from datasets import load_dataset, Audio\n",
29
- "import os\n",
30
- "import pandas as pd\n",
31
- "\n",
32
- "# Define the dataset name on Hugging Face Hub\n",
33
- "dataset_name = \"pianistprogrammer/Meter2800\"\n",
34
- "\n",
35
- "# Define the paths to your CSV files within the Hugging Face repository\n",
36
- "# Assuming your CSVs are at the root of your uploaded folder\n",
37
- "data_files = {\n",
38
- " 'train_4_classes': 'data_train_4_classes.csv',\n",
39
- " 'val_4_classes': 'data_val_4_classes.csv',\n",
40
- " 'test_4_classes': 'data_test_4_classes.csv',\n",
41
- " # Include your 2-class CSVs if you want to load them too\n",
42
- " 'train_2_classes': 'data_train_2_classes.csv',\n",
43
- " 'val_2_classes': 'data_val_2_classes.csv',\n",
44
- " 'test_2_classes': 'data_test_2_classes.csv',\n",
45
- "}\n",
46
- "\n",
47
- "try:\n",
48
- " # Load the dataset\n",
49
- " # The 'filename' column will be automatically treated as a path to an audio file\n",
50
- " # if the `Audio` feature type is specified.\n",
51
- " # The `data_dir` argument helps `datasets` locate the actual audio files\n",
52
- " # within the repository. Since your folders (GTZAN, MAG, OWN, FMA) are\n",
53
- " # in the root of the uploaded dataset, this should work.\n",
54
- " dataset = load_dataset(dataset_name, data_files=data_files, split='train_4_classes') # Example: load just one split first\n",
55
- "\n",
56
- " # To load all splits at once:\n",
57
- " # dataset_dict = load_dataset(dataset_name, data_files=data_files)\n",
58
- "\n",
59
- " print(f\"Dataset loaded successfully from {dataset_name}!\")\n",
60
- " print(dataset)\n",
61
- " print(f\"First example from 'train_4_classes':\")\n",
62
- " print(dataset[0])\n",
63
- "\n",
64
- " # Accessing an audio file - this will automatically load the audio data\n",
65
- " # The 'Audio' feature type handles the loading and provides sampling rate, array data.\n",
66
- " first_example = dataset[0]\n",
67
- " print(f\"\\nAudio path: {first_example['filename']}\")\n",
68
- " print(f\"Audio array (first 10 samples): {first_example['audio']['array'][:10]}\")\n",
69
- " print(f\"Sampling rate: {first_example['audio']['sampling_rate']}\")\n",
70
- "\n",
71
- " # Example of iterating through a dataset split\n",
72
- " # for i, example in enumerate(dataset):\n",
73
- " # if i >= 3: # Just process first 3 examples\n",
74
- " # break\n",
75
- " # print(f\"\\nExample {i+1}:\")\n",
76
- " # print(f\" Filename: {example['filename']}\")\n",
77
- " # print(f\" Label: {example['label']}\")\n",
78
- " # print(f\" Audio data shape: {example['audio']['array'].shape}\")\n",
79
- "\n",
80
- "except Exception as e:\n",
81
- " print(f\"Error loading dataset: {e}\")\n",
82
- " print(\"Please ensure your dataset is public or you're authenticated if it's private.\")\n",
83
- " print(\"Also, verify the structure of your CSV 'filename' column matches paths within the dataset repository (e.g., '/GTZAN/rock.00056.wav').\")\n",
84
- "\n",
85
- "# --- Combining splits (Optional) ---\n",
86
- "# If you want to work with a combined dataset (e.g., all 4-class data),\n",
87
- "# you can concatenate the splits after loading.\n",
88
- "# This requires loading all splits first.\n",
89
- "# try:\n",
90
- "# dataset_dict = load_dataset(dataset_name, data_files={\n",
91
- "# 'train': 'data_train_4_classes.csv',\n",
92
- "# 'validation': 'data_val_4_classes.csv',\n",
93
- "# 'test': 'data_test_4_classes.csv'\n",
94
- "# })\n",
95
- "# print(\"\\nLoaded dataset dictionary:\")\n",
96
- "# print(dataset_dict)\n",
97
- "\n",
98
- "# # To combine them into a single dataset for easier iteration\n",
99
- "# # combined_dataset = concatenate_datasets([dataset_dict['train'], dataset_dict['validation'], dataset_dict['test']])\n",
100
- "# # print(f\"\\nCombined dataset size: {len(combined_dataset)}\")\n",
101
- "# except Exception as e:\n",
102
- "# print(f\"Error loading multiple splits or combining them: {e}\")"
103
- ]
104
- }
105
- ],
106
- "metadata": {
107
- "kernelspec": {
108
- "display_name": "Python 3 (ipykernel)",
109
- "language": "python",
110
- "name": "python3"
111
- },
112
- "language_info": {
113
- "codemirror_mode": {
114
- "name": "ipython",
115
- "version": 3
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- },
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- "file_extension": ".py",
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- "mimetype": "text/x-python",
119
- "name": "python",
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- "nbconvert_exporter": "python",
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- "pygments_lexer": "ipython3",
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- "version": "3.11.9"
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- }
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- },
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- "nbformat": 4,
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- "nbformat_minor": 5
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- }