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95 lines
5.3 KiB
Python
95 lines
5.3 KiB
Python
import numpy as np
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import csv
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sample_rate = 32000
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clip_samples = sample_rate * 10 # Audio clips are 10-second
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# Load label
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with open('./audio_detection/audio_infer/metadata/class_labels_indices.csv', 'r') as f:
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reader = csv.reader(f, delimiter=',')
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lines = list(reader)
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labels = []
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ids = [] # Each label has a unique id such as "/m/068hy"
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for i1 in range(1, len(lines)):
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id = lines[i1][1]
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label = lines[i1][2]
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ids.append(id)
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labels.append(label)
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classes_num = len(labels)
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lb_to_ix = {label : i for i, label in enumerate(labels)}
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ix_to_lb = {i : label for i, label in enumerate(labels)}
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id_to_ix = {id : i for i, id in enumerate(ids)}
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ix_to_id = {i : id for i, id in enumerate(ids)}
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full_samples_per_class = np.array([
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937432, 16344, 7822, 10271, 2043, 14420, 733, 1511,
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1258, 424, 1751, 704, 369, 590, 1063, 1375,
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5026, 743, 853, 1648, 714, 1497, 1251, 2139,
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1093, 133, 224, 39469, 6423, 407, 1559, 4546,
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6826, 7464, 2468, 549, 4063, 334, 587, 238,
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1766, 691, 114, 2153, 236, 209, 421, 740,
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269, 959, 137, 4192, 485, 1515, 655, 274,
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69, 157, 1128, 807, 1022, 346, 98, 680,
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890, 352, 4169, 2061, 1753, 9883, 1339, 708,
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37857, 18504, 12864, 2475, 2182, 757, 3624, 677,
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1683, 3583, 444, 1780, 2364, 409, 4060, 3097,
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3143, 502, 723, 600, 230, 852, 1498, 1865,
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1879, 2429, 5498, 5430, 2139, 1761, 1051, 831,
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2401, 2258, 1672, 1711, 987, 646, 794, 25061,
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5792, 4256, 96, 8126, 2740, 752, 513, 554,
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106, 254, 1592, 556, 331, 615, 2841, 737,
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265, 1349, 358, 1731, 1115, 295, 1070, 972,
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174, 937780, 112337, 42509, 49200, 11415, 6092, 13851,
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2665, 1678, 13344, 2329, 1415, 2244, 1099, 5024,
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9872, 10948, 4409, 2732, 1211, 1289, 4807, 5136,
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1867, 16134, 14519, 3086, 19261, 6499, 4273, 2790,
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8820, 1228, 1575, 4420, 3685, 2019, 664, 324,
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513, 411, 436, 2997, 5162, 3806, 1389, 899,
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8088, 7004, 1105, 3633, 2621, 9753, 1082, 26854,
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3415, 4991, 2129, 5546, 4489, 2850, 1977, 1908,
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1719, 1106, 1049, 152, 136, 802, 488, 592,
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2081, 2712, 1665, 1128, 250, 544, 789, 2715,
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8063, 7056, 2267, 8034, 6092, 3815, 1833, 3277,
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8813, 2111, 4662, 2678, 2954, 5227, 1472, 2591,
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3714, 1974, 1795, 4680, 3751, 6585, 2109, 36617,
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6083, 16264, 17351, 3449, 5034, 3931, 2599, 4134,
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3892, 2334, 2211, 4516, 2766, 2862, 3422, 1788,
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2544, 2403, 2892, 4042, 3460, 1516, 1972, 1563,
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1579, 2776, 1647, 4535, 3921, 1261, 6074, 2922,
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3068, 1948, 4407, 712, 1294, 1019, 1572, 3764,
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5218, 975, 1539, 6376, 1606, 6091, 1138, 1169,
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7925, 3136, 1108, 2677, 2680, 1383, 3144, 2653,
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1986, 1800, 1308, 1344, 122231, 12977, 2552, 2678,
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7824, 768, 8587, 39503, 3474, 661, 430, 193,
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1405, 1442, 3588, 6280, 10515, 785, 710, 305,
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206, 4990, 5329, 3398, 1771, 3022, 6907, 1523,
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8588, 12203, 666, 2113, 7916, 434, 1636, 5185,
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1062, 664, 952, 3490, 2811, 2749, 2848, 15555,
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363, 117, 1494, 1647, 5886, 4021, 633, 1013,
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5951, 11343, 2324, 243, 372, 943, 734, 242,
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3161, 122, 127, 201, 1654, 768, 134, 1467,
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642, 1148, 2156, 1368, 1176, 302, 1909, 61,
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223, 1812, 287, 422, 311, 228, 748, 230,
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1876, 539, 1814, 737, 689, 1140, 591, 943,
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353, 289, 198, 490, 7938, 1841, 850, 457,
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814, 146, 551, 728, 1627, 620, 648, 1621,
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2731, 535, 88, 1736, 736, 328, 293, 3170,
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344, 384, 7640, 433, 215, 715, 626, 128,
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3059, 1833, 2069, 3732, 1640, 1508, 836, 567,
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2837, 1151, 2068, 695, 1494, 3173, 364, 88,
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188, 740, 677, 273, 1533, 821, 1091, 293,
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647, 318, 1202, 328, 532, 2847, 526, 721,
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370, 258, 956, 1269, 1641, 339, 1322, 4485,
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286, 1874, 277, 757, 1393, 1330, 380, 146,
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377, 394, 318, 339, 1477, 1886, 101, 1435,
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284, 1425, 686, 621, 221, 117, 87, 1340,
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201, 1243, 1222, 651, 1899, 421, 712, 1016,
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1279, 124, 351, 258, 7043, 368, 666, 162,
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7664, 137, 70159, 26179, 6321, 32236, 33320, 771,
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1169, 269, 1103, 444, 364, 2710, 121, 751,
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1609, 855, 1141, 2287, 1940, 3943, 289])
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