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yaohungt / Gated-Spatio-Temporal-Energy-Graph

[CVPR'19] [PyTorch] Gated Spatio Temporal Energy Graph
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charades_map/charades_nanmap #7

Closed pzhren closed 5 years ago

pzhren commented 5 years ago

https://github.com/wykang/Charades/blob/adc58b7cfe2567f17cc7b62caf4ff4a13a1e8f22/utils/map.py#L26 m_ap = np.mean(m_aps) m_ap = np.nanmean(m_aps) Are these two evaluation indicators the same?

yaohungt commented 5 years ago

See

https://docs.scipy.org/doc/numpy/reference/generated/numpy.nanmean.html

I think if there's no nan values, they are the same.

pzhren commented 5 years ago

See

https://docs.scipy.org/doc/numpy/reference/generated/numpy.nanmean.html

I think if there's no nan values, they are the same.

However, once nan appears in np.mean, the final result is nan, which does not get m_ap. In fact, a small batch on the charades data set is prone to the fact that the real label labels are all zero. Also, I counted the number of non-zero tags on class 157 of the charades dataset. How to deal with this.

Counted the number of non-zero tags on class 157 of the charades dataset： A = [] for i in range(157): a = np.sum(data[1][:,i]==1) A += [a]
A Out[56]: [613, 606, 452, 291, 258, 79, 612, 27, 781, 857, 46, 710, 200, 42, 239, 1043, 663, 217, 291, 217, 661, 351, 275, 272, 86, 186, 613, 275, 239, 91, 252, 58, 479, 567, 273, 280, 149, 125, 224, 95, 328, 177, 196, 177, 145, 34, 100, 255, 98, 91, 82, 344, 338, 228, 172, 153, 154, 190, 72, 1255, 46, 1048, 472, 646, 46, 453, 29, 397, 151, 160, 438, 201, 318, 199, 104, 137, 378, 171, 158, 160, 132, 470, 224, 72, 131, 28, 59, 219, 189, 52, 87, 39, 302, 94, 110, 37, 442, 1417, 361, 100, 125, 25, 235, 36, 205, 188, 1080, 972, 269, 464, 526, 47, 409, 584, 212, 316, 161, 168, 742, 428, 357, 106, 159, 480, 165, 393, 298, 464, 249, 152, 203, 46, 339, 95, 257, 312, 35, 208, 55, 81, 31, 496, 189, 243, 160, 236, 245, 316, 301, 584, 355, 951, 1011, 633, 1326, 366, 927]