numpy 除法时的broadcasting

最新推荐文章于 2023-07-12 13:35:09 发布

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最新推荐文章于 2023-07-12 13:35:09 发布

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import numpy as np

bbox_xywh = np.array([5,4,3,2])
strides = np.array([8, 16, 32])
bbox_xywh_scaled = 1.0 * bbox_xywh[np.newaxis, :] / strides[:, np.newaxis]
print('***************************')
print(bbox_xywh[np.newaxis, :])
print(strides[:,np.newaxis])
print('bbox_xywh[np.newaxis, :].shape=',bbox_xywh[np.newaxis, :].shape)
print('strides[:,np.newaxis].shape=',strides[:,np.newaxis].shape)
print(bbox_xywh_scaled.shape)
print(bbox_xywh_scaled)