INNER CODE UNIT · Python
train_img
MITDeepLearning/introtodeeplearning · mitdeeplearning/lab2.py:90
train_img = (self.images[sorted_inds, :, :, ::-1] / 255.0).astype(np.float32)
train_label = self.labels[sorted_inds, ...]
if not self.channels_last:
train_img = np.ascontiguousarray(
np.transpose(train_img, (0, 3, 1, 2))
) # [B, H, W, C] -> [B, C, H, W]
return (
(train_img, train_label, sorted_inds)
if return_inds
else (train_img, train_label)
)
def get_n_most_prob_faces(self, prob, n):
idx = np.argsort(prob)[::-1]
most_prob_inds = self.pos_train_inds[idx[: 10 * n : 10]]
return (self.images[most_prob_inds, ...] / 255.0).astype(np.float32)