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About random sampling in eval_7andN #32
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Hi @mystorm16 , thanks for your impressive and practical work! When I read your code, I have some question about the following code in eval_7andN.py:
# If number of points exceeds threshold, sample by points
if pts_all_masked.shape[0] > 999999:
sample_indices = np.random.choice(
pts_all_masked.shape[0], 999999, replace=False
)
pts_all_masked = pts_all_masked[sample_indices]
images_all_masked = images_all_masked[sample_indices]
# Apply the same sampling to GT point cloud
if pts_gt_all_masked.shape[0] > 999999:
sample_indices_gt = np.random.choice(
pts_gt_all_masked.shape[0], 999999, replace=False
)
pts_gt_all_masked = pts_gt_
all_masked[sample_indices_gt]
Why do you do a random sampling here which uses different indices to select pts_gt_all_masked and pts_all_masked?
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