Created
May 3, 2022 23:25
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A simple working example of how to use compressed numpy storage for data such as point clouds and classes.
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'''https://numpy.org/doc/stable/reference/generated/numpy.savez_compressed.html#numpy.savez_compressed | |
''' | |
import numpy as np | |
import os | |
# number of points in the point cloud | |
num_points = 10 | |
# a random array that is in a typical xyz arrangement | |
points = np.random.rand(num_points, 3) | |
# a random 1d array representing classes for each point | |
classes = np.random.randint(low=0, high=3, size=(num_points,)) | |
# setting up a place to save and then read data | |
CURR_DIR = os.getcwd() | |
filename = 'gt_points.npz' # or pd_points | |
filepath = os.path.join(CURR_DIR, filename) | |
# use np to save a compressed file that can access each array by keyword | |
np.savez_compressed(filepath, points=points, classes=classes) | |
loaded = np.load(filepath) | |
# the loaded arrays are the same as they were originally stored | |
print(loaded['points'] == points) |
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