test.py

from datasets.load import load_dataset
import matplotlib.pyplot as plt
import numpy as np


# load dataset
dataset = load_dataset("cgarciae/point-cloud-mnist")
dataset.set_format("np")


# get numpy arrays
X_train = dataset["train"]["points"]
y_train = dataset["train"]["label"]
X_test = dataset["test"]["points"]
y_test = dataset["test"]["label"]


# plot some training samples
figure = plt.figure(figsize=(10, 10))
for i in range(3):
    for j in range(3):
        k = 3 * i + j
        plt.subplot(3, 3, k + 1)
        idx = np.random.randint(0, len(X_train))

        plt.title(f"{y_train[idx]}")
        plt.scatter(X_train[idx, :, 0], X_train[idx, :, 1])

plt.show()