在 Tensorflow 中调整 MNIST 的大小 [英] Resize MNIST in Tensorflow

问题描述

我一直在研究 MNIST 数据集，以学习如何在我的深度学习课程中使用 Tensorflow 和 Python.

I have been working on MNIST dataset to learn how to use Tensorflow and Python for my deep learning course.

我想将 MNIST 的大小调整为 22 &22 使用tensorflow，那我训练它，但是我不会怎么办?

I want to resize MNIST as 22 & 22 using tensorflow, then I train it, but I do not how to do?

你能帮我吗?

推荐答案

TheRevanchist 的回答是正确的.但是，对于 mnist 数据集，首先需要对 mnist 数组进行整形，然后再将其发送到 tf.image.resize_images():

TheRevanchist's answer is correct. However, for the mnist dataset, you first need to reshape the mnist array before you send it to tf.image.resize_images():

import tensorflow as tf
import numpy as np
import cv2

mnist = tf.contrib.learn.datasets.load_dataset("mnist")

batch = mnist.train.next_batch(10)
X_batch = batch[0]
batch_tensor = tf.reshape(X_batch, [10, 28, 28, 1])
resized_images = tf.image.resize_images(batch_tensor, [22,22])

上面的代码取出一批 10 张 mnist 图像，并将它们从 28x28 图像重塑为 22x22 tensorflow 图像.

The code above takes out a batch of 10 mnist images and reshapes them from 28x28 images to 22x22 tensorflow images.

如果你想显示图像，你可以使用opencv和下面的代码.resized_images.eval() 将 tensorflow 图像转换为 numpy 数组！

If you want to display the images, you can use opencv and the code below. The resized_images.eval() converts the tensorflow image to a numpy array!

with tf.Session() as sess:
    numpy_imgs = resized_images.eval(session=sess) # mnist images converted to numpy array
    for i in range(10):
        cv2.namedWindow('Resized image #%d' % i, cv2.WINDOW_NORMAL)
        cv2.imshow('Resized image #%d' % i, numpy_imgs[i])
        cv2.waitKey(0)

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