TensorFlow2.0 读取与展示

不念不忘少年蓝@ 2022-10-18 12:52 126阅读 0赞

###### 一.引入库 ######

import matplotlib as mpl
    import matplotlib.pyplot as plt
    import numpy as np
    import sklearn
    import pandas as pd
    import os
    import sys
    import time
    import tensorflow as tf
    
    # 查看相应版本信息
    print(tf.__version__)
    print(sys.version_info)
    for module in mpl, np, pd, sklearn, tf, tf.keras:
        print(module.__name__, module.__version__)

2.5.0
    sys.version_info(major=3, minor=7, micro=0, releaselevel='final', serial=0)
    matplotlib 3.0.2
    numpy 1.19.5
    pandas 0.23.4
    sklearn 0.20.2
    tensorflow 2.5.0
    tensorflow.keras 2.5.0

###### 二.导入数据集 ######

fashion_mnist = tf.keras.datasets.fashion_mnist

###### 三.训练集和测试集 拆分 ######

(x_train_all, y_train_all), (x_test, y_test) = fashion_mnist.load_data()
    
    # 训练集拆分为训练集和验证集
    x_valid, x_train = x_train_all[:5000], x_train_all[5000:]
    y_valid, y_train = y_train_all[:5000], y_train_all[5000:]
    print(x_valid.shape, y_valid.shape)
    print(x_train.shape, y_train.shape)
    print(x_test.shape, y_test.shape)

(5000, 28, 28) (5000,)
    (55000, 28, 28) (55000,)
    (10000, 28, 28) (10000,)

###### 四.展示图像 ######

# 显示单张图片
    def show_single_image(img_arr):
        # cmap 定义颜色图谱,默认rgb,本来就是黑白图片 用二进制(binary)显示就行
        plt.imshow(img_arr, cmap="binary")
        plt.show()
    
    
    show_single_image(x_train[0])
    
    
    # 显示多张图片
    def show_imgs(n_rows, n_cols, x_data, y_data, class_names):
        assert len(x_data) == len(y_data)
        assert n_rows * n_cols < len(x_data)
        plt.figure(figsize=(n_cols * 1.4, n_rows * 1.6))
        for row in range(n_rows):
            for col in range(n_cols):
                index = n_cols * row + col
                plt.subplot(n_rows, n_cols, index + 1)
                plt.imshow(x_data[index], cmap="binary", interpolation="nearest")
                # 关闭坐标系
                plt.axis("off")
                plt.title(class_names[y_data[index]])
        plt.show()
    
    
    class_names = ["T-shirt", "Trouser", "Pullover", "Dress", "Coat", "Sandal", "Shirt",
                   "Sneaker", "Bag", "Ankle boot"
                   ]
    show_imgs(3, 5, x_train, y_train, class_names)

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[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L0NvY2t0YWlsX3B5_size_16_color_FFFFFF_t_70 1]: /images/20221005/3b9ea65ef41643d68486332e3519274e.png