tf2 图片读取

加载库

import tensorflow as tf
import pathlib
import random
import numpy as np
import os
import tensorflow as tf
from tensorflow import keras
from tensorflow.keras import layers
import matplotlib.pyplot as plt
from tensorflow.keras.models import Sequential,Model
from tensorflow.keras.layers import UpSampling2D, Conv2D, Dense, BatchNormalization, LeakyReLU, Input,Reshape, MaxPooling2D, Flatten, AveragePooling2D, Conv2DTranspose
from tensorflow.keras.optimizers import Adam
from PIL import Image
import matplotlib.pyplot as plt
import os
import numpy as np
import time

以秒计，当前时间

time.time()

1624588112.5667021

读取图片路径

file_name="/content/drive/MyDrive/机器学习展示/data/"

读取1500张图片

def read_image_np(file_name):
  start_time=time.time()
  # 创建队列，存储url
  imgs_temp = os.listdir(file_name)
  imgs=imgs_temp[:1000]
  print(len(imgs))
  # 建立np数组，存储数据
  x_train = np.empty((imgs.__len__(), 28,28, 3), dtype='float32')
  for i,j in enumerate(imgs):
    if i%100==0:
      print(i)
    img = Image.open(file_name+j)
    img = img.resize((28,28))
    # 图片规整
    img_arr = np.asarray(img, dtype='float32')
    x_train[i, :, :, :] = img_arr/127.5 - 1.
  end_time=time.time()
  consume_time=end_time-start_time
  print(f"消耗时间为{consume_time}")
  return x_train

显示图片

def show_image(data):
    fig=plt.figure(figsize=(4,4))
    for i in range(data.shape[0]):
        plt.subplot(4,4,i+1)
        plt.imshow((data[i]))
        plt.axis('off')
    plt.show()

运行

data=read_image_np(file_name)
show_image(data[:15])

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Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers).
Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers).
Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers).


消耗时间为357.83406949043274


Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers).
Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers).
Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers).
Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers).
Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers).
Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers).
Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers).
Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers).
Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers).
Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers).
Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers).
Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers).