keras对图像数据进行增强 | keras data augmentation


keras data augmentation




# import the necessary packages
from keras.preprocessing.image import ImageDataGenerator
from keras.preprocessing.image import img_to_array
from keras.preprocessing.image import load_img
import numpy as np
import argparse

from keras_util import *

construct the argument parse and parse the arguments

ap = argparse.ArgumentParser() ap.add_argument("-i", "--image", required=True, help="path to the input image") ap.add_argument("-o", "--output", required=True, help="path to output directory to store augmentation examples") ap.add_argument("-p", "--prefix", type=str, default="image", help="output filename prefix") args = vars(ap.parse_args())

load the input image, convert it to a NumPy array, and then

reshape it to have an extra dimension

print("[INFO] loading example image...") target_size = None #target_size=(224,224) image = load_img(args["image"], target_size=target_size) image = img_to_array(image) image = np.expand_dims(image, axis=0) # 1,h,w,c

construct the image generator for data augmentation then

initialize the total number of images generated thus far

preprocessing_function: The function will run after the image is resized and augmented.

The function should take one argument:

one image (Numpy tensor with rank 3),

and should output a Numpy tensor with the same shape.

for 1 image --->(424,640,3)--->aug---(424,640,3)--->preprocess_input--->(424,640,3)

for 1 image --->resize--->(224,224,3)--->aug---(224,224,3)--->preprocess_input--->(224,224,3)

aug = ImageDataGenerator(preprocessing_function=resnet.preprocess_input, rotation_range=30, width_shift_range=0.1, height_shift_range=0.1, shear_range=0.2, zoom_range=0.2, horizontal_flip=True, fill_mode="nearest") total = 0

construct the actual Python generator

print("[INFO] generating images...") imageGen = aug.flow(image, batch_size=1, save_to_dir=args["output"], save_prefix=args["prefix"], save_format="png")

next_image = next(imageGen) print(next_image.shape) print(next_image[0, :5,:5,0])

loop over examples from our image data augmentation generator

for image in imageGen: # increment our counter total += 1

# if we have reached 10 examples, break from the loop
if total == 10:


target_size = None:

1 image --->(424,640,3)--->aug--->(424,640,3)--->preprocess_input--->(424,640,3)

target_size = (224,224):

1 image --->resize--->(224,224,3)--->aug--->(224,224,3)--->preprocess_input--->(224,224,3)



  • 20190910: created.



全部评论: 0