Keras:如何将predict_generator与ImageDataGenerator一起使用? [英] Keras: How to use predict_generator with ImageDataGenerator?

问题描述

我对Keras非常陌生.我训练了一个模型，并希望预测一些存储在子文件夹中的图像(例如用于训练).为了进行测试，我希望从7个类(子文件夹)中预测2张图像.下面的test_generator可以看到14张图像，但是我得到196个预测.错误在哪里?非常感谢！

I'm very new to Keras. I trained a model and would like to predict some images stored in subfolders (like for training). For testing, I want to predict 2 images from 7 classes (subfolders). The test_generator below sees 14 images, but I get 196 predictions. Where is the mistake? Thanks a lot!

test_datagen = ImageDataGenerator(rescale=1./255)

test_generator = test_datagen.flow_from_directory(
        test_dir,
        target_size=(200, 200),
        color_mode="rgb",
        shuffle = "false",
        class_mode='categorical')

filenames = test_generator.filenames
nb_samples = len(filenames)

predict = model.predict_generator(test_generator,nb_samples)

推荐答案

您可以将flow_from_directory中batch_size的值从默认值(batch_size=32)更改为batch_size=1.然后将predict_generator的steps设置为测试图像的总数.像这样:

You can change the value of batch_size in flow_from_directory from default value (which is batch_size=32 ) to batch_size=1. Then set the steps of predict_generator to the total number of your test images. Something like this:

test_datagen = ImageDataGenerator(rescale=1./255)

test_generator = test_datagen.flow_from_directory(
        test_dir,
        target_size=(200, 200),
        color_mode="rgb",
        shuffle = False,
        class_mode='categorical',
        batch_size=1)

filenames = test_generator.filenames
nb_samples = len(filenames)

predict = model.predict_generator(test_generator,steps = nb_samples)

这篇关于Keras:如何将predict_generator与ImageDataGenerator一起使用?的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！