evaluate_model.py 文件源码

def test_images_generator(test_path):
    '''
    Creates a generator that pulls images from a test directory that contains
    shade vs sunny subdirectories.
    '''
    from keras.utils.np_utils import to_categorical
    from keras.preprocessing import image
    from keras.preprocessing.image import ImageDataGenerator
    from keras.applications.resnet50 import preprocess_input
    from sklearn.model_selection import train_test_split
    from image_utilities import load_images_from_directory, preprocess_input_resnet
    import numpy as np

    #load_images from from the train and val directories
    test_datagen = ImageDataGenerator(preprocessing_function=preprocess_input_resnet)
    test_generator = test_datagen.flow_from_directory(directory=test_path,
                                                target_size=[224, 224],
                                                batch_size=26,
                                                class_mode='categorical')

    return test_datagen, test_generator