single_layer_network.py 文件源码

def predictions_for_tiles(test_images, model):
    """Batch predictions on the test image set, to avoid a memory spike."""
    npy_test_images = numpy.array([img_loc_tuple[0] for img_loc_tuple in test_images])
    test_images = npy_test_images.astype(numpy.float32)
    test_images = numpy.multiply(test_images, 1.0 / 255.0)

    all_predictions = []
    for x in range(0, len(test_images) - 100, 100):
        for p in model.predict(test_images[x:x + 100]):
            all_predictions.append(p)

    for p in model.predict(test_images[len(all_predictions):]):
        all_predictions.append(p)
    assert len(all_predictions) == len(test_images)

    return all_predictions