utils.py 文件源码

def _write_deepdream(images, layer, path_outdir, path_logdir):
    is_success = True

    images = _im_normlize([images])
    layer, units, k = layer
    # write into disk
    path_out = os.path.join(path_outdir, "deepdream_" + layer.lower().replace("/", "_"))
    is_success = make_dir(path_out)

    for i in range(len(images)):
        for j in range(images[i].shape[0]):
            img_save = images[i][j]
            if img_save.shape[2] == 1:
                img_save = np.squeeze(img_save, axis=2)
            imsave(os.path.join(path_out, "image_%d.png" % (units[(i * images[i].shape[0]) + j + k])), img_save, format = "png")

    # write into logfile
    path_log = os.path.join(path_logdir, layer.lower().replace("/", "_"))
    is_success = make_dir(path_log)

    with tf.Graph().as_default() as g:
        image = tf.placeholder(tf.float32, shape = [None, None, None, None])

        image_summary_t = tf.summary.image(name = "One_By_One_DeepDream", tensor = image, max_outputs = config["MAX_FEATUREMAP"])

        with tf.Session() as sess:
            summary = sess.run(image_summary_t, feed_dict = {image : np.concatenate(images, axis = 0)})
        try:
            file_writer = tf.summary.FileWriter(path_log, g) # create file writer
            # compute and write the summary
            file_writer.add_summary(summary)
        except:
            is_success = False
            print("Error occured in writting results into log file.")
        finally:
            file_writer.close() # close file writer
    return is_success