resized_image_tensor: The input node of the recognition graph.
bottleneck_tensor: The bottleneck output layer of the CNN graph.
"""
- (sess, bottleneck_input, ground_truth_input, evaluation_step,
- prediction) = build_eval_session(model_info, class_count)
-
test_bottlenecks, test_ground_truth, test_filenames = (
get_random_cached_bottlenecks(sess, image_lists, FLAGS.test_batch_size,
'testing', FLAGS.bottleneck_dir,
FLAGS.image_dir, jpeg_data_tensor,
decoded_image_tensor, resized_image_tensor,
bottleneck_tensor, FLAGS.architecture))
+
+ (sess, bottleneck_input, ground_truth_input, evaluation_step,
+ prediction) = build_eval_session(model_info, class_count)
+
test_accuracy, predictions = sess.run(
[evaluation_step, prediction],
feed_dict={