Я пытаюсь запустить распознавание внимания в моделях тензорного потока https://github.com/tensorflow/models/tree/master/attention_ocr . Я могу найти сценарий для обучения и оценки набора данных FSNS, но у них нет кода для выполнения вывода на одном изображении. Я хочу протестировать его на своих изображениях и посмотреть, насколько хорошо он работает. Вот что я пробовал для части вывода, но получаю сообщение об ошибке «Попытка использовать неинициализированное значение AttentionOcr_v1/conv_tower_fn/INCE/InceptionV3/Conv2d_1a_3x3/weights»
dataset = common_flags.create_dataset(split_name=FLAGS.split_name)
model = common_flags.create_model(dataset.num_char_classes,
dataset.max_sequence_length,
1, dataset.null_code)
#images: A tensor of shape [batch_size, height, width, channels].
images_actual_data = Image.open("imagename.jpg").resize((600, 150))
#Increase dimension of data and make it 4D
images_actual_data = np.expand_dims(images_actual_data,axis=0)/255.0
slim.get_or_create_global_step()
master_checkpoint = "trained_files/attention_ocr_2017_05_17/model.ckpt-399731"
inception_checkpoint = "inception-v3_2016_08_28/inception_v3.ckpt"
#inference code
with tf.Session() as sess:
init_op = tf.initialize_all_variables()
sess.run(init_op)
images_placeholder = tf.placeholder(dtype=tf.float32,shape=(1,150,600,3))
endpoints = model.create_base(images_placeholder, labels_one_hot=None)
model.create_init_fn_to_restore(master_checkpoint, inception_checkpoint)
predictions = sess.run(endpoints.predicted_chars, feed_dict={images_placeholder: images_actual_data})
Вот выходной лог
DEBUG 2017-08-01 21:20:58.000825: model.py: 314 images: Tensor("Placeholder:0", shape=(1, 150, 600, 3), dtype=float32)
DEBUG 2017-08-01 21:20:58.000827: model.py: 319 Views=1 single view: Tensor("AttentionOcr_v1/split:0", shape=(1, 150, 600, 3), dtype=float32)
DEBUG 2017-08-01 21:20:58.000827: model.py: 186 Using final_endpoint=Mixed_5d
DEBUG 2017-08-01 21:20:59.000906: model.py: 325 Conv tower: Tensor("AttentionOcr_v1/conv_tower_fn/INCE/InceptionV3/Mixed_5d/concat:0", shape=(1, 16, 72, 288), dtype=float32)
DEBUG 2017-08-01 21:20:59.000909: model.py: 328 Pooled views: Tensor("AttentionOcr_v1/pool_views_fn/STCK/Reshape:0", shape=(1, 1152, 288), dtype=float32)
DEBUG 2017-08-01 21:20:59.000909: sequence_layers.py: 421 Use AttentionWithAutoregression as a layer class
DEBUG 2017-08-01 21:21:01.000588: model.py: 331 chars_logit: Tensor("AttentionOcr_v1/sequence_logit_fn/SQLR/concat:0", shape=(1, 37, 134), dtype=float32)
INFO 2017-08-01 21:21:01.000864: model.py: 511 Request to re-store 117 weights from trained_files/attention_ocr_2017_05_17/model.ckpt-399731
INFO 2017-08-01 21:21:02.000021: model.py: 511 Request to re-store 104 weights from inception-v3_2016_08_28/inception_v3.ckpt
Traceback (most recent call last):
File "/Users/sxa091/everything/example_projects/tf_projects/models/attention_ocr/python/eval_image.py", line 84, in <module>
app.run()
File "/usr/local/lib/python2.7/site-packages/tensorflow/python/platform/app.py", line 48, in run
_sys.exit(main(_sys.argv[:1] + flags_passthrough))
File "/Users/sxa091/everything/example_projects/tf_projects/models/attention_ocr/python/eval_image.py", line 80, in main
predictions = sess.run(endpoints.predicted_chars, feed_dict={images_placeholder: images_actual_data})
File "/usr/local/lib/python2.7/site-packages/tensorflow/python/client/session.py", line 778, in run
run_metadata_ptr)
File "/usr/local/lib/python2.7/site-packages/tensorflow/python/client/session.py", line 982, in _run
feed_dict_string, options, run_metadata)
File "/usr/local/lib/python2.7/site-packages/tensorflow/python/client/session.py", line 1032, in _do_run
target_list, options, run_metadata)
File "/usr/local/lib/python2.7/site-packages/tensorflow/python/client/session.py", line 1052, in _do_call
raise type(e)(node_def, op, message)
tensorflow.python.framework.errors_impl.FailedPreconditionError: Attempting to use uninitialized value AttentionOcr_v1/conv_tower_fn/INCE/InceptionV3/Conv2d_1a_3x3/weights
[[Node: AttentionOcr_v1/conv_tower_fn/INCE/InceptionV3/Conv2d_1a_3x3/weights/read = Identity[T=DT_FLOAT, _class=["loc:@AttentionOcr_v1/conv_tower_fn/INCE/InceptionV3/Conv2d_1a_3x3/weights"], _device="/job:localhost/replica:0/task:0/cpu:0"](AttentionOcr_v1/conv_tower_fn/INCE/InceptionV3/Conv2d_1a_3x3/weights)]]
