lvjianjin / crnn Goto Github PK

when I have deployed by docker，I use the following command that docker run --name tfserving-crnn-gpu --hostname tfserving-crnn-gpu -tid --restart=on-failure:10 --runtime=nvidia -p 8500:8500 -p 8501:8501 --mount type=bind,source=/opt/my/ocr/crnn_by_tensorflow2.2.0/output,target=/opt/my/ocr/crnn_by_tensorflow2.2.0/models -e MODEL_NAME=crnn -t tensorflow/serving:2.0.0-gpu &
python3 client.py
it appears the following error,please help me:
/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/dtypes.py:516: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
_np_qint8 = np.dtype([("qint8", np.int8, 1)])
/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/dtypes.py:517: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
_np_quint8 = np.dtype([("quint8", np.uint8, 1)])
/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/dtypes.py:518: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
_np_qint16 = np.dtype([("qint16", np.int16, 1)])
/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/dtypes.py:519: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
_np_quint16 = np.dtype([("quint16", np.uint16, 1)])
/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/dtypes.py:520: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
_np_qint32 = np.dtype([("qint32", np.int32, 1)])
/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/dtypes.py:525: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
np_resource = np.dtype([("resource", np.ubyte, 1)])
/usr/local/lib/python3.6/dist-packages/tensorboard/compat/tensorflow_stub/dtypes.py:541: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
_np_qint8 = np.dtype([("qint8", np.int8, 1)])
/usr/local/lib/python3.6/dist-packages/tensorboard/compat/tensorflow_stub/dtypes.py:542: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
_np_quint8 = np.dtype([("quint8", np.uint8, 1)])
/usr/local/lib/python3.6/dist-packages/tensorboard/compat/tensorflow_stub/dtypes.py:543: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
_np_qint16 = np.dtype([("qint16", np.int16, 1)])
/usr/local/lib/python3.6/dist-packages/tensorboard/compat/tensorflow_stub/dtypes.py:544: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
_np_quint16 = np.dtype([("quint16", np.uint16, 1)])
/usr/local/lib/python3.6/dist-packages/tensorboard/compat/tensorflow_stub/dtypes.py:545: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
_np_qint32 = np.dtype([("qint32", np.int32, 1)])
/usr/local/lib/python3.6/dist-packages/tensorboard/compat/tensorflow_stub/dtypes.py:550: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
np_resource = np.dtype([("resource", np.ubyte, 1)])
2020-09-15 15:02:47.193376: I tensorflow/core/platform/cpu_feature_guard.cc:142] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2020-09-15 15:02:47.235547: I tensorflow/core/platform/profile_utils/cpu_utils.cc:94] CPU Frequency: 2095324999 Hz
2020-09-15 15:02:47.237191: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x485a590 executing computations on platform Host. Devices:
2020-09-15 15:02:47.237237: I tensorflow/compiler/xla/service/service.cc:175] StreamExecutor device (0): ,
Traceback (most recent call last):
File "/usr/local/lib/python3.6/dist-packages/urllib3/connection.py", line 159, in _new_conn
(self._dns_host, self.port), self.timeout, **extra_kw)
File "/usr/local/lib/python3.6/dist-packages/urllib3/util/connection.py", line 80, in create_connection
raise err
File "/usr/local/lib/python3.6/dist-packages/urllib3/util/connection.py", line 70, in create_connection
sock.connect(sa)
ConnectionRefusedError: [Errno 111] Connection refused

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "/usr/local/lib/python3.6/dist-packages/urllib3/connectionpool.py", line 600, in urlopen
chunked=chunked)
File "/usr/local/lib/python3.6/dist-packages/urllib3/connectionpool.py", line 354, in _make_request
conn.request(method, url, **httplib_request_kw)
File "/usr/lib/python3.6/http/client.py", line 1264, in request
self._send_request(method, url, body, headers, encode_chunked)
File "/usr/lib/python3.6/http/client.py", line 1310, in _send_request
self.endheaders(body, encode_chunked=encode_chunked)
File "/usr/lib/python3.6/http/client.py", line 1259, in endheaders
self._send_output(message_body, encode_chunked=encode_chunked)
File "/usr/lib/python3.6/http/client.py", line 1038, in _send_output
self.send(msg)
File "/usr/lib/python3.6/http/client.py", line 976, in send
self.connect()
File "/usr/local/lib/python3.6/dist-packages/urllib3/connection.py", line 181, in connect
conn = self._new_conn()
File "/usr/local/lib/python3.6/dist-packages/urllib3/connection.py", line 168, in _new_conn
self, "Failed to establish a new connection: %s" % e)
urllib3.exceptions.NewConnectionError: <urllib3.connection.HTTPConnection object at 0x7f6b30d78cc0>: Failed to establish a new connection: [Errno 111] Connection refused

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "/usr/local/lib/python3.6/dist-packages/requests/adapters.py", line 449, in send
timeout=timeout
File "/usr/local/lib/python3.6/dist-packages/urllib3/connectionpool.py", line 638, in urlopen
_stacktrace=sys.exc_info()[2])
File "/usr/local/lib/python3.6/dist-packages/urllib3/util/retry.py", line 399, in increment
raise MaxRetryError(_pool, url, error or ResponseError(cause))
urllib3.exceptions.MaxRetryError: HTTPConnectionPool(host='192.168.50.236', port=8500): Max retries exceeded with url: /v1/models/crnn:predict (Caused by NewConnectionError('<urllib3.connection.HTTPConnection object at 0x7f6b30d78cc0>: Failed to establish a new connection: [Errno 111] Connection refused',))

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "client.py", line 85, in
result = text_ocr(image_list)
File "client.py", line 56, in text_ocr
predictions = requests.post(url,data=data, headers=headers,timeout=50).json()
File "/usr/local/lib/python3.6/dist-packages/requests/api.py", line 116, in post
return request('post', url, data=data, json=json, **kwargs)
File "/usr/local/lib/python3.6/dist-packages/requests/api.py", line 60, in request
return session.request(method=method, url=url, **kwargs)
File "/usr/local/lib/python3.6/dist-packages/requests/sessions.py", line 533, in request
resp = self.send(prep, **send_kwargs)
File "/usr/local/lib/python3.6/dist-packages/requests/sessions.py", line 646, in send
r = adapter.send(request, **kwargs)
File "/usr/local/lib/python3.6/dist-packages/requests/adapters.py", line 516, in send
raise ConnectionError(e, request=request)
requests.exceptions.ConnectionError: HTTPConnectionPool(host='192.168.50.236', port=8500): Max retries exceeded with url: /v1/models/crnn:predict (Caused by NewConnectionError('<urllib3.connection.HTTPConnection object at 0x7f6b30d78cc0>: Failed to establish a new connection: [Errno 111] Connection refused',))

Hi, I got below error messages when I run train.ipynb, can you help to take a look>

model.fit(train_ds,

      epochs=20, 

      steps_per_epoch=train_steps_per_epoch,

      validation_data=val_ds,

      validation_steps=val_steps_per_epoch,

      initial_epoch=0,

      callbacks = callbacks)

TypeError Traceback (most recent call last)
in
5 validation_steps=val_steps_per_epoch,
6 initial_epoch=0,
----> 7 callbacks = callbacks)

~/anaconda3/envs/tensorflow2_p36/lib/python3.6/site-packages/tensorflow_core/python/keras/engine/training.py in fit(self, x, y, batch_size, epochs, verbose, callbacks, validation_split, validation_data, shuffle, class_weight, sample_weight, initial_epoch, steps_per_epoch, validation_steps, validation_freq, max_queue_size, workers, use_multiprocessing, **kwargs)
823 max_queue_size=max_queue_size,
824 workers=workers,
--> 825 use_multiprocessing=use_multiprocessing)
826
827 def evaluate(self,

~/anaconda3/envs/tensorflow2_p36/lib/python3.6/site-packages/tensorflow_core/python/keras/engine/training_v2.py in fit(self, model, x, y, batch_size, epochs, verbose, callbacks, validation_split, validation_data, shuffle, class_weight, sample_weight, initial_epoch, steps_per_epoch, validation_steps, validation_freq, max_queue_size, workers, use_multiprocessing, **kwargs)
233 max_queue_size=max_queue_size,
234 workers=workers,
--> 235 use_multiprocessing=use_multiprocessing)
236
237 total_samples = _get_total_number_of_samples(training_data_adapter)

~/anaconda3/envs/tensorflow2_p36/lib/python3.6/site-packages/tensorflow_core/python/keras/engine/training_v2.py in _process_training_inputs(model, x, y, batch_size, epochs, sample_weights, class_weights, steps_per_epoch, validation_split, validation_data, validation_steps, shuffle, distribution_strategy, max_queue_size, workers, use_multiprocessing)
591 max_queue_size=max_queue_size,
592 workers=workers,
--> 593 use_multiprocessing=use_multiprocessing)
594 val_adapter = None
595 if validation_data:

~/anaconda3/envs/tensorflow2_p36/lib/python3.6/site-packages/tensorflow_core/python/keras/engine/training_v2.py in _process_inputs(model, mode, x, y, batch_size, epochs, sample_weights, class_weights, shuffle, steps, distribution_strategy, max_queue_size, workers, use_multiprocessing)
704 max_queue_size=max_queue_size,
705 workers=workers,
--> 706 use_multiprocessing=use_multiprocessing)
707
708 return adapter

~/anaconda3/envs/tensorflow2_p36/lib/python3.6/site-packages/tensorflow_core/python/keras/engine/data_adapter.py in init(self, x, y, sample_weights, standardize_function, **kwargs)
700
701 if standardize_function is not None:
--> 702 x = standardize_function(x)
703
704 # Note that the dataset instance is immutable, its fine to reusing the user

~/anaconda3/envs/tensorflow2_p36/lib/python3.6/site-packages/tensorflow_core/python/keras/engine/training_v2.py in standardize_function(dataset)
658 model.sample_weight_mode = getattr(model, 'sample_weight_mode', None)
659
--> 660 standardize(dataset, extract_tensors_from_dataset=False)
661
662 # Then we map using only the tensor standardization portion.

~/anaconda3/envs/tensorflow2_p36/lib/python3.6/site-packages/tensorflow_core/python/keras/engine/training.py in _standardize_user_data(self, x, y, sample_weight, class_weight, batch_size, check_steps, steps_name, steps, validation_split, shuffle, extract_tensors_from_dataset)
2376 is_compile_called = False
2377 if not self._is_compiled and self.optimizer:
-> 2378 self._compile_from_inputs(all_inputs, y_input, x, y)
2379 is_compile_called = True
2380

~/anaconda3/envs/tensorflow2_p36/lib/python3.6/site-packages/tensorflow_core/python/keras/engine/training.py in _compile_from_inputs(self, all_inputs, target, orig_inputs, orig_target)
2634 sample_weight_mode=self.sample_weight_mode,
2635 run_eagerly=self.run_eagerly,
-> 2636 experimental_run_tf_function=self._experimental_run_tf_function)
2637
2638 # TODO(omalleyt): Consider changing to a more descriptive function name.

~/anaconda3/envs/tensorflow2_p36/lib/python3.6/site-packages/tensorflow_core/python/training/tracking/base.py in _method_wrapper(self, *args, **kwargs)
455 self._self_setattr_tracking = False # pylint: disable=protected-access
456 try:
--> 457 result = method(self, *args, **kwargs)
458 finally:
459 self._self_setattr_tracking = previous_value # pylint: disable=protected-access

~/anaconda3/envs/tensorflow2_p36/lib/python3.6/site-packages/tensorflow_core/python/keras/engine/training.py in compile(self, optimizer, loss, metrics, loss_weights, sample_weight_mode, weighted_metrics, target_tensors, distribute, **kwargs)
437 targets=self._targets,
438 skip_target_masks=self._prepare_skip_target_masks(),
--> 439 masks=self._prepare_output_masks())
440
441 # Prepare sample weight modes. List with the same length as model outputs.

~/anaconda3/envs/tensorflow2_p36/lib/python3.6/site-packages/tensorflow_core/python/keras/engine/training.py in _handle_metrics(self, outputs, targets, skip_target_masks, sample_weights, masks, return_weighted_metrics, return_weighted_and_unweighted_metrics)
2020 metric_results.extend(
2021 self._handle_per_output_metrics(self._per_output_metrics[i],
-> 2022 target, output, output_mask))
2023 if return_weighted_and_unweighted_metrics or return_weighted_metrics:
2024 metric_results.extend(

~/anaconda3/envs/tensorflow2_p36/lib/python3.6/site-packages/tensorflow_core/python/keras/engine/training.py in _handle_per_output_metrics(self, metrics_dict, y_true, y_pred, mask, weights)
1971 with K.name_scope(metric_name):
1972 metric_result = training_utils.call_metric_function(
-> 1973 metric_fn, y_true, y_pred, weights=weights, mask=mask)
1974 metric_results.append(metric_result)
1975 return metric_results

~/anaconda3/envs/tensorflow2_p36/lib/python3.6/site-packages/tensorflow_core/python/keras/engine/training_utils.py in call_metric_function(metric_fn, y_true, y_pred, weights, mask)
1153
1154 if y_pred is not None:
-> 1155 return metric_fn(y_true, y_pred, sample_weight=weights)
1156 # Mean metric only takes a single value.
1157 return metric_fn(y_true, sample_weight=weights)

~/anaconda3/envs/tensorflow2_p36/lib/python3.6/site-packages/tensorflow_core/python/keras/metrics.py in call(self, *args, **kwargs)
194 from tensorflow.python.keras.distribute import distributed_training_utils # pylint:disable=g-import-not-at-top
195 return distributed_training_utils.call_replica_local_fn(
--> 196 replica_local_fn, *args, **kwargs)
197
198 @Property

~/anaconda3/envs/tensorflow2_p36/lib/python3.6/site-packages/tensorflow_core/python/keras/distribute/distributed_training_utils.py in call_replica_local_fn(fn, *args, **kwargs)
1133 with strategy.scope():
1134 return strategy.extended.call_for_each_replica(fn, args, kwargs)
-> 1135 return fn(*args, **kwargs)
1136
1137

~/anaconda3/envs/tensorflow2_p36/lib/python3.6/site-packages/tensorflow_core/python/keras/metrics.py in replica_local_fn(*args, **kwargs)
177 def replica_local_fn(*args, **kwargs):
178 """Updates the state of the metric in a replica-local context."""
--> 179 update_op = self.update_state(*args, **kwargs) # pylint: disable=not-callable
180 with ops.control_dependencies([update_op]):
181 result_t = self.result() # pylint: disable=not-callable

~/anaconda3/envs/tensorflow2_p36/lib/python3.6/site-packages/tensorflow_core/python/keras/utils/metrics_utils.py in decorated(metric_obj, *args, **kwargs)
74
75 with tf_utils.graph_context_for_symbolic_tensors(*args, **kwargs):
---> 76 update_op = update_state_fn(*args, **kwargs)
77 if update_op is not None: # update_op will be None in eager execution.
78 metric_obj.add_update(update_op)

~/anaconda3/envs/tensorflow2_p36/lib/python3.6/site-packages/tensorflow_core/python/eager/def_function.py in call(self, *args, **kwds)
566 xla_context.Exit()
567 else:
--> 568 result = self._call(*args, **kwds)
569
570 if tracing_count == self._get_tracing_count():

~/anaconda3/envs/tensorflow2_p36/lib/python3.6/site-packages/tensorflow_core/python/eager/def_function.py in _call(self, *args, **kwds)
613 # This is the first call of call, so we have to initialize.
614 initializers = []
--> 615 self._initialize(args, kwds, add_initializers_to=initializers)
616 finally:
617 # At this point we know that the initialization is complete (or less

~/anaconda3/envs/tensorflow2_p36/lib/python3.6/site-packages/tensorflow_core/python/eager/def_function.py in _initialize(self, args, kwds, add_initializers_to)
495 self._concrete_stateful_fn = (
496 self._stateful_fn._get_concrete_function_internal_garbage_collected( # pylint: disable=protected-access
--> 497 *args, **kwds))
498
499 def invalid_creator_scope(*unused_args, **unused_kwds):

~/anaconda3/envs/tensorflow2_p36/lib/python3.6/site-packages/tensorflow_core/python/eager/function.py in _get_concrete_function_internal_garbage_collected(self, *args, **kwargs)
2387 args, kwargs = None, None
2388 with self._lock:
-> 2389 graph_function, _, _ = self._maybe_define_function(args, kwargs)
2390 return graph_function
2391

~/anaconda3/envs/tensorflow2_p36/lib/python3.6/site-packages/tensorflow_core/python/eager/function.py in _maybe_define_function(self, args, kwargs)
2701
2702 self._function_cache.missed.add(call_context_key)
-> 2703 graph_function = self._create_graph_function(args, kwargs)
2704 self._function_cache.primary[cache_key] = graph_function
2705 return graph_function, args, kwargs

~/anaconda3/envs/tensorflow2_p36/lib/python3.6/site-packages/tensorflow_core/python/eager/function.py in _create_graph_function(self, args, kwargs, override_flat_arg_shapes)
2591 arg_names=arg_names,
2592 override_flat_arg_shapes=override_flat_arg_shapes,
-> 2593 capture_by_value=self._capture_by_value),
2594 self._function_attributes,
2595 # Tell the ConcreteFunction to clean up its graph once it goes out of

~/anaconda3/envs/tensorflow2_p36/lib/python3.6/site-packages/tensorflow_core/python/framework/func_graph.py in func_graph_from_py_func(name, python_func, args, kwargs, signature, func_graph, autograph, autograph_options, add_control_dependencies, arg_names, op_return_value, collections, capture_by_value, override_flat_arg_shapes)
976 converted_func)
977
--> 978 func_outputs = python_func(*func_args, **func_kwargs)
979
980 # invariant: func_outputs contains only Tensors, CompositeTensors,

~/anaconda3/envs/tensorflow2_p36/lib/python3.6/site-packages/tensorflow_core/python/eager/def_function.py in wrapped_fn(*args, **kwds)
437 # wrapped allows AutoGraph to swap in a converted function. We give
438 # the function a weak reference to itself to avoid a reference cycle.
--> 439 return weak_wrapped_fn().wrapped(*args, **kwds)
440 weak_wrapped_fn = weakref.ref(wrapped_fn)
441

~/anaconda3/envs/tensorflow2_p36/lib/python3.6/site-packages/tensorflow_core/python/framework/func_graph.py in wrapper(*args, **kwargs)
966 except Exception as e: # pylint:disable=broad-except
967 if hasattr(e, "ag_error_metadata"):
--> 968 raise e.ag_error_metadata.to_exception(e)
969 else:
970 raise

TypeError: in converted code:

/home/ec2-user/SageMaker/crnn_by_tensorflow2.2.0/models/accuracy.py:24 update_state  *
    y_true = tf.sparse.reset_shape(y_true, [b, max_width])
/home/ec2-user/anaconda3/envs/tensorflow2_p36/lib/python3.6/site-packages/tensorflow_core/python/ops/sparse_ops.py:1827 sparse_reset_shape
    sp_input = _convert_to_sparse_tensor(sp_input)
/home/ec2-user/anaconda3/envs/tensorflow2_p36/lib/python3.6/site-packages/tensorflow_core/python/ops/sparse_ops.py:69 _convert_to_sparse_tensor
    raise TypeError("Input must be a SparseTensor.")

TypeError: Input must be a SparseTensor.

按照readme的步骤下载dataset并在config中更改了路径，但是执行训练语句时程序执行到检测完cuda就推出了

i want to convert keras to onnx from crnn_30.h5, but it show like this:

...
Tensorflow op [crnn/bidirectional/backward_lstm/PartitionedCall/ReverseV2: ReverseV2] is not supported
Tensorflow op [crnn/bidirectional/ReverseV2: ReverseV2] is not supported
Tensorflow op [crnn/bidirectional_1/backward_lstm_1/PartitionedCall/ReverseV2: ReverseV2] is not supported
Tensorflow op [crnn/bidirectional_1/ReverseV2: ReverseV2] is not supported
Unsupported ops: Counter({'ReverseV2': 4})

if you know something about it , plz tell me

您好，CTC不是需要设置最长字符数吗？
在models里没有找到相关配置，请问，您现在一行可以最多识别多少个字符。
以及，如何处理英文空格问题。
@lvjianjin 谢谢

您好，想问一个关于数据集的问题

https://github.com/lvjianjin/crnn#chinese-dataset，百度网盘中哪个数据是chainese-dataset，我应该下载哪一个数据

I download your crnn_30.h5 and crnn_15.h5 file from baidu pan, but there has some errors when convert to tflite model, why?

您好，我看到您这里提供的下载地址的训练数据很丰富。想请教下这些数据的来源是哪里呢？谢谢！

模型训练
将800万数据放进去训练，经过19个epoch的训练，在验证集上面的表现就已经接近72%了。代码可参照train.ipynb。

准确度要怎么提升？微信nlanguage

您好：
一般的num_classes 都是 字符数+1，1代表是blank。
那么这里的 NUM_CLASSES = len(chardic) + 3， 3又是代表什么呢？
多出的两个位置用来指代谁？