calamari-train --files data/*.png --batch_size=64
I installed calamari-ocr using pip. Got the following error
Found 181 files in the dataset
Loading Dataset: 100%|██████████████████████████████████████████████████████████████████████████████████████| 181/181 [00:00<00:00, 242.80it/s]
Text Preprocessing: 100%|█████████████████████████████████████████████████████████████████████████████████| 181/181 [00:00<00:00, 14412.59it/s]
Data Preprocessing: 100%|████████████████████████████████████████████████████████████████████████████████████| 181/181 [00:03<00:00, 56.37it/s]
CODEC: ['', ' ', "'", '-', '.', '1', '2', 'ء', 'آ', 'أ', 'ؤ', 'ئ', 'ا', 'ب', 'ة', 'ت', 'ث', 'ج', 'ح', 'خ', 'د', 'ذ', 'ر', 'ز', 'س', 'ش', 'ص', 'ض', 'ط', 'ظ', 'ع', 'غ', 'ف', 'ق', 'ك', 'ل', 'م', 'ن', 'ه', 'و', 'ى', 'ي', 'ً', 'َ']
/home/ubuntu/anaconda3/envs/python3/lib/python3.6/importlib/_bootstrap.py:219: RuntimeWarning: numpy.dtype size changed, may indicate binary incompatibility. Expected 96, got 88
return f(*args, **kwds)
2018-08-08 05:28:36.538017: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2018-08-08 05:28:36.622038: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:897] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2018-08-08 05:28:36.622469: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1392] Found device 0 with properties:
name: Tesla K80 major: 3 minor: 7 memoryClockRate(GHz): 0.8235
pciBusID: 0000:00:1e.0
totalMemory: 11.17GiB freeMemory: 11.10GiB
2018-08-08 05:28:36.622503: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1471] Adding visible gpu devices: 0
2018-08-08 05:28:36.912184: I tensorflow/core/common_runtime/gpu/gpu_device.cc:952] Device interconnect StreamExecutor with strength 1 edge matrix:
2018-08-08 05:28:36.912241: I tensorflow/core/common_runtime/gpu/gpu_device.cc:958] 0
2018-08-08 05:28:36.912255: I tensorflow/core/common_runtime/gpu/gpu_device.cc:971] 0: N
2018-08-08 05:28:36.912544: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1084] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 10761 MB memory) -> physical GPU (device: 0, name: Tesla K80, pci bus id: 0000:00:1e.0, compute capability: 3.7)
Using CUDNN LSTM backend on GPU
Using CUDNN LSTM backend on GPU
Traceback (most recent call last):
File "/home/ubuntu/anaconda3/envs/python3/bin/calamari-train", line 11, in <module>
sys.exit(main())
File "/home/ubuntu/anaconda3/envs/python3/lib/python3.6/site-packages/calamari_ocr/scripts/train.py", line 233, in main
run(args)
File "/home/ubuntu/anaconda3/envs/python3/lib/python3.6/site-packages/calamari_ocr/scripts/train.py", line 226, in run
trainer.train(progress_bar=not args.no_progress_bars)
File "/home/ubuntu/anaconda3/envs/python3/lib/python3.6/site-packages/calamari_ocr/ocr/trainer.py", line 163, in train
test_net = backend.create_net(restore=None, weights=self.weights, graph_type="test", batch_size=checkpoint_params.batch_size)
File "/home/ubuntu/anaconda3/envs/python3/lib/python3.6/site-packages/calamari_ocr/ocr/backends/tensorflow_backend/tensorflow_backend.py", line 26, in create_net
model = TensorflowModel(self.network_proto, self.graph, self.session, graph_type, batch_size, reuse_weights=not self.first_model)
File "/home/ubuntu/anaconda3/envs/python3/lib/python3.6/site-packages/calamari_ocr/ocr/backends/tensorflow_backend/tensorflow_model.py", line 44, in __init__
self.create_network(self.inputs, self.input_seq_len, self.dropout_rate, reuse_variables=reuse_weights)
File "/home/ubuntu/anaconda3/envs/python3/lib/python3.6/site-packages/calamari_ocr/ocr/backends/tensorflow_backend/tensorflow_model.py", line 162, in create_network
time_major_outputs = gpu_cudnn_lstm_backend(time_major_inputs, lstm_layers[0].hidden_nodes)
File "/home/ubuntu/anaconda3/envs/python3/lib/python3.6/site-packages/calamari_ocr/ocr/backends/tensorflow_backend/tensorflow_model.py", line 156, in gpu_cudnn_lstm_backend
time_major_outputs, (output_h, output_c) = rnn_lstm(time_major_inputs)
File "/home/ubuntu/anaconda3/envs/python3/lib/python3.6/site-packages/tensorflow/python/layers/base.py", line 329, in __call__
outputs = super(Layer, self).__call__(inputs, *args, **kwargs)
File "/home/ubuntu/anaconda3/envs/python3/lib/python3.6/site-packages/tensorflow/python/keras/engine/base_layer.py", line 696, in __call__
self.build(input_shapes)
File "/home/ubuntu/anaconda3/envs/python3/lib/python3.6/site-packages/tensorflow/contrib/cudnn_rnn/python/layers/cudnn_rnn.py", line 362, in build
initializer=opaque_params_t, validate_shape=False)
File "/home/ubuntu/anaconda3/envs/python3/lib/python3.6/site-packages/tensorflow/python/ops/variable_scope.py", line 1328, in get_variable
constraint=constraint)
File "/home/ubuntu/anaconda3/envs/python3/lib/python3.6/site-packages/tensorflow/python/ops/variable_scope.py", line 1090, in get_variable
constraint=constraint)
File "/home/ubuntu/anaconda3/envs/python3/lib/python3.6/site-packages/tensorflow/python/ops/variable_scope.py", line 427, in get_variable
return custom_getter(**custom_getter_kwargs)
File "/home/ubuntu/anaconda3/envs/python3/lib/python3.6/site-packages/tensorflow/contrib/cudnn_rnn/python/layers/cudnn_rnn.py", line 294, in _update_trainable_weights
variable = getter(*args, **kwargs)
File "/home/ubuntu/anaconda3/envs/python3/lib/python3.6/site-packages/tensorflow/python/ops/variable_scope.py", line 404, in _true_getter
use_resource=use_resource, constraint=constraint)
File "/home/ubuntu/anaconda3/envs/python3/lib/python3.6/site-packages/tensorflow/python/ops/variable_scope.py", line 761, in _get_single_variable
"reuse=tf.AUTO_REUSE in VarScope?" % name)
ValueError: Variable cudnn_lstm_1/opaque_kernel does not exist, or was not created with tf.get_variable(). Did you mean to set reuse=tf.AUTO_REUSE in VarScope?
time_major_outputs, (output_h, output_c) = rnn_lstm(time_major_inputs)