PS C:\Users\Pondsi\Downloads\temp\CHINESE-OCR-master> & C:/builds/anaconda/envs/tensorflow/python.exe c:/Users/Pondsi/Downloads/temp/CHINESE-OCR-master/demo.py
Using TensorFlow backend.
C:\builds\anaconda\envs\tensorflow\lib\site-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_qint8 = np.dtype([("qint8", np.int8, 1)])
C:\builds\anaconda\envs\tensorflow\lib\site-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_quint8 = np.dtype([("quint8", np.uint8, 1)])
C:\builds\anaconda\envs\tensorflow\lib\site-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_qint16 = np.dtype([("qint16", np.int16, 1)])
C:\builds\anaconda\envs\tensorflow\lib\site-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_quint16 = np.dtype([("quint16", np.uint16, 1)])
C:\builds\anaconda\envs\tensorflow\lib\site-packages\tensorflow\python\framework\dtypes.py:521: 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)])
C:\builds\anaconda\envs\tensorflow\lib\site-packages\tensorflow\python\framework\dtypes.py:526: 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)])
Tensor("Placeholder:0", shape=(?, ?, ?, 3), dtype=float32)
Tensor("conv5_3/conv5_3:0", shape=(?, ?, ?, 512), dtype=float32)
Tensor("rpn_conv/3x3/rpn_conv/3x3:0", shape=(?, ?, ?, 512), dtype=float32)
WARNING:tensorflow:From C:\builds\anaconda\envs\tensorflow\lib\site-packages\tensorflow\contrib\learn\python\learn\datasets\base.py:198: retry (from tensorflow.contrib.learn.python.learn.datasets.base) is deprecated and will be removed in a future version.
Instructions for updating:
Use the retry module or similar alternatives.
Tensor("lstm_o/Reshape_2:0", shape=(?, ?, ?, 512), dtype=float32)
Tensor("lstm_o/Reshape_2:0", shape=(?, ?, ?, 512), dtype=float32)
Tensor("rpn_cls_score/Reshape_1:0", shape=(?, ?, ?, 20), dtype=float32)
Tensor("rpn_cls_prob:0", shape=(?, ?, ?, ?), dtype=float32)
Tensor("Reshape_2:0", shape=(?, ?, ?, 20), dtype=float32)
Tensor("rpn_bbox_pred/Reshape_1:0", shape=(?, ?, ?, 40), dtype=float32)
Tensor("Placeholder_1:0", shape=(?, 3), dtype=float32)
2023-10-04 11:17:17.456323: I T:\src\github\tensorflow\tensorflow\core\platform\cpu_feature_guard.cc:140] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2
2023-10-04 11:17:17.611372: I T:\src\github\tensorflow\tensorflow\core\common_runtime\gpu\gpu_device.cc:1344] Found device 0 with properties:
name: NVIDIA GeForce RTX 3060 Laptop GPU major: 8 minor: 6 memoryClockRate(GHz): 1.702
pciBusID: 0000:01:00.0
totalMemory: 6.00GiB freeMemory: 5.01GiB
2023-10-04 11:17:17.611968: I T:\src\github\tensorflow\tensorflow\core\common_runtime\gpu\gpu_device.cc:1423] Adding visible gpu devices: 0
2023-10-04 11:17:18.040100: I T:\src\github\tensorflow\tensorflow\core\common_runtime\gpu\gpu_device.cc:911] Device interconnect StreamExecutor with strength 1 edge matrix:
2023-10-04 11:17:18.040344: I T:\src\github\tensorflow\tensorflow\core\common_runtime\gpu\gpu_device.cc:917] 0
2023-10-04 11:17:18.040582: I T:\src\github\tensorflow\tensorflow\core\common_runtime\gpu\gpu_device.cc:930] 0: N
2023-10-04 11:17:18.040833: I T:\src\github\tensorflow\tensorflow\core\common_runtime\gpu\gpu_device.cc:1041] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 4914 MB memory) -> physical GPU (device: 0, name: NVIDIA GeForce RTX 3060 Laptop GPU, pci bus id: 0000:01:00.0, compute capability: 8.6)
Tensor_name is : lstm_o/bidirectional_rnn/bw/lstm_cell/kernel
Tensor_name is : conv1_1/biases
Tensor_name is : conv3_1/biases
Tensor_name is : conv1_1/weights
Tensor_name is : conv1_2/biases
Tensor_name is : conv1_2/weights
Tensor_name is : conv2_1/weights
Tensor_name is : conv4_3/weights
Tensor_name is : conv2_1/biases
Tensor_name is : conv2_2/biases
Tensor_name is : conv2_2/weights
Tensor_name is : conv3_1/weights
Tensor_name is : conv3_2/biases
Tensor_name is : conv3_2/weights
Tensor_name is : conv3_3/biases
Tensor_name is : conv3_3/weights
Tensor_name is : conv4_1/biases
Tensor_name is : rpn_conv/3x3/biases
Tensor_name is : conv4_1/weights
Tensor_name is : conv4_2/biases
Tensor_name is : conv4_2/weights
Tensor_name is : conv4_3/biases
Tensor_name is : conv5_1/biases
Tensor_name is : conv5_1/weights
Tensor_name is : conv5_2/biases
Tensor_name is : conv5_2/weights
Tensor_name is : conv5_3/biases
Tensor_name is : conv5_3/weights
Tensor_name is : lstm_o/biases
Tensor_name is : lstm_o/bidirectional_rnn/bw/lstm_cell/bias
Tensor_name is : lstm_o/bidirectional_rnn/fw/lstm_cell/bias
Tensor_name is : lstm_o/bidirectional_rnn/fw/lstm_cell/kernel
Tensor_name is : lstm_o/weights
Tensor_name is : rpn_bbox_pred/weights
Tensor_name is : rpn_bbox_pred/biases
Tensor_name is : rpn_cls_score/biases
Tensor_name is : rpn_cls_score/weights
Tensor_name is : rpn_conv/3x3/weights
load vggnet done
2023-10-04 11:17:19.301524: I T:\src\github\tensorflow\tensorflow\core\common_runtime\gpu\gpu_device.cc:1423] Adding visible gpu devices: 0
2023-10-04 11:17:19.301815: I T:\src\github\tensorflow\tensorflow\core\common_runtime\gpu\gpu_device.cc:911] Device interconnect StreamExecutor with strength 1 edge matrix:
2023-10-04 11:17:19.302066: I T:\src\github\tensorflow\tensorflow\core\common_runtime\gpu\gpu_device.cc:917] 0
2023-10-04 11:17:19.302267: I T:\src\github\tensorflow\tensorflow\core\common_runtime\gpu\gpu_device.cc:930] 0: N
2023-10-04 11:17:19.302464: I T:\src\github\tensorflow\tensorflow\core\common_runtime\gpu\gpu_device.cc:1041] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 4914 MB memory) -> physical GPU (device: 0, name: NVIDIA GeForce RTX 3060 Laptop GPU, pci bus id: 0000:01:00.0, compute capability: 8.6)
The angel of this character is: 0
Rotate the array of this img!
2023-10-04 11:17:22.792416: W T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:219] Allocator (GPU_0_bfc) ran out of memory trying to allocate 2.83GiB. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available.
2023-10-04 11:17:22.792834: W T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:219] Allocator (GPU_0_bfc) ran out of memory trying to allocate 2.83GiB. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available.
2023-10-04 11:17:23.319220: E T:\src\github\tensorflow\tensorflow\stream_executor\cuda\cuda_blas.cc:654] failed to run cuBLAS routine cublasSgemm_v2: CUBLAS_STATUS_EXECUTION_FAILED
Traceback (most recent call last):
File "C:\builds\anaconda\envs\tensorflow\lib\site-packages\tensorflow\python\client\session.py", line 1327, in _do_call
return fn(*args)
File "C:\builds\anaconda\envs\tensorflow\lib\site-packages\tensorflow\python\client\session.py", line 1312, in _run_fn
options, feed_dict, fetch_list, target_list, run_metadata)
File "C:\builds\anaconda\envs\tensorflow\lib\site-packages\tensorflow\python\client\session.py", line 1420, in _call_tf_sessionrun
status, run_metadata)
File "C:\builds\anaconda\envs\tensorflow\lib\site-packages\tensorflow\python\framework\errors_impl.py", line 516, in exit
c_api.TF_GetCode(self.status.status))
tensorflow.python.framework.errors_impl.InternalError: Blas GEMM launch failed : a.shape=(5115, 256), b.shape=(256, 512), m=5115, n=512, k=256
[[Node: lstm_o/MatMul = MatMul[T=DT_FLOAT, transpose_a=false, transpose_b=false, _device="/job:localhost/replica:0/task:0/device:GPU:0"](lstm_o/Reshape_1, lstm_o/weights/read/_153)]]
[[Node: rpn_bbox_pred/Reshape_1/_165 = _Recv[client_terminated=false, recv_device="/job:localhost/replica:0/task:0/device:CPU:0", send_device="/job:localhost/replica:0/task:0/device:GPU:0", send_device_incarnation=1, tensor_name="edge_490_rpn_bbox_pred/Reshape_1", tensor_type=DT_FLOAT, _device="/job:localhost/replica:0/task:0/device:CPU:0"]()]]
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "c:/Users/Pondsi/Downloads/temp/CHINESE-OCR-master/demo.py", line 21, in
img, model='keras', adjust=True, detectAngle=True)
File "c:\Users\Pondsi\Downloads\temp\CHINESE-OCR-master\model.py", line 114, in model
text_recs, tmp, img=text_detect(img)
File "c:\Users\Pondsi\Downloads\temp\CHINESE-OCR-master\ctpn\text_detect.py", line 13, in text_detect
scores, boxes, img = ctpn(img)
File "c:\Users\Pondsi\Downloads\temp\CHINESE-OCR-master\ctpn\ctpn\model.py", line 63, in ctpn
scores, boxes = test_ctpn(sess, net, img)
File "c:\Users\Pondsi\Downloads\temp\CHINESE-OCR-master\ctpn\lib\fast_rcnn\test.py", line 76, in test_ctpn
rois = sess.run([net.get_output('rois')[0]], feed_dict=feed_dict)
File "C:\builds\anaconda\envs\tensorflow\lib\site-packages\tensorflow\python\client\session.py", line 905, in run
run_metadata_ptr)
File "C:\builds\anaconda\envs\tensorflow\lib\site-packages\tensorflow\python\client\session.py", line 1140, in _run
feed_dict_tensor, options, run_metadata)
File "C:\builds\anaconda\envs\tensorflow\lib\site-packages\tensorflow\python\client\session.py", line 1321, in _do_run
run_metadata)
File "C:\builds\anaconda\envs\tensorflow\lib\site-packages\tensorflow\python\client\session.py", line 1340, in _do_call
raise type(e)(node_def, op, message)
tensorflow.python.framework.errors_impl.InternalError: Blas GEMM launch failed : a.shape=(5115, 256), b.shape=(256, 512), m=5115, n=512, k=256
[[Node: lstm_o/MatMul = MatMul[T=DT_FLOAT, transpose_a=false, transpose_b=false, _device="/job:localhost/replica:0/task:0/device:GPU:0"](lstm_o/Reshape_1, lstm_o/weights/read/_153)]]
[[Node: rpn_bbox_pred/Reshape_1/_165 = _Recv[client_terminated=false, recv_device="/job:localhost/replica:0/task:0/device:CPU:0", send_device="/job:localhost/replica:0/task:0/device:GPU:0", send_device_incarnation=1, tensor_name="edge_490_rpn_bbox_pred/Reshape_1", tensor_type=DT_FLOAT, _device="/job:localhost/replica:0/task:0/device:CPU:0"]()]]
Caused by op 'lstm_o/MatMul', defined at:
File "c:/Users/Pondsi/Downloads/temp/CHINESE-OCR-master/demo.py", line 8, in
import model
File "", line 971, in _find_and_load
File "", line 955, in _find_and_load_unlocked
File "", line 665, in _load_unlocked
File "", line 678, in exec_module
File "", line 219, in _call_with_frames_removed
File "c:\Users\Pondsi\Downloads\temp\CHINESE-OCR-master\model.py", line 15, in
from ctpn.text_detect import text_detect
File "", line 971, in _find_and_load
File "", line 955, in _find_and_load_unlocked
File "", line 665, in _load_unlocked
File "", line 678, in exec_module
File "", line 219, in _call_with_frames_removed
File "c:\Users\Pondsi\Downloads\temp\CHINESE-OCR-master\ctpn\text_detect.py", line 4, in
from .ctpn.model import ctpn
File "", line 971, in _find_and_load
File "", line 955, in _find_and_load_unlocked
File "", line 665, in _load_unlocked
File "", line 678, in exec_module
File "", line 219, in _call_with_frames_removed
File "c:\Users\Pondsi\Downloads\temp\CHINESE-OCR-master\ctpn\ctpn\model.py", line 52, in
sess, saver, net = load_tf_model()
File "c:\Users\Pondsi\Downloads\temp\CHINESE-OCR-master\ctpn\ctpn\model.py", line 32, in load_tf_model
net = get_network("VGGnet_test")
File "c:\Users\Pondsi\Downloads\temp\CHINESE-OCR-master\ctpn\lib\networks\factory.py", line 9, in get_network
return VGGnet_test()
File "c:\Users\Pondsi\Downloads\temp\CHINESE-OCR-master\ctpn\lib\networks\VGGnet_test.py", line 23, in init
self.setup()
File "c:\Users\Pondsi\Downloads\temp\CHINESE-OCR-master\ctpn\lib\networks\VGGnet_test.py", line 52, in setup
(self.feed('rpn_conv/3x3').Bilstm(512, 128, 512, name='lstm_o'))
File "c:\Users\Pondsi\Downloads\temp\CHINESE-OCR-master\ctpn\lib\networks\network.py", line 24, in layer_decorated
layer_output = op(self, layer_input, *args, **kwargs)
File "c:\Users\Pondsi\Downloads\temp\CHINESE-OCR-master\ctpn\lib\networks\network.py", line 115, in Bilstm
outputs = tf.matmul(lstm_out, weights) + biases
File "C:\builds\anaconda\envs\tensorflow\lib\site-packages\tensorflow\python\ops\math_ops.py", line 2108, in matmul
a, b, transpose_a=transpose_a, transpose_b=transpose_b, name=name)
File "C:\builds\anaconda\envs\tensorflow\lib\site-packages\tensorflow\python\ops\gen_math_ops.py", line 4492, in mat_mul
name=name)
File "C:\builds\anaconda\envs\tensorflow\lib\site-packages\tensorflow\python\framework\op_def_library.py", line 787, in _apply_op_helper
op_def=op_def)
File "C:\builds\anaconda\envs\tensorflow\lib\site-packages\tensorflow\python\framework\ops.py", line 3290, in create_op
op_def=op_def)
File "C:\builds\anaconda\envs\tensorflow\lib\site-packages\tensorflow\python\framework\ops.py", line 1654, in init
self._traceback = self._graph._extract_stack() # pylint: disable=protected-access
PS C:\Users\Pondsi\Downloads\temp\CHINESE-OCR-master> & C:/builds/anaconda/envs/tensorflow/python.exe c:/Users/Pondsi/Downloads/temp/CHINESE-OCR-master/demo.py Using TensorFlow backend. C:\builds\anaconda\envs\tensorflow\lib\site-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_qint8 = np.dtype([("qint8", np.int8, 1)]) C:\builds\anaconda\envs\tensorflow\lib\site-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_quint8 = np.dtype([("quint8", np.uint8, 1)]) C:\builds\anaconda\envs\tensorflow\lib\site-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_qint16 = np.dtype([("qint16", np.int16, 1)]) C:\builds\anaconda\envs\tensorflow\lib\site-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_quint16 = np.dtype([("quint16", np.uint16, 1)]) C:\builds\anaconda\envs\tensorflow\lib\site-packages\tensorflow\python\framework\dtypes.py:521: 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)]) C:\builds\anaconda\envs\tensorflow\lib\site-packages\tensorflow\python\framework\dtypes.py:526: 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)]) Tensor("Placeholder:0", shape=(?, ?, ?, 3), dtype=float32) Tensor("conv5_3/conv5_3:0", shape=(?, ?, ?, 512), dtype=float32) Tensor("rpn_conv/3x3/rpn_conv/3x3:0", shape=(?, ?, ?, 512), dtype=float32) WARNING:tensorflow:From C:\builds\anaconda\envs\tensorflow\lib\site-packages\tensorflow\contrib\learn\python\learn\datasets\base.py:198: retry (from tensorflow.contrib.learn.python.learn.datasets.base) is deprecated and will be removed in a future version. Instructions for updating: Use the retry module or similar alternatives. Tensor("lstm_o/Reshape_2:0", shape=(?, ?, ?, 512), dtype=float32) Tensor("lstm_o/Reshape_2:0", shape=(?, ?, ?, 512), dtype=float32) Tensor("rpn_cls_score/Reshape_1:0", shape=(?, ?, ?, 20), dtype=float32) Tensor("rpn_cls_prob:0", shape=(?, ?, ?, ?), dtype=float32) Tensor("Reshape_2:0", shape=(?, ?, ?, 20), dtype=float32) Tensor("rpn_bbox_pred/Reshape_1:0", shape=(?, ?, ?, 40), dtype=float32) Tensor("Placeholder_1:0", shape=(?, 3), dtype=float32) 2023-10-04 11:17:17.456323: I T:\src\github\tensorflow\tensorflow\core\platform\cpu_feature_guard.cc:140] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 2023-10-04 11:17:17.611372: I T:\src\github\tensorflow\tensorflow\core\common_runtime\gpu\gpu_device.cc:1344] Found device 0 with properties: name: NVIDIA GeForce RTX 3060 Laptop GPU major: 8 minor: 6 memoryClockRate(GHz): 1.702 pciBusID: 0000:01:00.0 totalMemory: 6.00GiB freeMemory: 5.01GiB 2023-10-04 11:17:17.611968: I T:\src\github\tensorflow\tensorflow\core\common_runtime\gpu\gpu_device.cc:1423] Adding visible gpu devices: 0 2023-10-04 11:17:18.040100: I T:\src\github\tensorflow\tensorflow\core\common_runtime\gpu\gpu_device.cc:911] Device interconnect StreamExecutor with strength 1 edge matrix: 2023-10-04 11:17:18.040344: I T:\src\github\tensorflow\tensorflow\core\common_runtime\gpu\gpu_device.cc:917] 0 2023-10-04 11:17:18.040582: I T:\src\github\tensorflow\tensorflow\core\common_runtime\gpu\gpu_device.cc:930] 0: N 2023-10-04 11:17:18.040833: I T:\src\github\tensorflow\tensorflow\core\common_runtime\gpu\gpu_device.cc:1041] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 4914 MB memory) -> physical GPU (device: 0, name: NVIDIA GeForce RTX 3060 Laptop GPU, pci bus id: 0000:01:00.0, compute capability: 8.6) Tensor_name is : lstm_o/bidirectional_rnn/bw/lstm_cell/kernel Tensor_name is : conv1_1/biases Tensor_name is : conv3_1/biases Tensor_name is : conv1_1/weights Tensor_name is : conv1_2/biases Tensor_name is : conv1_2/weights Tensor_name is : conv2_1/weights Tensor_name is : conv4_3/weights Tensor_name is : conv2_1/biases Tensor_name is : conv2_2/biases Tensor_name is : conv2_2/weights Tensor_name is : conv3_1/weights Tensor_name is : conv3_2/biases Tensor_name is : conv3_2/weights Tensor_name is : conv3_3/biases Tensor_name is : conv3_3/weights Tensor_name is : conv4_1/biases Tensor_name is : rpn_conv/3x3/biases Tensor_name is : conv4_1/weights Tensor_name is : conv4_2/biases Tensor_name is : conv4_2/weights Tensor_name is : conv4_3/biases Tensor_name is : conv5_1/biases Tensor_name is : conv5_1/weights Tensor_name is : conv5_2/biases Tensor_name is : conv5_2/weights Tensor_name is : conv5_3/biases Tensor_name is : conv5_3/weights Tensor_name is : lstm_o/biases Tensor_name is : lstm_o/bidirectional_rnn/bw/lstm_cell/bias Tensor_name is : lstm_o/bidirectional_rnn/fw/lstm_cell/bias Tensor_name is : lstm_o/bidirectional_rnn/fw/lstm_cell/kernel Tensor_name is : lstm_o/weights Tensor_name is : rpn_bbox_pred/weights Tensor_name is : rpn_bbox_pred/biases Tensor_name is : rpn_cls_score/biases Tensor_name is : rpn_cls_score/weights Tensor_name is : rpn_conv/3x3/weights load vggnet done 2023-10-04 11:17:19.301524: I T:\src\github\tensorflow\tensorflow\core\common_runtime\gpu\gpu_device.cc:1423] Adding visible gpu devices: 0 2023-10-04 11:17:19.301815: I T:\src\github\tensorflow\tensorflow\core\common_runtime\gpu\gpu_device.cc:911] Device interconnect StreamExecutor with strength 1 edge matrix: 2023-10-04 11:17:19.302066: I T:\src\github\tensorflow\tensorflow\core\common_runtime\gpu\gpu_device.cc:917] 0 2023-10-04 11:17:19.302267: I T:\src\github\tensorflow\tensorflow\core\common_runtime\gpu\gpu_device.cc:930] 0: N 2023-10-04 11:17:19.302464: I T:\src\github\tensorflow\tensorflow\core\common_runtime\gpu\gpu_device.cc:1041] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 4914 MB memory) -> physical GPU (device: 0, name: NVIDIA GeForce RTX 3060 Laptop GPU, pci bus id: 0000:01:00.0, compute capability: 8.6) The angel of this character is: 0 Rotate the array of this img! 2023-10-04 11:17:22.792416: W T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:219] Allocator (GPU_0_bfc) ran out of memory trying to allocate 2.83GiB. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available. 2023-10-04 11:17:22.792834: W T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:219] Allocator (GPU_0_bfc) ran out of memory trying to allocate 2.83GiB. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available. 2023-10-04 11:17:23.319220: E T:\src\github\tensorflow\tensorflow\stream_executor\cuda\cuda_blas.cc:654] failed to run cuBLAS routine cublasSgemm_v2: CUBLAS_STATUS_EXECUTION_FAILED Traceback (most recent call last): File "C:\builds\anaconda\envs\tensorflow\lib\site-packages\tensorflow\python\client\session.py", line 1327, in _do_call return fn(*args) File "C:\builds\anaconda\envs\tensorflow\lib\site-packages\tensorflow\python\client\session.py", line 1312, in _run_fn options, feed_dict, fetch_list, target_list, run_metadata) File "C:\builds\anaconda\envs\tensorflow\lib\site-packages\tensorflow\python\client\session.py", line 1420, in _call_tf_sessionrun status, run_metadata) File "C:\builds\anaconda\envs\tensorflow\lib\site-packages\tensorflow\python\framework\errors_impl.py", line 516, in exit c_api.TF_GetCode(self.status.status)) tensorflow.python.framework.errors_impl.InternalError: Blas GEMM launch failed : a.shape=(5115, 256), b.shape=(256, 512), m=5115, n=512, k=256 [[Node: lstm_o/MatMul = MatMul[T=DT_FLOAT, transpose_a=false, transpose_b=false, _device="/job:localhost/replica:0/task:0/device:GPU:0"](lstm_o/Reshape_1, lstm_o/weights/read/_153)]] [[Node: rpn_bbox_pred/Reshape_1/_165 = _Recv[client_terminated=false, recv_device="/job:localhost/replica:0/task:0/device:CPU:0", send_device="/job:localhost/replica:0/task:0/device:GPU:0", send_device_incarnation=1, tensor_name="edge_490_rpn_bbox_pred/Reshape_1", tensor_type=DT_FLOAT, _device="/job:localhost/replica:0/task:0/device:CPU:0"]()]]
During handling of the above exception, another exception occurred:
Traceback (most recent call last): File "c:/Users/Pondsi/Downloads/temp/CHINESE-OCR-master/demo.py", line 21, in
img, model='keras', adjust=True, detectAngle=True)
File "c:\Users\Pondsi\Downloads\temp\CHINESE-OCR-master\model.py", line 114, in model
text_recs, tmp, img=text_detect(img)
File "c:\Users\Pondsi\Downloads\temp\CHINESE-OCR-master\ctpn\text_detect.py", line 13, in text_detect
scores, boxes, img = ctpn(img)
File "c:\Users\Pondsi\Downloads\temp\CHINESE-OCR-master\ctpn\ctpn\model.py", line 63, in ctpn
scores, boxes = test_ctpn(sess, net, img)
File "c:\Users\Pondsi\Downloads\temp\CHINESE-OCR-master\ctpn\lib\fast_rcnn\test.py", line 76, in test_ctpn
rois = sess.run([net.get_output('rois')[0]], feed_dict=feed_dict)
File "C:\builds\anaconda\envs\tensorflow\lib\site-packages\tensorflow\python\client\session.py", line 905, in run
run_metadata_ptr)
File "C:\builds\anaconda\envs\tensorflow\lib\site-packages\tensorflow\python\client\session.py", line 1140, in _run
feed_dict_tensor, options, run_metadata)
File "C:\builds\anaconda\envs\tensorflow\lib\site-packages\tensorflow\python\client\session.py", line 1321, in _do_run
run_metadata)
File "C:\builds\anaconda\envs\tensorflow\lib\site-packages\tensorflow\python\client\session.py", line 1340, in _do_call
raise type(e)(node_def, op, message)
tensorflow.python.framework.errors_impl.InternalError: Blas GEMM launch failed : a.shape=(5115, 256), b.shape=(256, 512), m=5115, n=512, k=256
[[Node: lstm_o/MatMul = MatMul[T=DT_FLOAT, transpose_a=false, transpose_b=false, _device="/job:localhost/replica:0/task:0/device:GPU:0"](lstm_o/Reshape_1, lstm_o/weights/read/_153)]]
[[Node: rpn_bbox_pred/Reshape_1/_165 = _Recv[client_terminated=false, recv_device="/job:localhost/replica:0/task:0/device:CPU:0", send_device="/job:localhost/replica:0/task:0/device:GPU:0", send_device_incarnation=1, tensor_name="edge_490_rpn_bbox_pred/Reshape_1", tensor_type=DT_FLOAT, _device="/job:localhost/replica:0/task:0/device:CPU:0"]()]]
Caused by op 'lstm_o/MatMul', defined at: File "c:/Users/Pondsi/Downloads/temp/CHINESE-OCR-master/demo.py", line 8, in
import model
File "", line 971, in _find_and_load
File "", line 955, in _find_and_load_unlocked
File "", line 665, in _load_unlocked
File "", line 678, in exec_module
File "", line 219, in _call_with_frames_removed
File "c:\Users\Pondsi\Downloads\temp\CHINESE-OCR-master\model.py", line 15, in
from ctpn.text_detect import text_detect
File "", line 971, in _find_and_load
File "", line 955, in _find_and_load_unlocked
File "", line 665, in _load_unlocked
File "", line 678, in exec_module
File "", line 219, in _call_with_frames_removed
File "c:\Users\Pondsi\Downloads\temp\CHINESE-OCR-master\ctpn\text_detect.py", line 4, in
from .ctpn.model import ctpn
File "", line 971, in _find_and_load
File "", line 955, in _find_and_load_unlocked
File "", line 665, in _load_unlocked
File "", line 678, in exec_module
File "", line 219, in _call_with_frames_removed
File "c:\Users\Pondsi\Downloads\temp\CHINESE-OCR-master\ctpn\ctpn\model.py", line 52, in
sess, saver, net = load_tf_model()
File "c:\Users\Pondsi\Downloads\temp\CHINESE-OCR-master\ctpn\ctpn\model.py", line 32, in load_tf_model
net = get_network("VGGnet_test")
File "c:\Users\Pondsi\Downloads\temp\CHINESE-OCR-master\ctpn\lib\networks\factory.py", line 9, in get_network
return VGGnet_test()
File "c:\Users\Pondsi\Downloads\temp\CHINESE-OCR-master\ctpn\lib\networks\VGGnet_test.py", line 23, in init
self.setup()
File "c:\Users\Pondsi\Downloads\temp\CHINESE-OCR-master\ctpn\lib\networks\VGGnet_test.py", line 52, in setup
(self.feed('rpn_conv/3x3').Bilstm(512, 128, 512, name='lstm_o'))
File "c:\Users\Pondsi\Downloads\temp\CHINESE-OCR-master\ctpn\lib\networks\network.py", line 24, in layer_decorated
layer_output = op(self, layer_input, *args, **kwargs)
File "c:\Users\Pondsi\Downloads\temp\CHINESE-OCR-master\ctpn\lib\networks\network.py", line 115, in Bilstm
outputs = tf.matmul(lstm_out, weights) + biases
File "C:\builds\anaconda\envs\tensorflow\lib\site-packages\tensorflow\python\ops\math_ops.py", line 2108, in matmul
a, b, transpose_a=transpose_a, transpose_b=transpose_b, name=name)
File "C:\builds\anaconda\envs\tensorflow\lib\site-packages\tensorflow\python\ops\gen_math_ops.py", line 4492, in mat_mul
name=name)
File "C:\builds\anaconda\envs\tensorflow\lib\site-packages\tensorflow\python\framework\op_def_library.py", line 787, in _apply_op_helper
op_def=op_def)
File "C:\builds\anaconda\envs\tensorflow\lib\site-packages\tensorflow\python\framework\ops.py", line 3290, in create_op
op_def=op_def)
File "C:\builds\anaconda\envs\tensorflow\lib\site-packages\tensorflow\python\framework\ops.py", line 1654, in init
self._traceback = self._graph._extract_stack() # pylint: disable=protected-access
InternalError (see above for traceback): Blas GEMM launch failed : a.shape=(5115, 256), b.shape=(256, 512), m=5115, n=512, k=256 [[Node: lstm_o/MatMul = MatMul[T=DT_FLOAT, transpose_a=false, transpose_b=false, _device="/job:localhost/replica:0/task:0/device:GPU:0"](lstm_o/Reshape_1, lstm_o/weights/read/_153)]] [[Node: rpn_bbox_pred/Reshape_1/_165 = _Recv[client_terminated=false, recv_device="/job:localhost/replica:0/task:0/device:CPU:0", send_device="/job:localhost/replica:0/task:0/device:GPU:0", send_device_incarnation=1, tensor_name="edge_490_rpn_bbox_pred/Reshape_1", tensor_type=DT_FLOAT, _device="/job:localhost/replica:0/task:0/device:CPU:0"]()]]