Error running oemer.ipynb in Colab #70
Comments
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I get errors in Colab as well - in fact, I tried on my own virtual environment and get the same errors. I've uploaded various different files, seems it's not related to what I upload. Here are the errors I get... `env: DEBIAN_FRONTEND=noninteractive with the cudnn frontend json: with the cudnn frontend json: |
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It's because onnxrutime could not find a proper execution provider for TPU. Adjust runtime to use GPU should be fine. |
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Thank you for pointing me to the runtime settings. I chose "v2-8 TPU" and the script is running for some time, throwing the following error (full trace attached below): File "/usr/local/lib/python3.11/dist-packages/oemer/build_system.py", line 299, in align_symbols
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Thanks for the repository and the insights on the challenges related to OMR. I wanted to do a quick test run with oemer on a simple score sheet but faced the followng issues in Colab:
Describe the bug
When executing the IPython Notebook script sample (https://colab.research.google.com/github/BreezeWhite/oemer/blob/main/colab.ipynb), the first two sections (Setup & Upload Image) complete just fine, but running the third section (Run Recognition) produces errors. Thank you for any hint on how to make the script run - I'm happy to provide more traces or infos if needed!
The Runtime type in Colab is set to "T4 GPU".
Remark: Running the command oemer with the -d flag results in the same errors being produced as listed below.
Input Image
Full Traceback
env: DEBIAN_FRONTEND=noninteractive
env: QT_QPA_PLATFORM=offscreen
2025-01-09 20:41:27 No checkpoint found in /usr/local/lib/python3.10/dist-packages/oemer/checkpoints/unet_big/model.onnx
2025-01-09 20:41:27 Downloading checkpoints (1/4)
1st_model.onnx: 100% 70767752/70767752
2025-01-09 20:41:39 Downloading checkpoints (2/4)
1st_weights.h5: 100% 70977288/70977288
2025-01-09 20:41:52 Downloading checkpoints (3/4)
2nd_model.onnx: 100% 38448467/38448467
2025-01-09 20:41:59 Downloading checkpoints (4/4)
2nd_weights.h5: 100% 38570576/38570576
2025-01-09 20:42:06 Extracting staffline and symbols
2025-01-09 20:42:07.350031226 [W:onnxruntime:, cuda_execution_provider.cc:2497 ConvTransposeNeedFallbackToCPU] Dropping the ConvTranspose node: ConvTranspose__19277 to CPU because it requires asymmetric padding which the CUDA EP currently does not support
2025-01-09 20:42:07.350064421 [W:onnxruntime:, cuda_execution_provider.cc:2629 GetCapability] CUDA kernel not supported. Fallback to CPU execution provider for Op type: ConvTranspose node name: ConvTranspose__19277
2025-01-09 20:42:07.350075380 [W:onnxruntime:, cuda_execution_provider.cc:2497 ConvTransposeNeedFallbackToCPU] Dropping the ConvTranspose node: model/conv2d_transpose_1/conv2d_transpose to CPU because it requires asymmetric padding which the CUDA EP currently does not support
2025-01-09 20:42:07.350081893 [W:onnxruntime:, cuda_execution_provider.cc:2629 GetCapability] CUDA kernel not supported. Fallback to CPU execution provider for Op type: ConvTranspose node name: model/conv2d_transpose_1/conv2d_transpose
2025-01-09 20:42:07.350263230 [W:onnxruntime:, cuda_execution_provider.cc:2497 ConvTransposeNeedFallbackToCPU] Dropping the ConvTranspose node: ConvTranspose__19295 to CPU because it requires asymmetric padding which the CUDA EP currently does not support
2025-01-09 20:42:07.350272523 [W:onnxruntime:, cuda_execution_provider.cc:2629 GetCapability] CUDA kernel not supported. Fallback to CPU execution provider for Op type: ConvTranspose node name: ConvTranspose__19295
2025-01-09 20:42:07.350572855 [W:onnxruntime:, cuda_execution_provider.cc:2497 ConvTransposeNeedFallbackToCPU] Dropping the ConvTranspose node: ConvTranspose__19313 to CPU because it requires asymmetric padding which the CUDA EP currently does not support
2025-01-09 20:42:07.350582717 [W:onnxruntime:, cuda_execution_provider.cc:2629 GetCapability] CUDA kernel not supported. Fallback to CPU execution provider for Op type: ConvTranspose node name: ConvTranspose__19313
2025-01-09 20:42:07.350756462 [W:onnxruntime:, cuda_execution_provider.cc:2497 ConvTransposeNeedFallbackToCPU] Dropping the ConvTranspose node: ConvTranspose__19323 to CPU because it requires asymmetric padding which the CUDA EP currently does not support
2025-01-09 20:42:07.350765492 [W:onnxruntime:, cuda_execution_provider.cc:2629 GetCapability] CUDA kernel not supported. Fallback to CPU execution provider for Op type: ConvTranspose node name: ConvTranspose__19323
2025-01-09 20:42:07.351041047 [W:onnxruntime:, cuda_execution_provider.cc:2497 ConvTransposeNeedFallbackToCPU] Dropping the ConvTranspose node: ConvTranspose__19341 to CPU because it requires asymmetric padding which the CUDA EP currently does not support
2025-01-09 20:42:07.351049384 [W:onnxruntime:, cuda_execution_provider.cc:2629 GetCapability] CUDA kernel not supported. Fallback to CPU execution provider for Op type: ConvTranspose node name: ConvTranspose__19341
2025-01-09 20:42:07.351221613 [W:onnxruntime:, cuda_execution_provider.cc:2497 ConvTransposeNeedFallbackToCPU] Dropping the ConvTranspose node: ConvTranspose__19351 to CPU because it requires asymmetric padding which the CUDA EP currently does not support
2025-01-09 20:42:07.351230544 [W:onnxruntime:, cuda_execution_provider.cc:2629 GetCapability] CUDA kernel not supported. Fallback to CPU execution provider for Op type: ConvTranspose node name: ConvTranspose__19351
2025-01-09 20:42:07.351509695 [W:onnxruntime:, cuda_execution_provider.cc:2497 ConvTransposeNeedFallbackToCPU] Dropping the ConvTranspose node: ConvTranspose__19365 to CPU because it requires asymmetric padding which the CUDA EP currently does not support
2025-01-09 20:42:07.351518135 [W:onnxruntime:, cuda_execution_provider.cc:2629 GetCapability] CUDA kernel not supported. Fallback to CPU execution provider for Op type: ConvTranspose node name: ConvTranspose__19365
2025-01-09 20:42:07.421736576 [W:onnxruntime:, transformer_memcpy.cc:74 ApplyImpl] 64 Memcpy nodes are added to the graph tf2onnx for CUDAExecutionProvider. It might have negative impact on performance (including unable to run CUDA graph). Set session_options.log_severity_level=1 to see the detail logs before this message.
1738 2115
2025-01-09 20:42:08.851978652 [E:onnxruntime:Default, cudnn_fe_call.cc:33 CudaErrString<cudnn_frontend::error_object>] No valid engine configs for ConvFwd_
2025-01-09 20:42:08.852205177 [E:onnxruntime:, sequential_executor.cc:516 ExecuteKernel] Non-zero status code returned while running Conv node. Name:'model/conv2d_1/BiasAdd' Status Message: Failed to initialize CUDNN Frontend/onnxruntime_src/onnxruntime/core/providers/cuda/cudnn_fe_call.cc:99 std::conditional_t<THRW, void, onnxruntime::common::Status> onnxruntime::CudaCall(ERRTYPE, const char*, const char*, SUCCTYPE, const char*, const char*, int) [with ERRTYPE = cudnn_frontend::error_object; bool THRW = true; SUCCTYPE = cudnn_frontend::error_code_t; std::conditional_t<THRW, void, common::Status> = void] /onnxruntime_src/onnxruntime/core/providers/cuda/cudnn_fe_call.cc:91 std::conditional_t<THRW, void, onnxruntime::common::Status> onnxruntime::CudaCall(ERRTYPE, const char*, const char*, SUCCTYPE, const char*, const char*, int) [with ERRTYPE = cudnn_frontend::error_object; bool THRW = true; SUCCTYPE = cudnn_frontend::error_code_t; std::conditional_t<THRW, void, common::Status> = void] CUDNN_FE failure 8: HEURISTIC_QUERY_FAILED ; GPU=0 ; hostname=4b05f8273301 ; file=/onnxruntime_src/onnxruntime/core/providers/cuda/nn/conv.cc ; line=225 ; expr=s_.cudnn_fe_graph->create_execution_plans({heur_mode});
with the cudnn frontend json:
{"context":{"compute_data_type":"FLOAT","intermediate_data_type":"FLOAT","io_data_type":"FLOAT","name":"","sm_count":-1},"cudnn_backend_version":"9.6.0","cudnn_frontend_version":10700,"json_version":"1.0","nodes":[{"compute_data_type":"FLOAT","dilation":[1,1],"inputs":{"W":"w","X":"x"},"math_mode":"CROSS_CORRELATION","name":"","outputs":{"Y":"::Y"},"post_padding":[1,1],"pre_padding":[0,0],"stride":[2,2],"tag":"CONV_FPROP"}],"tensors":{"::Y":{"data_type":"FLOAT","dim":[16,128,128,128],"is_pass_by_value":false,"is_virtual":false,"name":"::Y","pass_by_value":null,"reordering_type":"NONE","stride":[2097152,16384,128,1],"uid":3,"uid_assigned":true},"w":{"data_type":"FLOAT","dim":[128,128,3,3],"is_pass_by_value":false,"is_virtual":false,"name":"w","pass_by_value":null,"reordering_type":"NONE","stride":[1152,9,3,1],"uid":1,"uid_assigned":true},"x":{"data_type":"FLOAT","dim":[16,128,256,256],"is_pass_by_value":false,"is_virtual":false,"name":"x","pass_by_value":null,"reordering_type":"NONE","stride":[8388608,65536,256,1],"uid":2,"uid_assigned":true}}}
EP Error: [ONNXRuntimeError] : 11 : EP_FAIL : Non-zero status code returned while running Conv node. Name:'model/conv2d_1/BiasAdd' Status Message: Failed to initialize CUDNN Frontend/onnxruntime_src/onnxruntime/core/providers/cuda/cudnn_fe_call.cc:99 std::conditional_t<THRW, void, onnxruntime::common::Status> onnxruntime::CudaCall(ERRTYPE, const char*, const char*, SUCCTYPE, const char*, const char*, int) [with ERRTYPE = cudnn_frontend::error_object; bool THRW = true; SUCCTYPE = cudnn_frontend::error_code_t; std::conditional_t<THRW, void, common::Status> = void] /onnxruntime_src/onnxruntime/core/providers/cuda/cudnn_fe_call.cc:91 std::conditional_t<THRW, void, onnxruntime::common::Status> onnxruntime::CudaCall(ERRTYPE, const char*, const char*, SUCCTYPE, const char*, const char*, int) [with ERRTYPE = cudnn_frontend::error_object; bool THRW = true; SUCCTYPE = cudnn_frontend::error_code_t; std::conditional_t<THRW, void, common::Status> = void] CUDNN_FE failure 8: HEURISTIC_QUERY_FAILED ; GPU=0 ; hostname=4b05f8273301 ; file=/onnxruntime_src/onnxruntime/core/providers/cuda/nn/conv.cc ; line=225 ; expr=s_.cudnn_fe_graph->create_execution_plans({heur_mode});
with the cudnn frontend json:
{"context":{"compute_data_type":"FLOAT","intermediate_data_type":"FLOAT","io_data_type":"FLOAT","name":"","sm_count":-1},"cudnn_backend_version":"9.6.0","cudnn_frontend_version":10700,"json_version":"1.0","nodes":[{"compute_data_type":"FLOAT","dilation":[1,1],"inputs":{"W":"w","X":"x"},"math_mode":"CROSS_CORRELATION","name":"","outputs":{"Y":"::Y"},"post_padding":[1,1],"pre_padding":[0,0],"stride":[2,2],"tag":"CONV_FPROP"}],"tensors":{"::Y":{"data_type":"FLOAT","dim":[16,128,128,128],"is_pass_by_value":false,"is_virtual":false,"name":"::Y","pass_by_value":null,"reordering_type":"NONE","stride":[2097152,16384,128,1],"uid":3,"uid_assigned":true},"w":{"data_type":"FLOAT","dim":[128,128,3,3],"is_pass_by_value":false,"is_virtual":false,"name":"w","pass_by_value":null,"reordering_type":"NONE","stride":[1152,9,3,1],"uid":1,"uid_assigned":true},"x":{"data_type":"FLOAT","dim":[16,128,256,256],"is_pass_by_value":false,"is_virtual":false,"name":"x","pass_by_value":null,"reordering_type":"NONE","stride":[8388608,65536,256,1],"uid":2,"uid_assigned":true}}} using ['CUDAExecutionProvider', 'CPUExecutionProvider']
Falling back to ['CPUExecutionProvider'] and retrying.
2025-01-09 20:45:38 Extracting layers of different symbols
2025-01-09 20:45:38.973998837 [W:onnxruntime:, cuda_execution_provider.cc:2497 ConvTransposeNeedFallbackToCPU] Dropping the ConvTranspose node: ConvTranspose__2063 to CPU because it requires asymmetric padding which the CUDA EP currently does not support
2025-01-09 20:45:38.974028097 [W:onnxruntime:, cuda_execution_provider.cc:2629 GetCapability] CUDA kernel not supported. Fallback to CPU execution provider for Op type: ConvTranspose node name: ConvTranspose__2063
2025-01-09 20:45:38.975354978 [W:onnxruntime:, cuda_execution_provider.cc:2497 ConvTransposeNeedFallbackToCPU] Dropping the ConvTranspose node: ConvTranspose__2103 to CPU because it requires asymmetric padding which the CUDA EP currently does not support
2025-01-09 20:45:38.975367628 [W:onnxruntime:, cuda_execution_provider.cc:2629 GetCapability] CUDA kernel not supported. Fallback to CPU execution provider for Op type: ConvTranspose node name: ConvTranspose__2103
2025-01-09 20:45:38.976036069 [W:onnxruntime:, cuda_execution_provider.cc:2497 ConvTransposeNeedFallbackToCPU] Dropping the ConvTranspose node: ConvTranspose__2123 to CPU because it requires asymmetric padding which the CUDA EP currently does not support
2025-01-09 20:45:38.976046777 [W:onnxruntime:, cuda_execution_provider.cc:2629 GetCapability] CUDA kernel not supported. Fallback to CPU execution provider for Op type: ConvTranspose node name: ConvTranspose__2123
2025-01-09 20:45:39.043515209 [W:onnxruntime:, transformer_memcpy.cc:74 ApplyImpl] 56 Memcpy nodes are added to the graph tf2onnx for CUDAExecutionProvider. It might have negative impact on performance (including unable to run CUDA graph). Set session_options.log_severity_level=1 to see the detail logs before this message.
1738 2115
2025-01-09 20:45:39.308226700 [E:onnxruntime:Default, cudnn_fe_call.cc:33 CudaErrString<cudnn_frontend::error_object>] No valid engine configs for ConvFwd_
2025-01-09 20:45:39.308415107 [E:onnxruntime:, sequential_executor.cc:516 ExecuteKernel] Non-zero status code returned while running Conv node. Name:'model/conv2d/BiasAdd' Status Message: Failed to initialize CUDNN Frontend/onnxruntime_src/onnxruntime/core/providers/cuda/cudnn_fe_call.cc:99 std::conditional_t<THRW, void, onnxruntime::common::Status> onnxruntime::CudaCall(ERRTYPE, const char*, const char*, SUCCTYPE, const char*, const char*, int) [with ERRTYPE = cudnn_frontend::error_object; bool THRW = true; SUCCTYPE = cudnn_frontend::error_code_t; std::conditional_t<THRW, void, common::Status> = void] /onnxruntime_src/onnxruntime/core/providers/cuda/cudnn_fe_call.cc:91 std::conditional_t<THRW, void, onnxruntime::common::Status> onnxruntime::CudaCall(ERRTYPE, const char*, const char*, SUCCTYPE, const char*, const char*, int) [with ERRTYPE = cudnn_frontend::error_object; bool THRW = true; SUCCTYPE = cudnn_frontend::error_code_t; std::conditional_t<THRW, void, common::Status> = void] CUDNN_FE failure 8: HEURISTIC_QUERY_FAILED ; GPU=0 ; hostname=4b05f8273301 ; file=/onnxruntime_src/onnxruntime/core/providers/cuda/nn/conv.cc ; line=225 ; expr=s_.cudnn_fe_graph->create_execution_plans({heur_mode});
with the cudnn frontend json:
{"context":{"compute_data_type":"FLOAT","intermediate_data_type":"FLOAT","io_data_type":"FLOAT","name":"","sm_count":-1},"cudnn_backend_version":"9.6.0","cudnn_frontend_version":10700,"json_version":"1.0","nodes":[{"compute_data_type":"FLOAT","dilation":[1,1],"inputs":{"W":"w","X":"x"},"math_mode":"CROSS_CORRELATION","name":"","outputs":{"Y":"::Y"},"post_padding":[1,1],"pre_padding":[0,0],"stride":[2,2],"tag":"CONV_FPROP"}],"tensors":{"::Y":{"data_type":"FLOAT","dim":[16,64,144,144],"is_pass_by_value":false,"is_virtual":false,"name":"::Y","pass_by_value":null,"reordering_type":"NONE","stride":[1327104,20736,144,1],"uid":3,"uid_assigned":true},"w":{"data_type":"FLOAT","dim":[64,128,3,3],"is_pass_by_value":false,"is_virtual":false,"name":"w","pass_by_value":null,"reordering_type":"NONE","stride":[1152,9,3,1],"uid":1,"uid_assigned":true},"x":{"data_type":"FLOAT","dim":[16,128,288,288],"is_pass_by_value":false,"is_virtual":false,"name":"x","pass_by_value":null,"reordering_type":"NONE","stride":[10616832,82944,288,1],"uid":2,"uid_assigned":true}}}
EP Error: [ONNXRuntimeError] : 11 : EP_FAIL : Non-zero status code returned while running Conv node. Name:'model/conv2d/BiasAdd' Status Message: Failed to initialize CUDNN Frontend/onnxruntime_src/onnxruntime/core/providers/cuda/cudnn_fe_call.cc:99 std::conditional_t<THRW, void, onnxruntime::common::Status> onnxruntime::CudaCall(ERRTYPE, const char*, const char*, SUCCTYPE, const char*, const char*, int) [with ERRTYPE = cudnn_frontend::error_object; bool THRW = true; SUCCTYPE = cudnn_frontend::error_code_t; std::conditional_t<THRW, void, common::Status> = void] /onnxruntime_src/onnxruntime/core/providers/cuda/cudnn_fe_call.cc:91 std::conditional_t<THRW, void, onnxruntime::common::Status> onnxruntime::CudaCall(ERRTYPE, const char*, const char*, SUCCTYPE, const char*, const char*, int) [with ERRTYPE = cudnn_frontend::error_object; bool THRW = true; SUCCTYPE = cudnn_frontend::error_code_t; std::conditional_t<THRW, void, common::Status> = void] CUDNN_FE failure 8: HEURISTIC_QUERY_FAILED ; GPU=0 ; hostname=4b05f8273301 ; file=/onnxruntime_src/onnxruntime/core/providers/cuda/nn/conv.cc ; line=225 ; expr=s_.cudnn_fe_graph->create_execution_plans({heur_mode});
with the cudnn frontend json:
{"context":{"compute_data_type":"FLOAT","intermediate_data_type":"FLOAT","io_data_type":"FLOAT","name":"","sm_count":-1},"cudnn_backend_version":"9.6.0","cudnn_frontend_version":10700,"json_version":"1.0","nodes":[{"compute_data_type":"FLOAT","dilation":[1,1],"inputs":{"W":"w","X":"x"},"math_mode":"CROSS_CORRELATION","name":"","outputs":{"Y":"::Y"},"post_padding":[1,1],"pre_padding":[0,0],"stride":[2,2],"tag":"CONV_FPROP"}],"tensors":{"::Y":{"data_type":"FLOAT","dim":[16,64,144,144],"is_pass_by_value":false,"is_virtual":false,"name":"::Y","pass_by_value":null,"reordering_type":"NONE","stride":[1327104,20736,144,1],"uid":3,"uid_assigned":true},"w":{"data_type":"FLOAT","dim":[64,128,3,3],"is_pass_by_value":false,"is_virtual":false,"name":"w","pass_by_value":null,"reordering_type":"NONE","stride":[1152,9,3,1],"uid":1,"uid_assigned":true},"x":{"data_type":"FLOAT","dim":[16,128,288,288],"is_pass_by_value":false,"is_virtual":false,"name":"x","pass_by_value":null,"reordering_type":"NONE","stride":[10616832,82944,288,1],"uid":2,"uid_assigned":true}}} using ['CUDAExecutionProvider', 'CPUExecutionProvider']
Falling back to ['CPUExecutionProvider'] and retrying.
2025-01-09 20:53:04 Dewarping
2025-01-09 20:53:13 Extracting stafflines
99 298 5
299 498 10
499 698 10
699 898 10
899 1098 10
1099 1298 10
1299 1498 10
1499 1700 10
2025-01-09 20:53:15 Extracting noteheads
2025-01-09 20:53:15 Analyzing notehead bboxes
2025-01-09 20:53:16 Instanitiating notes
2025-01-09 20:53:17 Grouping noteheads
2025-01-09 20:53:21 Extracting symbols
/usr/local/lib/python3.10/dist-packages/sklearn/base.py:380: InconsistentVersionWarning: Trying to unpickle estimator SVC from version 1.2.0 when using version 1.6.0. This might lead to breaking code or invalid results. Use at your own risk. For more info please refer to:
https://scikit-learn.org/stable/model_persistence.html#security-maintainability-limitations
warnings.warn(
/usr/local/lib/python3.10/dist-packages/sklearn/base.py:380: InconsistentVersionWarning: Trying to unpickle estimator SVC from version 1.2.0 when using version 1.6.0. This might lead to breaking code or invalid results. Use at your own risk. For more info please refer to:
https://scikit-learn.org/stable/model_persistence.html#security-maintainability-limitations
warnings.warn(
/usr/local/lib/python3.10/dist-packages/sklearn/base.py:380: InconsistentVersionWarning: Trying to unpickle estimator SVC from version 1.2.0 when using version 1.6.0. This might lead to breaking code or invalid results. Use at your own risk. For more info please refer to:
https://scikit-learn.org/stable/model_persistence.html#security-maintainability-limitations
warnings.warn(
/usr/local/lib/python3.10/dist-packages/sklearn/base.py:380: InconsistentVersionWarning: Trying to unpickle estimator SVC from version 1.2.0 when using version 1.6.0. This might lead to breaking code or invalid results. Use at your own risk. For more info please refer to:
https://scikit-learn.org/stable/model_persistence.html#security-maintainability-limitations
warnings.warn(
/usr/local/lib/python3.10/dist-packages/sklearn/base.py:380: InconsistentVersionWarning: Trying to unpickle estimator SVC from version 1.2.0 when using version 1.6.0. This might lead to breaking code or invalid results. Use at your own risk. For more info please refer to:
https://scikit-learn.org/stable/model_persistence.html#security-maintainability-limitations
warnings.warn(
/usr/local/lib/python3.10/dist-packages/sklearn/base.py:380: InconsistentVersionWarning: Trying to unpickle estimator SVC from version 1.2.0 when using version 1.6.0. This might lead to breaking code or invalid results. Use at your own risk. For more info please refer to:
https://scikit-learn.org/stable/model_persistence.html#security-maintainability-limitations
warnings.warn(
/usr/local/lib/python3.10/dist-packages/sklearn/base.py:380: InconsistentVersionWarning: Trying to unpickle estimator SVC from version 1.2.0 when using version 1.6.0. This might lead to breaking code or invalid results. Use at your own risk. For more info please refer to:
https://scikit-learn.org/stable/model_persistence.html#security-maintainability-limitations
warnings.warn(
/usr/local/lib/python3.10/dist-packages/sklearn/base.py:380: InconsistentVersionWarning: Trying to unpickle estimator SVC from version 1.2.0 when using version 1.6.0. This might lead to breaking code or invalid results. Use at your own risk. For more info please refer to:
https://scikit-learn.org/stable/model_persistence.html#security-maintainability-limitations
warnings.warn(
/usr/local/lib/python3.10/dist-packages/sklearn/base.py:380: InconsistentVersionWarning: Trying to unpickle estimator SVC from version 1.2.0 when using version 1.6.0. This might lead to breaking code or invalid results. Use at your own risk. For more info please refer to:
https://scikit-learn.org/stable/model_persistence.html#security-maintainability-limitations
warnings.warn(
/usr/local/lib/python3.10/dist-packages/sklearn/base.py:380: InconsistentVersionWarning: Trying to unpickle estimator SVC from version 1.2.0 when using version 1.6.0. This might lead to breaking code or invalid results. Use at your own risk. For more info please refer to:
https://scikit-learn.org/stable/model_persistence.html#security-maintainability-limitations
warnings.warn(
/usr/local/lib/python3.10/dist-packages/sklearn/base.py:380: InconsistentVersionWarning: Trying to unpickle estimator SVC from version 1.2.0 when using version 1.6.0. This might lead to breaking code or invalid results. Use at your own risk. For more info please refer to:
https://scikit-learn.org/stable/model_persistence.html#security-maintainability-limitations
warnings.warn(
/usr/local/lib/python3.10/dist-packages/sklearn/base.py:380: InconsistentVersionWarning: Trying to unpickle estimator SVC from version 1.2.0 when using version 1.6.0. This might lead to breaking code or invalid results. Use at your own risk. For more info please refer to:
https://scikit-learn.org/stable/model_persistence.html#security-maintainability-limitations
warnings.warn(
/usr/local/lib/python3.10/dist-packages/sklearn/base.py:380: InconsistentVersionWarning: Trying to unpickle estimator SVC from version 1.2.0 when using version 1.6.0. This might lead to breaking code or invalid results. Use at your own risk. For more info please refer to:
https://scikit-learn.org/stable/model_persistence.html#security-maintainability-limitations
warnings.warn(
/usr/local/lib/python3.10/dist-packages/sklearn/base.py:380: InconsistentVersionWarning: Trying to unpickle estimator SVC from version 1.2.0 when using version 1.6.0. This might lead to breaking code or invalid results. Use at your own risk. For more info please refer to:
https://scikit-learn.org/stable/model_persistence.html#security-maintainability-limitations
warnings.warn(
/usr/local/lib/python3.10/dist-packages/sklearn/base.py:380: InconsistentVersionWarning: Trying to unpickle estimator SVC from version 1.2.0 when using version 1.6.0. This might lead to breaking code or invalid results. Use at your own risk. For more info please refer to:
https://scikit-learn.org/stable/model_persistence.html#security-maintainability-limitations
warnings.warn(
/usr/local/lib/python3.10/dist-packages/sklearn/base.py:380: InconsistentVersionWarning: Trying to unpickle estimator SVC from version 1.2.0 when using version 1.6.0. This might lead to breaking code or invalid results. Use at your own risk. For more info please refer to:
https://scikit-learn.org/stable/model_persistence.html#security-maintainability-limitations
warnings.warn(
/usr/local/lib/python3.10/dist-packages/sklearn/base.py:380: InconsistentVersionWarning: Trying to unpickle estimator SVC from version 1.2.0 when using version 1.6.0. This might lead to breaking code or invalid results. Use at your own risk. For more info please refer to:
https://scikit-learn.org/stable/model_persistence.html#security-maintainability-limitations
warnings.warn(
/usr/local/lib/python3.10/dist-packages/sklearn/base.py:380: InconsistentVersionWarning: Trying to unpickle estimator SVC from version 1.2.0 when using version 1.6.0. This might lead to breaking code or invalid results. Use at your own risk. For more info please refer to:
https://scikit-learn.org/stable/model_persistence.html#security-maintainability-limitations
warnings.warn(
/usr/local/lib/python3.10/dist-packages/sklearn/base.py:380: InconsistentVersionWarning: Trying to unpickle estimator SVC from version 1.2.0 when using version 1.6.0. This might lead to breaking code or invalid results. Use at your own risk. For more info please refer to:
https://scikit-learn.org/stable/model_persistence.html#security-maintainability-limitations
warnings.warn(
/usr/local/lib/python3.10/dist-packages/sklearn/base.py:380: InconsistentVersionWarning: Trying to unpickle estimator SVC from version 1.2.0 when using version 1.6.0. This might lead to breaking code or invalid results. Use at your own risk. For more info please refer to:
https://scikit-learn.org/stable/model_persistence.html#security-maintainability-limitations
warnings.warn(
/usr/local/lib/python3.10/dist-packages/sklearn/base.py:380: InconsistentVersionWarning: Trying to unpickle estimator SVC from version 1.2.0 when using version 1.6.0. This might lead to breaking code or invalid results. Use at your own risk. For more info please refer to:
https://scikit-learn.org/stable/model_persistence.html#security-maintainability-limitations
warnings.warn(
/usr/local/lib/python3.10/dist-packages/sklearn/base.py:380: InconsistentVersionWarning: Trying to unpickle estimator SVC from version 1.2.0 when using version 1.6.0. This might lead to breaking code or invalid results. Use at your own risk. For more info please refer to:
https://scikit-learn.org/stable/model_persistence.html#security-maintainability-limitations
warnings.warn(
/usr/local/lib/python3.10/dist-packages/sklearn/base.py:380: InconsistentVersionWarning: Trying to unpickle estimator SVC from version 1.2.0 when using version 1.6.0. This might lead to breaking code or invalid results. Use at your own risk. For more info please refer to:
https://scikit-learn.org/stable/model_persistence.html#security-maintainability-limitations
warnings.warn(
/usr/local/lib/python3.10/dist-packages/sklearn/base.py:380: InconsistentVersionWarning: Trying to unpickle estimator SVC from version 1.2.0 when using version 1.6.0. This might lead to breaking code or invalid results. Use at your own risk. For more info please refer to:
https://scikit-learn.org/stable/model_persistence.html#security-maintainability-limitations
warnings.warn(
/usr/local/lib/python3.10/dist-packages/sklearn/base.py:380: InconsistentVersionWarning: Trying to unpickle estimator SVC from version 1.2.0 when using version 1.6.0. This might lead to breaking code or invalid results. Use at your own risk. For more info please refer to:
https://scikit-learn.org/stable/model_persistence.html#security-maintainability-limitations
warnings.warn(
/usr/local/lib/python3.10/dist-packages/sklearn/base.py:380: InconsistentVersionWarning: Trying to unpickle estimator SVC from version 1.2.0 when using version 1.6.0. This might lead to breaking code or invalid results. Use at your own risk. For more info please refer to:
https://scikit-learn.org/stable/model_persistence.html#security-maintainability-limitations
warnings.warn(
/usr/local/lib/python3.10/dist-packages/sklearn/base.py:380: InconsistentVersionWarning: Trying to unpickle estimator SVC from version 1.2.0 when using version 1.6.0. This might lead to breaking code or invalid results. Use at your own risk. For more info please refer to:
https://scikit-learn.org/stable/model_persistence.html#security-maintainability-limitations
warnings.warn(
/usr/local/lib/python3.10/dist-packages/sklearn/base.py:380: InconsistentVersionWarning: Trying to unpickle estimator SVC from version 1.2.0 when using version 1.6.0. This might lead to breaking code or invalid results. Use at your own risk. For more info please refer to:
https://scikit-learn.org/stable/model_persistence.html#security-maintainability-limitations
warnings.warn(
/usr/local/lib/python3.10/dist-packages/sklearn/base.py:380: InconsistentVersionWarning: Trying to unpickle estimator SVC from version 1.2.0 when using version 1.6.0. This might lead to breaking code or invalid results. Use at your own risk. For more info please refer to:
https://scikit-learn.org/stable/model_persistence.html#security-maintainability-limitations
warnings.warn(
/usr/local/lib/python3.10/dist-packages/sklearn/base.py:380: InconsistentVersionWarning: Trying to unpickle estimator SVC from version 1.2.0 when using version 1.6.0. This might lead to breaking code or invalid results. Use at your own risk. For more info please refer to:
https://scikit-learn.org/stable/model_persistence.html#security-maintainability-limitations
warnings.warn(
/usr/local/lib/python3.10/dist-packages/sklearn/base.py:380: InconsistentVersionWarning: Trying to unpickle estimator SVC from version 1.2.0 when using version 1.6.0. This might lead to breaking code or invalid results. Use at your own risk. For more info please refer to:
https://scikit-learn.org/stable/model_persistence.html#security-maintainability-limitations
warnings.warn(
/usr/local/lib/python3.10/dist-packages/sklearn/base.py:380: InconsistentVersionWarning: Trying to unpickle estimator SVC from version 1.2.0 when using version 1.6.0. This might lead to breaking code or invalid results. Use at your own risk. For more info please refer to:
https://scikit-learn.org/stable/model_persistence.html#security-maintainability-limitations
warnings.warn(
/usr/local/lib/python3.10/dist-packages/sklearn/base.py:380: InconsistentVersionWarning: Trying to unpickle estimator SVC from version 1.2.0 when using version 1.6.0. This might lead to breaking code or invalid results. Use at your own risk. For more info please refer to:
https://scikit-learn.org/stable/model_persistence.html#security-maintainability-limitations
warnings.warn(
/usr/local/lib/python3.10/dist-packages/sklearn/base.py:380: InconsistentVersionWarning: Trying to unpickle estimator SVC from version 1.2.0 when using version 1.6.0. This might lead to breaking code or invalid results. Use at your own risk. For more info please refer to:
https://scikit-learn.org/stable/model_persistence.html#security-maintainability-limitations
warnings.warn(
/usr/local/lib/python3.10/dist-packages/sklearn/base.py:380: InconsistentVersionWarning: Trying to unpickle estimator SVC from version 1.2.0 when using version 1.6.0. This might lead to breaking code or invalid results. Use at your own risk. For more info please refer to:
https://scikit-learn.org/stable/model_persistence.html#security-maintainability-limitations
warnings.warn(
/usr/local/lib/python3.10/dist-packages/sklearn/base.py:380: InconsistentVersionWarning: Trying to unpickle estimator SVC from version 1.2.0 when using version 1.6.0. This might lead to breaking code or invalid results. Use at your own risk. For more info please refer to:
https://scikit-learn.org/stable/model_persistence.html#security-maintainability-limitations
warnings.warn(
/usr/local/lib/python3.10/dist-packages/sklearn/base.py:380: InconsistentVersionWarning: Trying to unpickle estimator SVC from version 1.2.0 when using version 1.6.0. This might lead to breaking code or invalid results. Use at your own risk. For more info please refer to:
https://scikit-learn.org/stable/model_persistence.html#security-maintainability-limitations
warnings.warn(
/usr/local/lib/python3.10/dist-packages/sklearn/base.py:380: InconsistentVersionWarning: Trying to unpickle estimator SVC from version 1.2.0 when using version 1.6.0. This might lead to breaking code or invalid results. Use at your own risk. For more info please refer to:
https://scikit-learn.org/stable/model_persistence.html#security-maintainability-limitations
warnings.warn(
2025-01-09 20:53:22 Extracting rhythm types
2025-01-09 20:53:30 Building MusicXML document
Traceback (most recent call last):
File "/usr/local/bin/oemer", line 8, in
sys.exit(main())
File "/usr/local/lib/python3.10/dist-packages/oemer/ete.py", line 287, in main
mxl_path = extract(args)
File "/usr/local/lib/python3.10/dist-packages/oemer/ete.py", line 215, in extract
builder.build()
File "/usr/local/lib/python3.10/dist-packages/oemer/build_system.py", line 574, in build
self.gen_measures(group_container)
File "/usr/local/lib/python3.10/dist-packages/oemer/build_system.py", line 680, in gen_measures
mm = gen_measure(buffer, grp, num, at_beginning, double_barline)
File "/usr/local/lib/python3.10/dist-packages/oemer/build_system.py", line 741, in gen_measure
mm.align_symbols()
File "/usr/local/lib/python3.10/dist-packages/oemer/build_system.py", line 299, in align_symbols
assert track_nums == 2, track_nums
AssertionError: 6
QStandardPaths: XDG_RUNTIME_DIR not set, defaulting to '/tmp/runtime-root'
convert <miserere.musicxml>...
File "miserere.musicxml" not found.
QStandardPaths: XDG_RUNTIME_DIR not set, defaulting to '/tmp/runtime-root'
convert <miserere.musicxml>...
File "miserere.musicxml" not found.
FileNotFoundError Traceback (most recent call last)
in <cell line: 14>()
12
13
---> 14 img = plt.imread(f"{basename}-1.png")
15 plt.rcParams['figure.figsize'] = (15, 15)
16 plt.axis('off')
2 frames
/usr/local/lib/python3.10/dist-packages/PIL/ImageFile.py in init(self, fp, filename)
130 if is_path(fp):
131 # filename
--> 132 self.fp = open(fp, "rb")
133 self.filename = os.fspath(fp)
134 self._exclusive_fp = True
FileNotFoundError: [Errno 2] No such file or directory: 'miserere-1.png'
Command You Execute
#@title Run Recoginition
%env DEBIAN_FRONTEND=noninteractive
%env QT_QPA_PLATFORM=offscreen
import IPython.display as dsp
!oemer "$img_path"
!musescore3 -o "${basename}.mp3" $basename.musicxml
!musescore3 -o "${basename}.png" $basename.musicxml
img = plt.imread(f"{basename}-1.png")
plt.rcParams['figure.figsize'] = (15, 15)
plt.axis('off')
plt.imshow(img)
plt.show()
dsp.display(dsp.Audio(f"{basename}.mp3"))
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