Error while running SDMGR

[AnoZee]

Reproduction

python demo/image_demo.py demo/0.jpeg configs/kie/sdmgr/sdmgr_unet16_60e_wildreceipt.py model_weights/tr_weights/sdmgr_unet16_60e_wildreceipt_20210405-16a47642.pth demo/image_recog_results/SDMGR/0_sdmgr_vt.jpg

No modifications were made to the config.

Environment

sys.platform: linux Python: 3.7.10 (default, Feb 26 2021, 18:47:35) [GCC 7.3.0] CUDA available: True GPU 0: Tesla K80 CUDA_HOME: /usr/local/cuda NVCC: Cuda compilation tools, release 10.0, V10.0.130 GCC: gcc (Ubuntu 5.4.0-6ubuntu1~16.04.12) 5.4.0 20160609 PyTorch: 1.5.0 PyTorch compiling details: PyTorch built with:

• GCC 7.3
• C++ Version: 201402
• Intel(R) Math Kernel Library Version 2020.0.2 Product Build 20200624 for Intel(R) 64 architecture applications
• Intel(R) MKL-DNN v0.21.1 (Git Hash 7d2fd500bc78936d1d648ca713b901012f470dbc)
• OpenMP 201511 (a.k.a. OpenMP 4.5)
• NNPACK is enabled
• CPU capability usage: AVX2
• CUDA Runtime 10.1
• NVCC architecture flags: -gencode;arch=compute_37,code=sm_37;-gencode;arch=compute_50,code=sm_50;-gencode;arch=compute_60,code=sm_60;-gencode;arch=compute_61,code=sm_61;-gencode;arch=compute_70,code=sm_70;-gencode;arch=compute_75,code=sm_75;-gencode;arch=compute_37,code=compute_37
• CuDNN 7.6.3
• Magma 2.5.2
• Build settings: BLAS=MKL, BUILD_TYPE=Release, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -fopenmp -DNDEBUG -DUSE_FBGEMM -DUSE_QNNPACK -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DUSE_INTERNAL_THREADPOOL_IMPL -O2 -fPIC -Wno-narrowing -Wall -Wextra -Werror=return-type -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-sign-compare -Wno-unused-parameter -Wno-unused-variable -Wno-unused-function -Wno-unused-result -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Wno-stringop-overflow, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, USE_CUDA=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=ON, USE_MKLDNN=ON, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=ON, USE_OPENMP=ON, USE_STATIC_DISPATCH=OFF,

TorchVision: 0.6.0a0+82fd1c8 OpenCV: 4.5.1 MMCV: 1.2.6 MMCV Compiler: GCC 7.3 MMCV CUDA Compiler: 10.1 MMOCR: 0.1.0+5244984

All installation steps were followed as per the documentation.

Error traceback

/home/ubuntu/anaconda3/envs/mmocr/lib/python3.7/site-packages/mmdet/apis/inference.py:47: UserWarning: Class names are not saved in the checkpoint's meta data, use COCO classes by default.
  warnings.warn('Class names are not saved in the checkpoint\'s '
Traceback (most recent call last):
  File "demo/image_demo.py", line 44, in <module>
    main()
  File "demo/image_demo.py", line 32, in main
    result = model_inference(model, args.img)
  File "/home/ubuntu/Desktop/mmocr/mmocr/mmocr/apis/inference.py", line 25, in model_inference
    data = test_pipeline(data)
  File "/home/ubuntu/anaconda3/envs/mmocr/lib/python3.7/site-packages/mmdet/datasets/pipelines/compose.py", line 40, in __call__
    data = t(data)
  File "/home/ubuntu/anaconda3/envs/mmocr/lib/python3.7/site-packages/mmdet/datasets/pipelines/loading.py", line 365, in __call__
    results = self._load_bboxes(results)
  File "/home/ubuntu/anaconda3/envs/mmocr/lib/python3.7/site-packages/mmdet/datasets/pipelines/loading.py", line 240, in _load_bboxes
    ann_info = results['ann_info']
KeyError: 'ann_info'

[innerlee]

Currently image_demo.pydoes not support sdmgr. We will add an end2end demo shortly https://github.com/open-mmlab/mmocr/issues/60

[cuhk-hbsun]

1. sdmg-r requires both image and the related metas (bboxes and text), while image_demo.py only use image as input.
2. we will give end2end demo (text detect + text recognize + key information extraction) soon.
3. Currently, you can use tools/kie_test_imgs.py to do visualize (download wildreceipt datasets first https://mmocr.readthedocs.io/en/latest/datasets.html)