KSAI-ToolKits
KSAI-Toolkits is a toolkit from AI group of Kingsoft Office Corporation. The inference engine is KSAI-Lite (derived from TensorFlow Lite). The toolkit supports OCR function on multiple OS platforms, including Windows, Linux x86_64, and Linux ARM, at the time of initial release. With time, we plan to add support for more functionalities in the future.
- Linux: ubuntu 16.04
- Windows: windows 10
The CMake version: 3.16+
- Linux: GCC 5.4+
- Windows: Visual Studio 2019
git clone https://github.com/kingsoft-wps/KSAI-Toolkits.git
- Download libraries from server (IP: https://sdk.ai.wpscdn.cn/KSAI/KSAI-Toolkits/3rdparty.zip)
- Decompress the package, and put the 3rdparty folder in the root of the repository.
The downloaded package mainly contains:
- opencv lib and the header files
- KSAI-Lite lib and the header files
- Clipper source code
- Download models and test data from server(IP: https://sdk.ai.wpscdn.cn/KSAI/KSAI-Toolkits/data.zip)
- Decompress the package, and put the data folder in the root of the repository
the build scripts are in tools folder
- build script on windows is build_windows.bat
build_windows.bat
- build script on linux x86 is build_linux.sh
./build_linux.sh
- build script on arm is build_aarch64.sh
./build_aarch64.sh
- build script on mips64 is build_mips64.sh
./build_mips64.sh
Once the compilation is sucessfully finished, look for the executable file KSAI_Toolkits_demo in /output/$platform$/bin/ folder. You can execute it with the following command line paremeters:
./output/linux/bin/KSAI_Toolkits_demo data/OCR/model/db_171_varied.tflite data/OCR/model/cls_best.tflite data/OCR/model/mv3_345000.tflite data/OCR/dictionary/char_6599.txt data/OCR/input/test.jpg
The output of the program should be:
finish the 0 process!! and cost 5.87865s
boxes size:55
绝密★考试结束前
2017年11月浙江省普通高校招生 选考科日考试
历史试题
2017.11
选择题部分
一、选择题(本大题共 30小题,每小题 2分,共 60分。每小题列出的四个备选
项中只有一个是符合题目要求的,不选、多选、错选均不得分)
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之显诸侯。”这反映了
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其观点旨在表达
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7.**古代皇帝制度建立后,围绕集权与分权,官僚体制不断调整和变化。下列与“分宰
第1页
Take a look at ./test/test_ocr.cpp.
What you need to do is:
- Include ks_ocr.h file in your project.
- Import libKSAI-Toolkits.lib/libKSAI-Toolkits.dll/libKSAI-Toolkits.so and related 3rd party libs into your project reference.
- Do whatever you want with the KSAIxxx classes.