:zap: Based on yolo's ultra-lightweight universal target detection algorithm, the calculation amount is only 250mflops, the ncnn model size is only 666kb, the Raspberry Pi 3b can run up to 15fps+, and the mobile terminal can run up to 178fps+
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In linux, compile darknet as libdarknet.so. I just write a simple yolo_console_dll.cpp to link .so. #67
when i type the command as g++ -fPIC -std=c++11 -D_GLIBCXX_USE_CXX11_ABI=0 yolo_console_dll.cpp -L./lib/ -I. -ldarknet $(pkg-config --cflags --libs opencv) -o test.
The error is /tmp/ccis7rE8.o：in function‘main’： yolo_console_dll.cpp:(.text+0xb11):‘Detector::Detector(std::string, std::string, int)’undefined reference collect2: error: ld returned 1 exit status
when i type the command as g++ -fPIC -std=c++11 -D_GLIBCXX_USE_CXX11_ABI=0 yolo_console_dll.cpp -L./lib/ -I. -ldarknet $(pkg-config --cflags --libs opencv) -o test. The error is /tmp/ccis7rE8.o：in function‘main’： yolo_console_dll.cpp:(.text+0xb11):‘Detector::Detector(std::string, std::string, int)’undefined reference collect2: error: ld returned 1 exit status
look forward your reply