actionNet.h

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#ifndef __ACTION_NET_H__
#define __ACTION_NET_H__
 
 
#include "tensorNet.h"
 
 
#define ACTIONNET_DEFAULT_INPUT   "input"
 
#define ACTIONNET_DEFAULT_OUTPUT  "output"
 
#define ACTIONNET_MODEL_TYPE "action"
 
#define ACTIONNET_USAGE_STRING  "actionNet arguments: \n"                                                       \
                  "  --network=NETWORK    pre-trained model to load, one of the following:\n"   \
                  "                           * resnet-18 (default)\n"                                          \
                  "                           * resnet-34\n"                                                    \
                  "  --model=MODEL        path to custom model to load (.onnx)\n"                       \
                  "  --labels=LABELS      path to text file containing the labels for each class\n"                             \
                  "  --input-blob=INPUT   name of the input layer (default is '" ACTIONNET_DEFAULT_INPUT "')\n"         \
                  "  --output-blob=OUTPUT name of the output layer (default is '" ACTIONNET_DEFAULT_OUTPUT "')\n"       \
                  "  --threshold=CONF     minimum confidence threshold for classification (default is 0.01)\n"  \
                  "  --skip-frames=SKIP   how many frames to skip between classifications (default is 1)\n"         \
                  "  --profile            enable layer profiling in TensorRT\n\n"
 
 
class actionNet : public tensorNet
{
public:
        static actionNet* Create( const char* network="resnet-18", uint32_t maxBatchSize=DEFAULT_MAX_BATCH_SIZE, 
                                                 precisionType precision=TYPE_FASTEST, deviceType device=DEVICE_GPU, 
                                                 bool allowGPUFallback=true );
        
        static actionNet* Create( const char* model_path, const char* class_labels, 
                                                const char* input=ACTIONNET_DEFAULT_INPUT, 
                                                const char* output=ACTIONNET_DEFAULT_OUTPUT, 
                                                uint32_t maxBatchSize=DEFAULT_MAX_BATCH_SIZE, 
                                                precisionType precision=TYPE_FASTEST,
                                                deviceType device=DEVICE_GPU, bool allowGPUFallback=true );
        
        static actionNet* Create( int argc, char** argv );
 
        static actionNet* Create( const commandLine& cmdLine );
 
        static inline const char* Usage()               { return ACTIONNET_USAGE_STRING; }
 
        virtual ~actionNet();
        
        template<typename T> int Classify( T* image, uint32_t width, uint32_t height, float* confidence=NULL )          { return Classify((void*)image, width, height, imageFormatFromType<T>(), confidence); }
        
        int Classify( void* image, uint32_t width, uint32_t height, imageFormat format, float* confidence=NULL );
 
        inline uint32_t GetNumClasses() const                                           { return mNumClasses; }
        
        inline const char* GetClassLabel( int index ) const                     { return GetClassDesc(index); }
        
        inline const char* GetClassDesc( int index )    const                   { return index >= 0 ? mClassDesc[index].c_str() : "none"; }
 
        inline const char* GetClassPath() const                                         { return mClassPath.c_str(); }
 
        inline float GetThreshold() const                                                       { return mThreshold; }
        
        inline void SetThreshold( float threshold )                                     { mThreshold = threshold; }
        
        inline uint32_t GetSkipFrames() const                                           { return mSkipFrames; }
        
        inline void SetSkipFrames( uint32_t frames )                                    { mSkipFrames = frames; }
         
protected:
        actionNet();
        
        bool init( const char* model_path, const char* class_path, const char* input, const char* output, uint32_t maxBatchSize, precisionType precision, deviceType device, bool allowGPUFallback );
        bool preProcess( void* image, uint32_t width, uint32_t height, imageFormat format );
 
        float* mInputBuffers[2];
        
        uint32_t mNumClasses;
        uint32_t mNumFrames;    // number of frames fed into the model
        uint32_t mSkipFrames;   // number of frames to skip when processing
        uint32_t mFramesSkipped;        // frame skip counter
        
        uint32_t mCurrentInputBuffer;
        uint32_t mCurrentFrameIndex;
 
        float mThreshold;
        float mLastConfidence;
        int   mLastClassification;
        
        std::vector<std::string> mClassDesc;
 
        std::string mClassPath;
};
 
 
#endif