File reader implementation

Makefile

@@ -8,7 +8,7 @@ BUILD_DIR := build
 DEBUG := FALSE
 
 # Objects and executable
-OBJS := $(addprefix $(BUILD_DIR)/, main.o pipeline.o segfilter.o StateManager.o IdlingState.o ProcessingState.o IOBridge.o UART.o ThreadLogger.o LoggingLevel.o )
+OBJS := $(addprefix $(BUILD_DIR)/, main.o pipeline.o StateManager.o IdlingState.o ProcessingState.o segfilter.o IOBridge.o UART.o Reader.o ThreadLogger.o LoggingLevel.o )
 TARGET := $(BUILD_DIR)/pipeline
 
 LIB := tensorflow
@@ -26,9 +26,9 @@ ifeq ($(LIB),nvinfer)
 endif
 
 # Compiler flags
-CFLAGS := -Wall -Werror -Wpedantic 
+CFLAGS := -Wall -Werror -Wpedantic -std=c++17 -fopenmp
 
-LINKERFLAGS := -lstdc++ -lpthread
+LINKERFLAGS := -lstdc++ -lpthread 
 
 # Conditionally add leak sanitizer
 ifeq ($(LEAK),TRUE)
@@ -95,7 +95,9 @@ $(BUILD_DIR)/LoggingLevel.o: $(SRC_DIR)/utils/LoggingLevel.cpp $(SRC_DIR)/utils/
 	@mkdir -p $(@D)
 	$(CC) $(CFLAGS) -c $(SRC_DIR)/utils/LoggingLevel.cpp -o $@
 
-
+$(BUILD_DIR)/Reader.o: $(SRC_DIR)/utils/Reader.cpp $(SRC_DIR)/utils/Reader.hpp
+	@mkdir -p $(@D)
+	$(CC) $(CFLAGS) -c $(SRC_DIR)/utils/Reader.cpp -o $@
 
 
 

src/bridge/UART.cpp

@@ -6,9 +6,9 @@ UartIO::UartIO(ThreadLogger *logger)
     // SETUP SERIAL WORLD
 
     struct termios port_options; // Create the structure
-
+    uartId = open(uart_target, O_RDWR | O_NOCTTY);
     tcgetattr(uartId, &port_options); // Get the current attributes of the Serial port
-
+    
     //------------------------------------------------
     //  OPEN THE UART
     //------------------------------------------------
@@ -24,7 +24,8 @@ UartIO::UartIO(ThreadLogger *logger)
     //                 Caution: VMIN and VTIME flags are ignored if O_NONBLOCK flag is set.
     //	    O_NOCTTY - When set and path identifies a terminal device, open() shall not cause the terminal device to become the controlling terminal for the process.uartId = open("/dev/ttyTHS1", O_RDWR | O_NOCTTY | O_NDELAY);		//Open in non blocking read/write mode
 
-    uartId = open(uart_target, O_RDWR | O_NOCTTY);
+
+
 
     tcflush(uartId, TCIFLUSH);
     tcflush(uartId, TCIOFLUSH);

src/filter/IFilter.hpp

@@ -5,6 +5,6 @@ class IFilter
 {
 public:
     virtual ~IFilter() {}
-    virtual void doProcessing(unsigned char* image, int width, int height, int channels) = 0;
+    virtual int * doProcessing(unsigned char* image, int width, int height, int channels) = 0;
     virtual void doDecision() = 0;
 };

src/filter/segfilter.cpp

@@ -3,8 +3,8 @@
 
 
 
-void SegFilter::doProcessing(unsigned char* image, int width, int height, int channels) {
-    SegFilter::model -> predict(image, width, height, channels);   
+int * SegFilter::doProcessing(unsigned char* image, int width, int height, int channels) {
+    return SegFilter::model -> predict(image, width, height, channels);   
 }
 
 void SegFilter::doDecision() {
@@ -14,7 +14,7 @@ void SegFilter::doDecision() {
 
 SegFilter::SegFilter(const char *modelPath,ThreadLogger * logger) {
     logger -> log("Mounting segmentation filter...");
-    IModel * model = new TFLiteModel(logger);
+    IModel * model = new TensorRTModel(logger);
     model -> loadModel(modelPath);
     SegFilter::model = model;
 

src/filter/segfilter.hpp

@@ -2,7 +2,7 @@
 #define SEG_FILTER_H
 
 #include "IFilter.hpp"
-#include "../model/TFLiteModel.hpp"
+#include "../model/TensorRTModel.hpp"
 #include <stdio.h>
 #include "../utils/ThreadLogger.hpp"
 
@@ -14,7 +14,7 @@ class SegFilter: public IFilter{
 public:
     SegFilter(const char *modelPath,ThreadLogger * logger);
     ~SegFilter();
-    virtual void doProcessing(unsigned char* image, int width, int height, int channels);
+    virtual int * doProcessing(unsigned char* image, int width, int height, int channels);
     virtual void doDecision();
 
 };

src/model/IModel.hpp

@@ -7,5 +7,5 @@ class IModel
 public:
     virtual ~IModel() {}
     virtual void loadModel(const char *modelPath) = 0;
-    virtual void predict(unsigned char* image, int height, int width, int channels) = 0;
+    virtual int * predict(unsigned char* image, int height, int width, int channels) = 0;
 };

src/model/TFLiteModel.cpp

@@ -43,15 +43,15 @@ void TFLiteModel::loadModel(const char *modelPath)
     TF_DeleteBuffer(model_buffer);
 }
 
-void TFLiteModel::predict(unsigned char *image, int height, int width, int channels)
+int * TFLiteModel::predict(unsigned char *image, int height, int width, int channels)
 {
 
     TFLiteModel::logger -> log("Performing inference");
     if (graph == nullptr)
     {
         LoggingLevelWrapper level(LoggingLevel::ERROR);
         TFLiteModel::logger -> log(level, "Graph not initialized");
-        return;
+        return nullptr;
     }
     // Set input tensor
     TF_DataType dtype = TF_UINT8;
@@ -69,13 +69,13 @@ void TFLiteModel::predict(unsigned char *image, int height, int width, int chann
     {
         LoggingLevelWrapper level(LoggingLevel::ERROR);
         TFLiteModel::logger -> log(level,"TF object session not initialized");
-        return;
+        return nullptr;
     }
     if (status == nullptr)
     {
         LoggingLevelWrapper level(LoggingLevel::ERROR);
         TFLiteModel::logger -> log(level,"TF object status not initialized");
-        return;
+        return nullptr;
     }
 
     this -> logger -> log("Running session");
@@ -85,7 +85,7 @@ void TFLiteModel::predict(unsigned char *image, int height, int width, int chann
     this -> logger -> log("Session run");
     if (input_tensor)
         TF_DeleteTensor(input_tensor);
-
+    return nullptr;
 }
 void TFLiteModel::deallocator(void *data, size_t length, void *arg)
 {

src/model/TFLiteModel.hpp

@@ -22,7 +22,7 @@ class TFLiteModel : public IModel{
     TFLiteModel(ThreadLogger * logger);
     virtual ~TFLiteModel();
     virtual void loadModel(const char *modelPath);
-    virtual void predict(unsigned char* image, int height, int width, int channels);
+    virtual int * predict(unsigned char* image, int height, int width, int channels);
 };
 
 #endif // MODEL_HPP

src/model/TensorRTModel.cpp

@@ -3,8 +3,9 @@
 class Logger : public nvinfer1::ILogger
 {
     ThreadLogger *logger;
-
-    public:void setLogger(ThreadLogger *logger)
+
+public:
+    void setLogger(ThreadLogger *logger)
     {
         Logger::logger = logger;
     }
@@ -90,12 +91,12 @@ void TensorRTModel::loadModel(const char *modelPath)
     }
 }
 
-void TensorRTModel::predict(unsigned char *image, int height, int width, int channels)
+int *TensorRTModel::predict(unsigned char *image, int height, int width, int channels)
 {
     if (engine == nullptr)
     {
         this->logger->log("Engine not initialized\n");
-        return;
+        return nullptr;
     }
     this->logger->log("Performing TensorRT inference...\n");
     // Allocate GPU memory for the input and output buffers
@@ -117,12 +118,32 @@ void TensorRTModel::predict(unsigned char *image, int height, int width, int cha
     float *cpu_output = new float[height * width * 7];
     cudaMemcpy(cpu_output, gpu_output, sizeof(float) * height * width * 7, cudaMemcpyDeviceToHost);
 
-    // Clean up
-    //! TODO: This is possibly the image output from the model so it has to be returned
-    delete[] cpu_output;
-
     cudaFree(gpu_input);
     cudaFree(gpu_output);
+
+    int *max_indices = new int[height * width];
     delete context;
+
+    // Parallelized post-processing using OpenMP
+    #pragma omp parallel for
+    for (int i = 0; i < height * width; ++i)
+    {
+        float max_value = cpu_output[i * 7];
+        int max_index = 0;
+        for (int j = 1; j < 7; ++j)
+        {
+            if (cpu_output[i * 7 + j] > max_value)
+            {
+                max_value = cpu_output[i * 7 + j];
+                max_index = j;
+            }
+        }
+        max_indices[i] = max_index;
+    }
+    // Clean up
+    //! TODO: This is possibly the image output from the model so it has to be returned
+
+
     this->logger->log("TensorRT inference done!\n");
+    return max_indices;
 }

src/model/TensorRTModel.hpp

@@ -21,7 +21,7 @@ class TensorRTModel : public IModel{
     TensorRTModel(ThreadLogger * logger);
     virtual ~TensorRTModel();
     virtual void loadModel(const char *modelPath);
-    virtual void predict(unsigned char* image, int height, int width, int channels);
+    virtual int * predict(unsigned char* image, int height, int width, int channels);
 };
 
 #endif // TENSORRTMODEL_HPP

src/pipeline.cpp

@@ -6,7 +6,7 @@ Pipeline::Pipeline(){
     this->logger = new ThreadLogger();
     logger->log("Starting system pipeline...");
     this->stateManager = new StateManager(logger);
-    this->stateManager->transitionTo(new IdlingState());
+    this->stateManager->transitionTo(new ProcessingState());
     this->ioBridge = new IOBridge(logger, stateManager);
     stateManager -> pushShutdown([this](){this -> stop();});
 }