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DAISGram.cpp

@@ -0,0 +1,76 @@
+#include <iostream>
+#include <string>
+
+#include "dais_exc.h"
+#include "tensor.h"
+#include "libbmp.h"
+#include "DAISGram.h"
+
+using namespace std;
+
+/**
+ * Load a bitmap from file
+ *
+ * @param filename String containing the path of the file
+ */
+void DAISGram::load_image(string filename){
+    BmpImg img = BmpImg();
+
+    img.read(filename.c_str());
+
+    const int h = img.get_height();
+    const int w = img.get_width();
+
+    data = Tensor(h, w, 3, 0.0);
+
+    for(int i=0;i<img.get_height();i++){
+        for(int j=0;j<img.get_width();j++){ 
+            data(i,j,0) = (float) img.red_at(j,i);
+            data(i,j,1) = (float) img.green_at(j,i);    
+            data(i,j,2) = (float) img.blue_at(j,i);   
+        }                
+    }
+}
+
+
+/**
+ * Save a DAISGram object to a bitmap file.
+ * 
+ * Data is clamped to 0,255 before saving it.
+ *
+ * @param filename String containing the path where to store the image.
+ */
+void DAISGram::save_image(string filename){
+
+    data.clamp(0,255);
+
+    BmpImg img = BmpImg(getCols(), getRows());
+
+    img.init(getCols(), getRows());
+
+    for(int i=0;i<getRows();i++){
+        for(int j=0;j<getCols();j++){
+            img.set_pixel(j,i,(unsigned char) data(i,j,0),(unsigned char) data(i,j,1),(unsigned char) data(i,j,2));                   
+        }                
+    }
+
+    img.write(filename);
+
+}
+
+
+/**
+ * Generate Random Image
+ * 
+ * Generate a random image from nois
+ * 
+ * @param h height of the image
+ * @param w width of the image
+ * @param d number of channels
+ * @return returns a new DAISGram containing the generated image.
+ */  
+void DAISGram::generate_random(int h, int w, int d){
+    data = Tensor(h,w,d,0.0);
+    data.init_random(128,50);
+    data.rescale(255);
+}

DAISGram.h

@@ -18,33 +18,16 @@ class DAISGram{
 
     public:
 
-        DAISGram(){}
+        DAISGram();
 
-        ~DAISGram(){}
+        ~DAISGram();
 
         /**
          * Load a bitmap from file
          *
          * @param filename String containing the path of the file
          */
-        void load_image(string filename){
-            BmpImg img = BmpImg();
-
-        	img.read(filename.c_str());
-
-            const int h = img.get_height();
-            const int w = img.get_width();
-
-            data = Tensor(h, w, 3, 0.0);
-
-            for(int i=0;i<img.get_height();i++){
-                for(int j=0;j<img.get_width();j++){ 
-                    data(i,j,0) = (float) img.red_at(j,i);
-                    data(i,j,1) = (float) img.green_at(j,i);    
-                    data(i,j,2) = (float) img.blue_at(j,i);   
-                }                
-            }
-        }
+        void load_image(string filename);
 
 
         /**
@@ -54,23 +37,7 @@ class DAISGram{
          *
          * @param filename String containing the path where to store the image.
          */
-        void save_image(string filename){
-
-            data.clamp(0,255);
-
-            BmpImg img = BmpImg(getCols(), getRows());
-
-            img.init(getCols(), getRows());
-
-            for(int i=0;i<getRows();i++){
-                for(int j=0;j<getCols();j++){
-                    img.set_pixel(j,i,(unsigned char) data(i,j,0),(unsigned char) data(i,j,1),(unsigned char) data(i,j,2));                   
-                }                
-            }
-
-            img.write(filename);
-
-        }
+        void save_image(string filename);
 
         /**
          * Get rows
@@ -98,6 +65,8 @@ class DAISGram{
          * 
          * It sums the bright variable to all the values in the image.
          * 
+         * Before returning the image, the corresponding tensor should be clamped in [0,255]
+         * 
          * @param bright the amount of bright to add (if negative the image gets darker)
          * @return returns a new DAISGram containing the modified object
          */
@@ -138,7 +107,7 @@ class DAISGram{
          *    0  -1  0
          *  
          * Before returning the image, the corresponding tensor should be clamped in [0,255]
-         *  
+         * 
          * @return returns a new DAISGram containing the modified object
          */
         DAISGram sharpen();
@@ -153,7 +122,7 @@ class DAISGram{
          *    -2 -1  0
          *    -1  1  1
          *     0  1  2
-         *  
+         * 
          * Before returning the image, the corresponding tensor should be clamped in [0,255]
          *  
          * @return returns a new DAISGram containing the modified object
@@ -176,7 +145,7 @@ class DAISGram{
          * @param h the size of the filter
          * @return returns a new DAISGram containing the modified object
          */
-        DAISGram smooth(int h=3); 
+        DAISGram smooth(int h=3);
 
         /**
          * Edges of an image
@@ -190,13 +159,13 @@ class DAISGram{
          * -1   8  -1
          * -1  -1  -1
          * 
-         * Remember to convert the image to grayscale before running the convolution.
+         * Remeber to convert the image to grayscale before running the convolution.
          * 
          * Before returning the image, the corresponding tensor should be clamped in [0,255]
          *  
          * @return returns a new DAISGram containing the modified object
          */  
-        DAISGram edge();   
+        DAISGram edge();
 
         /**
          * Blend with anoter image
@@ -213,12 +182,12 @@ class DAISGram{
          * @param alpha The parameter of the convex combination  
          * @return returns a new DAISGram containing the blending of the two images.
          */  
-        DAISGram blend(DAISGram rhs, float alpha);
+        DAISGram blend(const DAISGram & rhs, float alpha=0.5);
 
         /**
          * Green Screen
          * 
-         * This function substitutes a pixe with the corresponding one in a background image 
+         * This function substitutes a pixel with the corresponding one in a background image 
          * if its colors are in the surrounding (+- threshold) of a given color (rgb).
          * 
          * (rgb - threshold) <= pixel <= (rgb + threshold)
@@ -253,12 +222,7 @@ class DAISGram{
          * @param d number of channels
          * @return returns a new DAISGram containing the generated image.
          */  
-        void generate_random(int h, int w, int d){
-            data = Tensor(h,w,d,0.0);
-            data.init_random(128,30);
-            data.rescale(255);
-        }
-
+        void generate_random(int h, int w, int d);
 };
 
 #endif

main.cpp

@@ -58,6 +58,7 @@ int main (int argc, char * argv[]) {
         img = b.brighten(k_size); /* aumenta la luminosità */
     }
     else if (strcmp(operation, "blend") == 0) {
+        cout<<alpha<<endl;
         c.load_image(fn_in_2);        
         img = b.blend(c, alpha); /* effettua il blending di due immagini */
     }else if (strcmp(operation, "gray") == 0) {

main_tensor.cpp

@@ -0,0 +1,69 @@
+#include <stdio.h>
+#include <string.h>
+#include <math.h>
+#include "tensor.h"
+
+void show_help(){
+    printf("*** Tensors Operations ***\n");
+    printf("\targ 1: input file name (tensor1) \n");
+    printf("\targ 2: input file name (tensor2) \n");
+    printf("\targ 3: operazione da effettuare (+,-,/,*,convolve, concat)\n");
+    printf("\targ 4: output file name\n");
+    printf("\targ 5: Diversi significati in funzione dell'operazione (default 3):\n"
+           "\t\t- [smooth]: kernel size \n"
+           "\t\t- [brighten]: valore bright per aumentare la luminosità \n"
+           "\t\t\n");
+    printf("\targ 6: Diversi significati in funzione dell'operazione (default 1.0):\n"
+           "\t\t- [blend] parametro alpha per il blending di due immagini"); 
+    printf("\n");
+}
+
+int main (int argc, char * argv[]) {
+
+    char * fn_in_1;  /* file 1 */
+    char * fn_in_2;  /* file 2 */
+    char * operation; /* operazione da eseguire */
+    char * fn_out; /* output file */
+
+    int axis = 3; /* axis for concat */
+
+    /* variabili di appoggio per le computazioni */
+    Tensor a,b,out;
+
+    if(argc<4){
+        show_help();
+        return 0;
+    }
+
+    fn_in_1 = argv[1];  /* file 1 */
+    fn_in_2 = argv[2];  /* file 2 */
+    operation = argv[3]; /* operazione da eseguire */
+    fn_out = argv[4]; /* output file */
+
+    if(argc>5) {
+        axis = atoi(argv[5]);
+    }
+
+    a.read_file(fn_in_1);
+    b.read_file(fn_in_2);
+
+    if (strcmp(operation, "+") == 0) {
+        out=a+b; /* aumenta la luminosità */
+    }else if(strcmp(operation, "-") == 0) {
+        out=a-b; /* aumenta la luminosità */
+    }else if(strcmp(operation, "*") == 0) {
+        out=a*b; /* aumenta la luminosità */
+    }else if(strcmp(operation, "/") == 0) {
+        out=a/b; /* aumenta la luminosità */
+    }else if(strcmp(operation, "convolve") == 0) {
+        out=a.convolve(b); /* aumenta la luminosità */
+    }else if(strcmp(operation, "concat") == 0) {
+        out=a.concat(b,axis); /* aumenta la luminosità */
+    }else {
+        throw(unknown_operation());
+    }
+
+    out.write_file(fn_out);
+
+    return 0; /* ciao a tutti!*/
+}

tensor.cpp

@@ -0,0 +1,42 @@
+#include <iostream>
+#include <string>
+#include <random>
+#include <math.h>
+#include <fstream>
+
+#include "dais_exc.h"
+#include "tensor.h"
+
+#define PI 3.141592654
+#define FLT_MAX 3.402823466e+38F /* max value */
+#define FLT_MIN 1.175494351e-38F /* min positive value */
+
+using namespace std;
+
+
+/**
+ * Random Initialization
+ * 
+ * Perform a random initialization of the tensor
+ * 
+ * @param mean The mean
+ * @param std  Standard deviation
+ */
+void Tensor::init_random(float mean, float std){
+    if(data){
+
+        std::default_random_engine generator;
+        std::normal_distribution<float> distribution(mean,std);
+
+        for(int i=0;i<r;i++){
+            for(int j=0;j<c;j++){
+                for(int k=0;k<d;k++){
+                    this->operator()(i,j,k)= distribution(generator);
+                }
+            }
+        }    
+
+    }else{
+        throw(tensor_not_initialized());
+    }
+}