diff --git a/src/machine_learning/image/filters/average_filter.h b/src/machine_learning/image/filters/average_filter.h
index 680d9ac9..146eb75f 100644
--- a/src/machine_learning/image/filters/average_filter.h
+++ b/src/machine_learning/image/filters/average_filter.h
@@ -23,7 +23,7 @@ namespace avg_filter {
     int width = img._width();
     Image resulted_img(height, width);
     std::vector<std::vector<float> > kernel = {{1.0/9, 1.0/9, 1.0/9}, {1.0/9, 1.0/9, 1.0/9}, {1.0/9, 1.0/9, 1.0/9}};
-    return img.apply_filter2d_float(kernel).get_2d_array();
+    return img.apply_filter2d(kernel).get_2d_array();
   }
 }
 
diff --git a/src/machine_learning/image/image.h b/src/machine_learning/image/image.h
index 297d1016..5c25d452 100644
--- a/src/machine_learning/image/image.h
+++ b/src/machine_learning/image/image.h
@@ -1,6 +1,7 @@
 #ifndef img_H
 #define img_H
 
+#include <cinttypes>
 #ifdef __cplusplus
 #include <iostream>
 #include <vector>
@@ -274,11 +275,11 @@ class Image{
   }
 
   /**
-  * @brief apply_filter2d_float function
+  * @brief apply_filter2d function
   * @param filter: 3x3 kernel with floats to be applied to the image
   * @return vector<vector<int32_t> > the resulted image
   */
-  Image apply_filter2d_float(std::vector<std::vector<float> > &filter) const {
+  Image apply_filter2d(std::vector<std::vector<float> > &filter) const {
     assert(filter.size() == 3 && filter[0].size() == 3);
     Image resulted_img(height, width);
     for(int x = 0; x<height; x++){
@@ -312,5 +313,36 @@ class Image{
     }
     return resulted_img;
   }
+
+  /**
+  * @brief overloaded operator << for Image class
+  */
+  friend std::ostream & operator << (std::ostream &out, const Image &img) {
+      int height = img._height(), width = img._width();
+
+      auto write = [&](const int &start_at, const int &end_at) -> void {
+        for(int i = start_at; i<=end_at && i<height; i++) {
+            int j = 0;
+            for(; j<=10 && j<width; j++) {
+                if(j != std::min(10, width - 1)) {
+                    out << img.get_point(i, j) << ", ";
+                }
+                else {
+                    out << img.get_point(i, j);
+                }
+            }
+            out << '\n';
+        }
+      };
+
+      out << '[';
+      write(0, 2);
+      out << "...";
+      out << '\n';
+      write(height - 3, height - 1);
+      out << "(height: " << height << ", width: " << width << ')' << ']';
+      out << '\n';
+      return out;
+  }
 };
 #endif
diff --git a/tests/machine_learning/image/image.cc b/tests/machine_learning/image/image.cc
index d6993033..11bb89fa 100644
--- a/tests/machine_learning/image/image.cc
+++ b/tests/machine_learning/image/image.cc
@@ -18,14 +18,14 @@ TEST_CASE("Testing secondary constructor of Image class") {
 }
 
 TEST_CASE("Testing getting point of a 2d image") {
-   std::vector<std::vector<int32_t> > img = {{1,0,0}, {1,0,0}, {0,0,1}, {0,0,0}}; 
+   std::vector<std::vector<int32_t> > img = {{1,0,0}, {1,0,0}, {0,0,1}, {0,0,0}};
    Image i(img);
    REQUIRE(i.get_point(0, 0) == 1);
    REQUIRE(i.get_point(0, 1) == 0);
 }
 
 TEST_CASE("Testing setting point at a 2d image") {
-    std::vector<std::vector<int32_t> > img = {{1,0,0}, {1,0,0}, {0,0,1}, {0,0,0}}; 
+    std::vector<std::vector<int32_t> > img = {{1,0,0}, {1,0,0}, {0,0,1}, {0,0,0}};
     Image i(img);
 
     REQUIRE(i.get_point(0, 0) == 1);
@@ -34,7 +34,7 @@ TEST_CASE("Testing setting point at a 2d image") {
 }
 
 TEST_CASE("Testing adding to a point in 2d image") {
-    std::vector<std::vector<int32_t> > img = {{1,0,0}, {1,0,0}, {0,0,1}, {0,0,0}}; 
+    std::vector<std::vector<int32_t> > img = {{1,0,0}, {1,0,0}, {0,0,1}, {0,0,0}};
     Image i(img);
 
     REQUIRE(i.get_point(1, 1) == 0);
@@ -74,16 +74,38 @@ TEST_CASE("Testing sub 2 2d images") {
 TEST_CASE("Testing multiplying 2 2d images") {
     std::vector<std::vector<int32_t> > img = {{0, 0, 0}, {1, 1, 1}, {0, 0, 0}};
     std::vector<std::vector<int32_t> > img2 = {{0, 0, 0}, {1, 1, 1}, {0, 0, 0}};
-    Image i1(img), i2(img2); 
+    Image i1(img), i2(img2);
     i1 = i1.mul(i2);
     REQUIRE(i1.get_2d_array() == img2);
 }
 
 TEST_CASE("Testing applying 2d filter") {
     std::vector<std::vector<int32_t> > img = {{1, 1, 1, 1}, {1, 1, 1, 1}, {1, 1, 1, 1}, {1, 1, 1, 1}, {1, 1, 1, 1}, {1, 1, 1, 1}, {1, 1, 1, 1}, {1, 1, 1, 1}, {1, 1, 1, 1}, {1, 1, 1, 1}, {1, 1, 1, 1}, {1, 1, 1, 1}, {1, 1, 1, 1}, {1, 1, 1, 1}};
-    std::vector<std::vector<int32_t> > kernel = {{0, 0, 0}, {0, 0, 0}, {0, 0, 0}}; 
+    std::vector<std::vector<int32_t> > kernel = {{0, 0, 0}, {0, 0, 0}, {0, 0, 0}};
     std::vector<std::vector<int32_t> > check(img.size(), std::vector<int32_t>(img[0].size(), 0));
     Image i(img);
     i = i.apply_filter2d(kernel);
     REQUIRE(i.get_2d_array() == check);
+
+    std::vector<std::vector<float> > kernel2 = { {1.0/9, 1.0/9, 1.0/9}, {1.0/9, 1.0/9, 1.0/9}, {1.0/9, 1.0/9, 1.0/9} };
+
+    CHECK_NOTHROW(i = i.apply_filter2d(kernel2));
+}
+
+TEST_CASE("Testing operator << for image class") {
+    std::vector<std::vector<int32_t> > img = {{1, 1, 1, 1}, {1, 1, 1, 1}, {1, 1, 1, 1}};
+
+    Image i(img);
+
+    CHECK_NOTHROW(std::cout << i << '\n');
+
+    std::vector<std::vector<int32_t> > img2(100, std::vector<int32_t>(100));
+
+    for(int i = 0; i<100; i++) {
+        std::iota(img2[i].begin(), img2[i].end(), 1);
+    }
+
+    Image i2(img2);
+
+    CHECK_NOTHROW(std::cout << i2 << '\n');
 }