Saving attempts at optimizing

Data_Generation/Dataset_Generation_Functions.py

@@ -1,5 +1,13 @@
 import numpy as np
 
+from Data_Generation.Shape_Generation_Functions import basic_box, diagonal_box_split, horizontal_vertical_box_split, \
+    back_slash_box, forward_slash_box, back_slash_plus_box, forward_slash_plus_box, hot_dog_box, hamburger_box, \
+    x_hamburger_box, x_hot_dog_box, x_plus_box
+
+import matplotlib.pyplot as plt
+
+from Data_Generation.Piecewise_Box_Functions import add_pixels
+
 
 ########################################################################################################################
 # Make the data using all the code in Shape_Generation_Functions.py
@@ -11,28 +19,102 @@ def make_boxes(image_size, densities, shapes):
     :return: [list[tuple]] - [Array, Density, Thickness, Shape]
     """
 
+    # matrix = []
+    #
+    # for function in shapes:  # Adds different types of shapes
+    #
+    #     # Adds different density values
+    #     for i in range(len(densities)):
+    #         # Loops through the possible thickness values
+    #         for j in range(image_size):  # Adds additional Pixels
+    #             thickness = j
+    #             Array = (function(thickness, densities[i], image_size))
+    #
+    #             # Checks if there are any 0's left in the array to append
+    #             if (np.where((Array == float(0)))[0] > 0).any():
+    #                 the_tuple = (Array, str(function.__name__), densities[i], thickness)
+    #                 matrix.append(the_tuple)
+    #
+    #             # Prevents solids shapes from being appended to the array
+    #             else:
+    #                 break
     matrix = []
+    base_shapes = []
+    density_1 = []
+    for function in shapes:  # Create an array of the base shapes
+        thickness = 0
+        Array = function(thickness, 1, image_size)
+        # density_1_tuple = np.array([Array, str(function.__name__), 1, thickness])  # Array, Shape, Density, Thickness
+        # base_shapes.append(density_1_tuple)
 
-    for function in shapes:  # Adds different types of shapes
+        density_1 = np.append(density_1,(np.array([Array, str(function.__name__), 1, thickness])), axis=1)  # Array, Shape, Density, Thickness
+        # Add one to the thickness of the previous array
+        # for j in range(image_size):
+        while (np.where((Array == float(0)))[0] > 0).any():
+            # Checks if there are any 0's left in the array to append
+            # if (np.where((Array == float(0)))[0] > 0).any():
+                # density_1.append(density_1_tuple, axis=0)
+            thickness += 1
+            if np.shape(density_1) == (4,):
+                Array = add_pixels(density_1[0], 1) # will add 1 pixel to each previous array, rather than adding multiple and having to loop
 
-        # Adds different density values
-        for i in range(len(densities)):
-            # Loops through the possible thickness values
-            for j in range(image_size):  # Adds additional Pixels
-                thickness = j
-                Array = (function(thickness, densities[i], image_size))
+            else:
+                print(np.shape(density_1))
+                print(density_1[-1][0])
+                Array = add_pixels(density_1[-1][0], 1)
+            # print(np.shape(Array))
+            density_1_tuple = np.array([Array, str(function.__name__), 1, thickness])
+            # else:  # Prevents solids shapes from being appended to the array
+            #     break
+            density_1 = np.vstack((density_1, density_1_tuple))
 
-                # Checks if there are any 0's left in the array to append
-                if (np.where((Array == float(0)))[0] > 0).any():
-                    the_tuple = (Array, str(function.__name__), densities[i], thickness)
-                    matrix.append(the_tuple)
+    matrix = []
+    # print(np.shape(density_1[0]))
+    # print(density_1[:][0])
+    for i in range(len(densities)):
+        some = np.multiply(density_1[:][0],densities[i]) #,density_1[:1])
+        # print(np.shape(some))
+        matrix.append(tuple(some))
 
-                # Prevents solids shapes from being appended to the array
-                else:
-                    break
+
+        # # Adds different density values
+        # for i in range(len(densities)):
+        #     # Loops through the possible thickness values
+        #     for j in range(image_size):  # Adds additional Pixels
+        #         thickness = j
+        #         Array = (function(thickness, densities[i], image_size))
+        #
+        #         # Checks if there are any 0's left in the array to append
+        #         if (np.where((Array == float(0)))[0] > 0).any():
+        #             the_tuple = (Array, str(function.__name__), densities[i], thickness)
+        #             matrix.append(the_tuple)
+        #
+        #         # Prevents solids shapes from being appended to the array
+        #         else:
+        #             break
     return matrix
 
 
 ########################################################################################################################
+# Testing
+image_size = 9
+densities = [1]
+shapes = [basic_box, diagonal_box_split, horizontal_vertical_box_split, back_slash_box, forward_slash_box,
+                 back_slash_plus_box, forward_slash_plus_box, hot_dog_box, hamburger_box, x_hamburger_box,
+                 x_hot_dog_box, x_plus_box]
+
+boxes = make_boxes(image_size, densities, shapes)
+
+# print(np.shape(boxes))
+desired_label = 'basic_box'
+desired_density = 1
+desired_thickness = 0
 
+box_arrays, box_shape, box_density, box_thickness,  = list(zip(*boxes))[0], list(zip(*boxes))[1], list(zip(*boxes))[2], list(zip(*boxes))[3]
+# print(np.shape(box_arrays))
+# print(np.shape(box_shape))
+# print(np.shape(box_density))
 
+indices = [i for i in range(len(box_arrays)) if box_shape[i] == desired_label and box_density[i] == desired_density and box_thickness[i] == desired_thickness]
+plt.imshow(box_arrays[indices[0]])
+plt.show()