Added data download button, and incorporating code to use different arrays in the readmme file

app.py

@@ -2,7 +2,7 @@
 
 import matplotlib.pyplot as plt
 import numpy as np
-
+import pandas as pd
 
 import streamlit as st
 from Data_Generation.Dataset_Generation_Functions import make_boxes
@@ -21,7 +21,7 @@ densities = np.linspace(0, 1, num=density_selection+1)[1:]
 sample_basic_box = basic_box_array(image_size, 1)
 sample_forward_slash_box = forward_slash_array(image_size, 1)
 sample_combined = combine_arrays([sample_forward_slash_box, sample_basic_box])
-print(sample_combined)
+# print(sample_combined)
 
 sample_density = np.array([sample_combined * density_value for density_value in densities])
 
@@ -32,9 +32,9 @@ sample_thickness = []
 # print(sample_thickness)
 for i in [1, 2, 3, 4]:
     copy = sample_combined
-    print(i)
+    # print(i)
     test = add_thickness(copy, i)
-    print(test)
+    # print(test)
     sample_thickness.append(test)
     # print(sample_thickness)
 ########################################################################################################################
@@ -117,9 +117,26 @@ indices = [i for i in range(len(box_arrays)) if box_density[i] == desired_densit
 plt.imshow(box_arrays[indices[0]], cmap='gray', vmin=0, vmax=1)
 plt.show()
 '''
+# # Testing
+# image_size = 8
+# densities = [1]
+
+if st.button('Generate Dataset'):  # Generate the samples
+    boxes = make_boxes(image_size, densities)
+    box_arrays, box_density, basic_box_thickness, forward_slash_box_thickness, back_slash_box_thickness,hot_dog_box_thickness, hamburger_box_thickness\
+        = list(zip(*boxes))[0], list(zip(*boxes))[1], list(zip(*boxes))[2], list(zip(*boxes))[3], list(zip(*boxes))[4], list(zip(*boxes))[5], list(zip(*boxes))[6]
+
+    # Create a dataframe to convert the data to a csv file
+    dataframe = (pd.DataFrame((box_arrays, box_density, basic_box_thickness, forward_slash_box_thickness, back_slash_box_thickness,hot_dog_box_thickness, hamburger_box_thickness)).T).astype(str)
+
+    # Rename the columns to the desired outputs
+    dataframe = dataframe.rename(columns={0: "Array", 1: "Density", 2:"Basic Box Thickness", 3:"Forward Slash Strut Thickness", 4:"Back Slash Strut Thickness", 5:"Vertical Strut Thickness", 6:"Horizontal Strut Thickness"})
 
+    csv = dataframe.to_csv('2D_Lattice.csv')
 
+    file = '2D_Lattice.csv'
 
+    st.download_button("Download Dataset", file, file_name='2D_Lattice.csv')
 '''
 
 # food = load_dataset("cmudrc/2d-lattices", split="train[:15]")  # Loads the training data samples