Modifying the number of options for interpolation lengths. Also changed the definition of the interpolation length

app.py

@@ -260,7 +260,7 @@ shape_options = ("basic_box", "diagonal_box_split", "horizontal_vertical_box_spl
 "x_hot_dog_box", "x_plus_box")
 density_options = ["{:.2f}".format(x) for x in np.linspace(0.1, 1, 10)]
 thickness_options = [str(int(x)) for x in np.linspace(0, 10, 11)]
-interpolation_options = [str(int(x)) for x in [3, 5, 10, 20]]
+interpolation_options = [str(int(x)) for x in np.linspace(2, 20, 19)]
 
 # Provide User Options
 st.header("Option 1: Perform a Linear Interpolation")
@@ -338,8 +338,8 @@ latent_point_2 = encoder_model_boxes.predict(number_2_expand)[0]
 latent_dimensionality = len(latent_point_1)  # define the dimensionality of the latent space
 ########################################################################################################################
 # Establish the Framework for a LINEAR Interpolation
-number_internal = int(interp_length)  # the number of interpolations that the model will find between two points
-num_interp = number_internal + 2  # the number of images to be pictured
+# number_internal = int(interp_length)  # the number of interpolations that the model will find between two points
+num_interp = int(interp_length)   # the number of images to be pictured
 latent_matrix = []  # This will contain the latent points of the interpolation
 for column in range(latent_dimensionality):
     new_column = np.linspace(latent_point_1[column], latent_point_2[column], num_interp)