Modified the output size of the interpolations for readability

app.py

@@ -338,7 +338,6 @@ 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 = 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):
@@ -348,10 +347,7 @@ latent_matrix = np.array(latent_matrix).T  # Transposes the matrix so that each
 ########################################################################################################################
 # Plotting the Interpolation in 2D Using Chosen Points
 if st.button("Generate Linear Interpolation"):
-    # plt.figure(2)
-
     linear_interp_latent = np.linspace(latent_point_1, latent_point_2, num_interp)
-    print(len(linear_interp_latent))
 
     linear_predicted_interps = []
     figure_2 = np.zeros((28, 28 * num_interp))
@@ -360,11 +356,7 @@ if st.button("Generate Linear Interpolation"):
         figure_2[0:28, i * 28:(i + 1) * 28, ] = generated_image[:, :, -1]
         linear_predicted_interps.append(generated_image[:, :, -1])
 
-    # plt.figure_2(figsize=(15, 15))
-    # plt.imshow(figure, cmap='gray')
-    # plt.figure(2)
-    # st.pyplot(figure_2)
-    st.image(figure_2)
+    st.image(figure_2, width=600)
 ########################################################################################################################
 # Provide User Options
 st.header("Option 2: Perform a Mesh Interpolation")
@@ -436,4 +428,4 @@ if st.button("Generate Mesh Interpolation"):
             figure_3[i * 28:(i + 1) * 28, j * 28:(j + 1) * 28, ] = generated_image[:, :, -1]
             mesh_predicted_interps.append(generated_image[:, :, -1])
 
-    st.image(figure_3)
+    st.image(figure_3, width=600)