updates

backend/disentangle_concepts.py

@@ -31,7 +31,7 @@ def generate_composite_images(model, z, decision_boundaries, lambdas, latent_spa
 
     z = torch.from_numpy(z.copy()).to(device)
     repetitions = 16 
-    z_0 = z.copy()
+    z_0 = z
     
     for decision_boundary, lmbd in zip(decision_boundaries, lambdas):
         decision_boundary = torch.from_numpy(decision_boundary.copy()).to(device)

pages/1_Textiles_Disentanglement.py

@@ -47,7 +47,14 @@ if 'color_ids' not in st.session_state:
     st.session_state.concept_ids = COLORS_LIST[-1]
 if 'space_id' not in st.session_state:
     st.session_state.space_id = 'W'
-
+if 'color_lambda' not in st.session_state:
+    st.session_state.color_lambda = 7
+if 'saturation_lambda' not in st.session_state:
+    st.session_state.saturation_lambda = 0
+if 'value_lambda' not in st.session_state:
+    st.session_state.value_lambda = 0
+    
+    
 # def on_change_random_input():
 #     st.session_state.image_id = st.session_state.image_id
 
@@ -87,9 +94,12 @@ with input_col_2:
         color_lambda = chosen_color_lambda_input.number_input('Lambda:', min_value=0, step=1, value=7)
         color_lambda_button = st.form_submit_button('Choose the defined lambda')
           
-        if colors_button:
+        if colors_button or color_lambda_button:
             st.session_state.concept_ids = type_col
-            st.session_state.space_id = space_id
+            st.session_state.color_lambda = color_lambda
+            
+            
+            
         
 with input_col_3:
     with st.form('text_form'):
@@ -104,6 +114,10 @@ with input_col_3:
         value_lambda = chosen_value_lambda_input.number_input('Lambda:', min_value=0, step=1, key=1)
         value_lambda_button = st.form_submit_button('Choose the defined lambda for Value')
         
+        if saturation_lambda_button or value_lambda_button:
+            st.session_state.saturation_lambda = int(saturation_lambda)
+            st.session_state.value_lambda = int(value_lambda)
+            
 # with input_col_4:
 #     with st.form('Network specifics:'):
 #         st.write('**Choose a latent space to use**')
@@ -142,7 +156,7 @@ with header_col_2:
     color_separation_vector, performance_color = concept_vectors[concept_vectors['color'] == st.session_state.concept_ids].reset_index().loc[0, ['vector', 'score']]
     saturation_separation_vector, performance_saturation = concept_vectors[concept_vectors['color'] == 'Saturation'].reset_index().loc[0, ['vector', 'score']]
     value_separation_vector, performance_value = concept_vectors[concept_vectors['color'] == 'Value'].reset_index().loc[0, ['vector', 'score']]
-    st.write(f'Change in {st.session_state.concept_ids} of {np.round(color_lambda, 2)}, in saturation of {np.round(saturation_lambda, 2)}, in value of {np.round(value_lambda, 2)}. - Performance color vector: {performance_color}, saturation vector: {performance_saturation}, value vector: {performance_value}')
+    st.write(f'Change in {st.session_state.concept_ids} of {np.round(st.session_state.color_lambda, 2)}, in saturation of {np.round(st.session_state.saturation_lambda, 2)}, in value of {np.round(st.session_state.value_lambda, 2)}. - Performance color vector: {performance_color}, saturation vector: {performance_saturation/100}, value vector: {performance_value/100}')
 
 # ---------------------------- DISPLAY COL 2 ROW 1 ------------------------------
 
@@ -157,5 +171,5 @@ with output_col_1:
     st.image(img)
 
 with output_col_2:
-    image_updated = generate_composite_images(model, original_image_vec, [separation_vector_color, saturation_separation_vector, value_separation_vector], lambdas=[color_lambda, saturation_lambda, value_lambda])
+    image_updated = generate_composite_images(model, original_image_vec, [color_separation_vector, saturation_separation_vector, value_separation_vector], lambdas=[st.session_state.color_lambda, st.session_state.saturation_lambda, st.session_state.value_lambda])
     st.image(image_updated)