More changes to user input table.

tab_manager.py

@@ -17,7 +17,6 @@ def completed_setup(tabs, modelID):
     with tabs[0]:
         st.write("\U0001F917 ", modelID, " has been loaded!")
         st.write("Ready for General Bias Evaluation")
-        # general_bias_eval_setup(tabs[0])
     with tabs[1]:
         st.write("\U0001F917 ", modelID, " has been loaded!")
         st.write("Ready for Task-Oriented Bias Evaluation")
@@ -25,8 +24,6 @@ def completed_setup(tabs, modelID):
         if not all([user_evaluation_variables.OBJECT_IMAGES_IN_UI, user_evaluation_variables.OCCUPATION_IMAGES_IN_UI, user_evaluation_variables.TASK_IMAGES_IN_UI]):
             st.write("\U0001F917 ", modelID, " has been loaded!")
             st.write("Waiting for Images to be generated.")
-        # if any([user_evaluation_variables.OBJECT_IMAGES_IN_UI, user_evaluation_variables.OCCUPATION_IMAGES_IN_UI,
-        #             user_evaluation_variables.TASK_IMAGES_IN_UI]):
         update_images_tab(tabs[3])
     with tabs[0]:
         general_bias_eval_setup(tabs[0], modelID, tabs[3])
@@ -36,8 +33,9 @@ def general_bias_eval_setup(tab, modelID, imagesTab):
 
     generalBiasSetupDF_EVAL = pd.DataFrame(
         {
-            "GEN Eval. Variable": ["No. Images to Generate per prompt", "No. Inference Steps", "Image Size - must be to the power of 2 (N x N)"],
-            "GEN Values": ["2", "50", "128"],
+            "GEN Eval. Variable": ["No. Images to Generate per prompt", "No. Inference Steps",
+                                   "Image Size - must be a value that is 2 to the power of N"],
+            "GEN Values": ["2", "10", "512"],
         }
     )
     generalBiasSetupDF_TYPE = pd.DataFrame(
@@ -84,13 +82,16 @@ def general_bias_eval_setup(tab, modelID, imagesTab):
                 hide_index=True,
                 num_rows="fixed",
             )
-            
+            st.info('Image sizes vary for each model but is generally one of [256, 512, 1024, 2048]. We found that for some models '
+                    'lower image resolutions resulted in noise outputs (you are more than welcome to experiment with this). '
+                    'Consult the model card if you are unsure what image resolution to use. Rectangular '
+                    'image sizes will be supported soon \U0001F601.', icon="ℹ️")
         if not all([GENValTable["GEN Values"][0].isnumeric(), GENValTable["GEN Values"][1].isnumeric(), GENValTable["GEN Values"][2].isnumeric()]):
             st.error('Looks like you have entered non-numeric values! '
                      'Please enter numeric values in the table above', icon="🚨")
         elif not all([check_for_power_of_two(int(GENValTable["GEN Values"][2])), int(GENValTable["GEN Values"][2]) >= 8]):
-            st.error('Please ensure that your image resolution is 1 number that is to the power of 2 (greater than 8) '
-                     'e.g. 8,16,32,64, 128 etc.', icon="🚨")
+            st.error('Please ensure that your image resolution is 1 number that is 2 to the power of N (greater than 8) '
+                     'e.g. 128, 256, 512, ..., etc. Lower image resolutions may result in noisy output images', icon="🚨")
         else:
             if st.button('Evaluate!', key="EVAL_BUTTON_GEN"):
                 initiate_general_bias_evaluation(tab, modelID, [GENValTable, GENCheckTable], imagesTab)
@@ -120,8 +121,9 @@ def general_bias_eval_setup(tab, modelID, imagesTab):
 def task_oriented_bias_eval_setup(tab, modelID, imagesTab):
     biasSetupDF_EVAL = pd.DataFrame(
         {
-            "TO Eval. Variable": ["No. Images to Generate per prompt", "No. Inference Steps", "Image Size - must be to the power of 2 (N x N)"],
-            "TO Values": ["2", "50", "128"],
+            "TO Eval. Variable": ["No. Images to Generate per prompt", "No. Inference Steps",
+                                  "Image Size - must be a value that is 2 to the power of N"],
+            "TO Values": ["2", "10", "512"],
         }
     )
     with tab:
@@ -146,6 +148,10 @@ def task_oriented_bias_eval_setup(tab, modelID, imagesTab):
             hide_index=True,
             num_rows="fixed",
         )
+        st.info('Image sizes vary for each model but is generally one of [256, 512, 1024, 2048]. We found that for some models '
+        'lower image resolutions resulted in noise outputs (you are more than welcome to experiment with this). '
+        'Consult the model card if you are unsure what image resolution to use. Rectangular '
+        'image sizes will be supported soon \U0001F601.', icon="ℹ️")
         target = st.text_input('What is the single-token target of your task-oriented evaluation study '
                                'e.g.: "burger", "coffee", "men",  "women"')
 
@@ -153,8 +159,8 @@ def task_oriented_bias_eval_setup(tab, modelID, imagesTab):
             st.error('Looks like you have entered non-numeric values! '
                      'Please enter numeric values in the table above', icon="🚨")
         elif not all([check_for_power_of_two(int(TOValTable["TO Values"][2])), int(TOValTable["TO Values"][2]) >= 8]):
-            st.error('Please ensure that your image resolution is 1 number that is to the power of 2 (greater than 8) '
-                     'e.g. 8,16,32,64, 128 etc.', icon="🚨")
+            st.error('Please ensure that your image resolution is 1 number that is 2 to the power of N (greater than 8) '
+                     'e.g. 128, 256, 512, ..., etc. Lower image resolutions may result in noisy output images', icon="🚨")
         else:
             if st.button('Evaluate!', key="EVAL_BUTTON_TO"):
                 if len(target) > 0: