import streamlit as st import numpy as np import pandas as pd from PIL import Image st.title('Manual assessment') st.write('On this page you can rate all uploaded images with regards to how good they match their respective prompts. You can see the outcome of your assessment on the summary page.') st.write(' ') side_image = Image.open('Graphics/IL_Logo.png') st.sidebar.image(side_image) # Create placeholders for key elements assessment_progress = st.empty() # Extract how many images are available for manual assessment in entire uploaded dataset ## Set to zero if the dataset has not been created yet due to starting the app on an assessment page manual_eval_available = 0 try: curr_eval_df = st.session_state['eval_df'] curr_eval_df['Picture_index']=curr_eval_df.index.values curr_manual_eval = curr_eval_df.loc[(curr_eval_df['manual_eval']==True)&(curr_eval_df['manual_eval_completed']==False)] manual_eval_available = len(curr_manual_eval) curr_prompt_dir = st.session_state['prompt_dir'] except KeyError: manual_eval_available = 0 st.session_state['uploaded_img'] = [] #safety if program is started on manual assesssment page and not desktop # Main rating loop ## If images are available for rating this creates a from to submit ratings to database ## If subprompt option is selected, it expands the form to include these as well ## If no images are available it prints situation specific instructions if manual_eval_available > 0: # Let user choose whether subprompts should be presented include_subprompts = st.checkbox('Show related subprompts if available (uploaded subprompts may not be shown if images have been assessed already).', value=True) # Update the progress statement assessment_progress.write('{0} images ready / left for assessment.'.format(manual_eval_available)) # Extract first example for manual assessment which is not rated yet (first meaning the lowest index, for lowest prompt number) ## Also extract relevant metadata of this example curr_eval_df = st.session_state['eval_df'] lowest_prompt_no = curr_eval_df.loc[(curr_eval_df['manual_eval']==True)&(curr_eval_df['manual_eval_completed']==False)].Prompt_no.astype('int').min() curr_picture_index = curr_eval_df.loc[ (curr_eval_df['manual_eval']==True)& (curr_eval_df['manual_eval_completed']==False)& (curr_eval_df['Prompt_no']==str(lowest_prompt_no))].Picture_index.min() curr_manual_eval_row = curr_eval_df.iloc[[curr_picture_index]] curr_prompt_ID = int(curr_manual_eval_row.Prompt_no.item()) curr_prompt_row =st.session_state['prompt_dir'].loc[st.session_state['prompt_dir']['ID']==curr_prompt_ID] # Extract information about linked subprompts curr_linked_prompts = curr_prompt_row.Linked_prompts.item() # Set it to nan if the user chose to hide subprompts in evaluation if include_subprompts == False: curr_linked_prompts = float('nan') # Split the subprompt string to get actual list of subprompt IDs if pd.notna(curr_linked_prompts): curr_linked_prompts = curr_linked_prompts.split(',') # Create form to collect assessment ## First create main prompt inputs, then render subprompts if subprompt list found ## The submit button writes assessment to database form_loc = st.empty() with form_loc.form("multi_form",clear_on_submit=True): # Write main prompt st.write('Prompt: {0}'.format( curr_prompt_dir.loc[curr_prompt_dir['ID']==int(curr_manual_eval_row.Prompt_no.item())]['Prompt'].item() )) # Exclude prompt from rating if user chooses to include_prompt = st.checkbox('Include this prompt in assessment summary', value=True) # Show image of current prompt and rating st.image(st.session_state['uploaded_img'][curr_manual_eval_row.Picture_index.item()],width=350) curr_manual_eval_row['manual_eval_task_score'] = st.radio( "Does the image match the prompt?",('Yes', 'No'), horizontal=True, key='base') st.write(' ') # Create whitespace st.write(' ') # Create whitespace # If there are linked prompts, create df with info # Else create emtpy df which will automatically skip the rating creation for these prompts # Here we do not test for (curr_eval_df['manual_eval']==True) as the curr_linked_prompts is already testing for valid prompt number and we want to ignore the exclusion for subprompts if type(curr_linked_prompts)==list: curr_linked_rows = curr_eval_df.loc[ (curr_eval_df['manual_eval_completed']==False)& (curr_eval_df['Prompt_no'].isin(curr_linked_prompts))] curr_linked_rows = curr_linked_rows.groupby('Prompt_no').first() else: curr_linked_rows = pd.DataFrame() # Create rating for subprompts if a df for subprompt info was created for row in curr_linked_rows.itertuples(): # Prompt st.write('Prompt: {0}'.format( curr_prompt_dir.loc[curr_prompt_dir['ID']==int(row.Index)]['Prompt'].item() )) # Image st.image(st.session_state['uploaded_img'][row.Picture_index],width=350) # Rating curr_linked_rows.loc[curr_linked_rows['Picture_index']==row.Picture_index,'manual_eval_task_score'] = st.radio( "Does the image match the prompt?",('Yes', 'No'), horizontal=True, key=row.Picture_index) st.write(' ') st.write(' ') # Submit assessments to database submitted = st.form_submit_button("Submit") if submitted: # First add main prompt assessment st.session_state['eval_df'].loc[ curr_picture_index,'manual_eval']=include_prompt st.session_state['eval_df'].loc[ curr_picture_index,'manual_eval_completed']=True st.session_state['eval_df'].loc[ curr_picture_index,'manual_eval_task_score']=curr_manual_eval_row['manual_eval_task_score'].item() # Add subprompt assessment if dataset was created for subprompts # This stage will automatically be skipped if the df for linked prompts is empty for row in curr_linked_rows.itertuples(): st.session_state['eval_df'].loc[ row.Picture_index,'manual_eval']=include_prompt st.session_state['eval_df'].loc[ row.Picture_index,'manual_eval_completed']=True st.session_state['eval_df'].loc[ row.Picture_index,'manual_eval_task_score']=row.manual_eval_task_score # Reset page after ratings were submitted st.experimental_rerun() # If no files are uploaded elif len(st.session_state['uploaded_img'])==0: assessment_progress.write('Upload files on dashboard starting page to start manual assessment.') # If files are uploaded but all ratings are completed else: assessment_progress.write('You finished assessing the current batch of uploaded images. Upload more pictures of generate your results on the summary page.') #st.session_state['eval_df'].loc[curr_manual_eval,'manual_eval_completed']=True #st.write(st.session_state['eval_df'])