import streamlit as st import numpy as np from itertools import compress from PIL import Image from Dashboard_setup import sidebar_information sidebar_information() # Move this up to be displayed before the evaluation functions are loaded from Dashboard_automation_setup import fun_dict st.title('Automated Assessment') st.write('On this page you can use automated assessment algorithms to assess how good uploaded images match their respective prompts. Note that the automatic assessment routines have not been validated and accuracy estimated will be provided in a future version.') st.write(' ') ###### Setup of variables ############################ try: # Create necessary variables prompt_dir = st.session_state['prompt_dir'] curr_eval_df = st.session_state['eval_df'] curr_eval_df['Picture_index']=curr_eval_df.index.values # Assess how many images are available for automatic assessment automated_eval_available = sum(curr_eval_df['automated_eval']) # Add task name to eval_df temp_prompt_dir=prompt_dir[['ID','Representations','Task_specific_label']] temp_prompt_dir['Prompt_no']=temp_prompt_dir['ID'].astype('str') curr_eval_df = curr_eval_df.merge(temp_prompt_dir,on='Prompt_no') # Check that user correctly filled out the automation setup file assert list(fun_dict.keys())==st.session_state['automated_tasks'], 'Unsure that the list of automated tasks in Dashboard_setup.py is the same as the keys of the function dict in Dashboard_automation_setup.py' except KeyError: automated_eval_available = 0 ###### Rating loop ############################ # If images for assessment available: create form to start assessment # Else: Note to upload images for assessment if automated_eval_available > 0: # Create objects to hold selections of tasks for automated assessment task_list = list(fun_dict.keys()) task_list_len = len(task_list) task_list_selected = task_list.copy() with st.form("auto_assessment_form",clear_on_submit=True): # Form info statment st.write('Select tasks to assess with the automated assessment below. Once you started an assessment you will not be able to leave this page before the assessment is completed.') # Create list of bool selection buttons, one for every task for i_task in range(task_list_len): curr_task = task_list[i_task] curr_task_count = len(curr_eval_df.loc[ (curr_eval_df['automated_eval']==True)& (curr_eval_df['Task']==curr_task)]) task_list_selected[i_task] = st.checkbox( '{0} ({1} images available)'.format(curr_task, str(curr_task_count))) submitted = st.form_submit_button("Start automated assessment") if submitted: # Create list for tasks which were selected for assessment selected_tasks = list(compress(task_list,task_list_selected)) # Create dataset to loop over with assessment assessed_df = curr_eval_df.loc[ (curr_eval_df['automated_eval']==True)& (curr_eval_df['Task'].isin(selected_tasks))] results_column = [] # Add counter for progress bars num_automated_rows = len(assessed_df) i_num_row = 0 i_progress_increase = 1/num_automated_rows st.write('Progress of automatic evaluation:') auto_assessment_progress = st.progress(0) for row in assessed_df.itertuples(): i_num_row +=1 auto_assessment_progress.progress(0+i_num_row*i_progress_increase) # Apply task based classifier and safe in list temp_image = Image.open(st.session_state['uploaded_img'][row.Picture_index]) temp_result = fun_dict[row.Task]( temp_image,row.Representations,row.Task_specific_label) results_column.append(temp_result) assessed_df['Score']=results_column st.session_state['auto_eval_df']=assessed_df[['File_name','Prompt_no','Picture_index','Task','Score']] st.write('Assessment completed. You can access the results on the summary page. Running a new automated assessment will override past results.') else: st.write('Upload files on dashboard starting page to start automated assessment.')