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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.')
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