Preparing for TBYB V2

app.py

@@ -1,6 +1,5 @@
 import streamlit as st
-st.set_page_config(layout="centered")
-import streamlit_authenticator as stauth
+st.set_page_config(layout="wide")
 from uuid import uuid4
 import model_comparison as MCOMP
 import model_loading as MLOAD
@@ -17,114 +16,8 @@ from huggingface_hub import CommitScheduler, login, snapshot_download
 login(token=os.environ.get("HF_TOKEN"), write_permission=True)
 
 
-AUTHENTICATOR = None
 TBYB_LOGO = Image.open('./assets/TBYB_logo_light.png')
-USER_LOGGED_IN = False
 
-
-USER_DATABASE_DIR = Path("data")
-USER_DATABASE_DIR.mkdir(parents=True, exist_ok=True)
-
-USER_DATABASE_PATH = USER_DATABASE_DIR / f"user_database.yaml"
-
-USER_DATABASE_UPDATE_SCHEDULER = CommitScheduler(
-    repo_id="try-before-you-bias-data",
-    repo_type="dataset",
-    folder_path=USER_DATABASE_DIR,
-    path_in_repo="data",
-    every=1,
-)
-def create_new_user(authenticator, users):
-
-    try:
-        if authenticator.register_user('Register user', preauthorization=False):
-            st.success('User registered successfully')
-    except Exception as e:
-        st.error(e)
-    with USER_DATABASE_UPDATE_SCHEDULER.lock:
-        with USER_DATABASE_PATH.open('w') as file:
-            yaml.dump(users, file, default_flow_style=False)
-
-
-def forgot_password(authenticator, users):
-    try:
-        username_of_forgotten_password, email_of_forgotten_password, new_random_password = authenticator.forgot_password(
-            'Forgot password')
-        if username_of_forgotten_password:
-            st.success('New password to be sent securely')
-            # Random password should be transferred to user securely
-    except Exception as e:
-        st.error(e)
-    with USER_DATABASE_UPDATE_SCHEDULER.lock:
-        with open(USER_DATABASE_PATH, 'w') as file:
-            yaml.dump(users, file, default_flow_style=False)
-def update_account_details(authenticator, users):
-    if st.session_state["authentication_status"]:
-        try:
-            if authenticator.update_user_details(st.session_state["username"], 'Update user details'):
-                st.success('Entries updated successfully')
-        except Exception as e:
-            st.error(e)
-    with USER_DATABASE_UPDATE_SCHEDULER.lock:
-        with open(USER_DATABASE_PATH, 'w') as file:
-            yaml.dump(users, file, default_flow_style=False)
-def reset_password(authenticator, users):
-    if st.session_state["authentication_status"]:
-        try:
-            if authenticator.reset_password(st.session_state["username"], 'Reset password'):
-                st.success('Password modified successfully')
-        except Exception as e:
-            st.error(e)
-    with USER_DATABASE_UPDATE_SCHEDULER.lock:
-        with open(USER_DATABASE_PATH, 'w') as file:
-            yaml.dump(users, file, default_flow_style=False)
-def user_login_create():
-    global AUTHENTICATOR
-    global TBYB_LOGO
-    global USER_LOGGED_IN
-    users = None
-    snapshot_download(repo_id='JVice/try-before-you-bias-data',repo_type='dataset',local_dir='user_data')
-    with open('user_data/data/user_database.yaml') as file:
-        users = yaml.load(file, Loader=SafeLoader)
-        AUTHENTICATOR = stauth.Authenticate(
-            users['credentials'],
-            users['cookie']['name'],
-            users['cookie']['key'],
-            users['cookie']['expiry_days'],
-            users['preauthorized']
-        )
-            
-    with st.sidebar:
-        st.image(TBYB_LOGO, width=70)
-        loginTab, registerTab, detailsTab = st.tabs(["Log in", "Register", "Account details"])
-
-        with loginTab:
-            # name, authentication_status, username = AUTHENTICATOR.login('Login', 'main')
-            name, authentication_status, username = AUTHENTICATOR.login('main', fields = {'Form name': 'Login'})
-            if authentication_status:
-                AUTHENTICATOR.logout('Logout', 'main')
-                st.write(f'Welcome *{name}*')
-                user_evaluation_variables.USERNAME = username
-                USER_LOGGED_IN = True
-            elif authentication_status == False:
-                st.error('Username/password is incorrect')
-                forgot_password(AUTHENTICATOR, users)
-            elif authentication_status == None:
-                st.warning('Please enter your username and password')
-                forgot_password(AUTHENTICATOR, users)
-        if not authentication_status:
-            with registerTab:
-                create_new_user(AUTHENTICATOR, users)
-        else:
-            with detailsTab:
-                st.write('**Username:** ', username)
-                st.write('**Name:** ', name)
-                st.write('**Email:** ', users['credentials']['usernames'][username]['email'])
-                # update_account_details(AUTHENTICATOR, users)
-                reset_password(AUTHENTICATOR, users)
-
-
-    return USER_LOGGED_IN
 def setup_page_banner():
     global USER_LOGGED_IN
     # for tab in [tab1, tab2, tab3, tab4, tab5]:
@@ -138,18 +31,17 @@ def setup_page_banner():
 def setup_how_to():
     expander = st.expander("How to Use")
     expander.write("1. Watch our tutorial video series on [YouTube](https://www.youtube.com/channel/UCk-0xyUyT0MSd_hkp4jQt1Q)\n"
-                   "2. Login to your TBYB Account using the bar on the left\n"
-                   "3. Navigate to the '\U0001F527 Setup' tab and input the ID of the HuggingFace \U0001F917 T2I model you want to evaluate\n")
+                   "2. Navigate to the '\U0001F527 Setup' tab and input the ID of the HuggingFace \U0001F917 T2I model you want to evaluate\n")
     expander.image(Image.open('./assets/HF_MODEL_ID_EXAMPLE.png'))
-    expander.write("4. Test your chosen model by generating an image using an input prompt e.g.: 'A corgi with some cool sunglasses'\n")
+    expander.write("3. Test your chosen model by generating an image using an input prompt e.g.: 'A corgi with some cool sunglasses'\n")
     expander.image(Image.open('./assets/lykon_corgi.png'))
-    expander.write("5. Navigate to the '\U0001F30E Bias Evaluation (BEval)' or '\U0001F3AF Task-Oriented BEval' tabs "
+    expander.write("4. Navigate to the '\U0001F30E Bias Evaluation (BEval)' or '\U0001F3AF Task-Oriented BEval' tabs "
                    "   to evaluate your model once it has been loaded\n"
-                   "6. Once you have generated some evaluation images, head over to the '\U0001F4C1 Generated Images' tab to have a look at them\n"
-                   "7. To check out your evaluations or all of the TBYB Community evaluations, head over to the '\U0001F4CA Model Comparison' tab\n"
-                   "8. For more information about the evaluation process, see our paper on [ArXiv](https://arxiv.org/abs/2312.13053) or navigate to the "
+                   "5. Once you have generated some evaluation images, head over to the '\U0001F4C1 Generated Images' tab to have a look at them\n"
+                   "6. To check out your evaluations or all of the TBYB Community evaluations, head over to the '\U0001F4CA Model Comparison' tab\n"
+                   "7. For more information about the evaluation process, see our paper on [ArXiv](https://arxiv.org/abs/2312.13053) or navigate to the "
                    "   '\U0001F4F0 Additional Information' tab for a TL;DR.\n"
-                   "9. For any questions or to report any bugs/issues. Please contact [email protected].\n")
+                   "8. For any questions or to report any bugs/issues. Please contact [email protected].\n")
 
 def setup_additional_information_tab(tab):
     with tab:
@@ -276,12 +168,13 @@ def setup_additional_information_tab(tab):
             - Currently, a model_index.json file is required to load models and use them with TBYB, we will look to
             address other models in the future.
             - Target models must be public. Gated models are currently not supported.
-            - Images are generated using square resolutions based on user inputs. Width and height modifiers will be added soon.
-            - TBYB only works on T2I models hosted on HuggingFace, other model repositories are not currently supported
+            - TBYB only works on T2I models hosted on HuggingFace, other model repositories are not currently supported.
             - Adaptor models are currently not supported, we will look to add evaluation functionalities of these
             models in the future.
-            - Download, generation, inference and evaluation times are hardware dependent. We are currently deploying the
-            TBYB space on a T4 GPU. With more funding and interest (usage), we plan on deploying more powerful GPU options.
+            - Download, generation, inference and evaluation times are hardware and model dependent. We are currently deploying the
+            TBYB space on a T4 GPU. With more funding and interest (usage).
+            - BLIP and CLIP models used for evaluations are limited by their own biases and object recognition
+            capabilities. However, manual evaluations of bias could result in subjective labelling biases.   
             
             Keep in mind that these constraints may be removed or added to any time.
             """)
@@ -311,66 +204,59 @@ setup_page_banner()
 setup_how_to()
 
 
-if user_login_create():
-    tab1, tab2, tab3, tab4, tab5, tab6 = st.tabs(["\U0001F527 Setup", "\U0001F30E Bias Evaluation (BEval)", "\U0001F3AF Task-Oriented BEval.",
-                                           "\U0001F4CA Model Comparison", "\U0001F4C1 Generated Images", "\U0001F4F0 Additional Information"])
-    setup_additional_information_tab(tab6)
+tab1, tab2, tab3, tab4, tab5, tab6 = st.tabs(["\U0001F527 Setup", "\U0001F30E Bias Evaluation (BEval)", "\U0001F3AF Task-Oriented BEval.",
+                                       "\U0001F4CA Model Comparison", "\U0001F4C1 Generated Images", "\U0001F4F0 Additional Information"])
+setup_additional_information_tab(tab6)
 
-    # PLASTER THE LOGO EVERYWHERE
-    tab2.subheader("General Bias Evaluation")
-    tab2.write("Waiting for \U0001F527 Setup to be complete...")
-    tab3.subheader("Task-Oriented Bias Evaluation")
-    tab3.write("Waiting for \U0001F527 Setup to be complete...")
-    tab4.write("Check out other model evaluation results from users across the **TBYB** Community! \U0001F30E ")
-    tab4.write("You can also just compare your own model evaluations by clicking the '*Personal Evaluation*' buttons")
-    MCOMP.initialise_page(tab4)
-    tab5.subheader("Generated Images from General and Task-Oriented Bias Evaluations")
-    tab5.write("Waiting for \U0001F527 Setup to be complete...")
+# PLASTER THE LOGO EVERYWHERE
+tab2.subheader("General Bias Evaluation")
+tab2.write("Waiting for \U0001F527 Setup to be complete...")
+tab3.subheader("Task-Oriented Bias Evaluation")
+tab3.write("Waiting for \U0001F527 Setup to be complete...")
+tab4.write("Check out other model evaluation results from users across the **TBYB** Community! \U0001F30E ")
+tab4.write("You can also just compare your own model evaluations by clicking the '*Personal Evaluation*' buttons")
+MCOMP.initialise_page(tab4)
+tab5.subheader("Generated Images from General and Task-Oriented Bias Evaluations")
+tab5.write("Waiting for \U0001F527 Setup to be complete...")
 
-    with tab1:
-        with st.form("model_definition_form", clear_on_submit=True):
-            modelID = st.text_input('Input the HuggingFace \U0001F917 T2I model_id for the model you '
-                                    'want to analyse e.g.: "runwayml/stable-diffusion-v1-5"')
-            submitted1 = st.form_submit_button("Submit")
-            if modelID:
-                with st.spinner('Checking if ' + modelID + ' is valid and downloading it (if required)'):
-                    modelLoaded = MLOAD.check_if_model_exists(modelID)
-                    if modelLoaded is not None:
-                        # st.write("Located " + modelID + " model_index.json file")
-                        st.write("Located " + modelID)
+with tab1:
+    with st.form("model_definition_form", clear_on_submit=True):
+        modelID = st.text_input('Input the HuggingFace \U0001F917 T2I model_id for the model you '
+                                'want to analyse e.g.: "runwayml/stable-diffusion-v1-5"')
+        submitted1 = st.form_submit_button("Submit")
+        if modelID:
+            with st.spinner('Checking if ' + modelID + ' is valid and downloading it (if required)'):
+                modelLoaded = MLOAD.check_if_model_exists(modelID)
+                if modelLoaded is not None:
+                    # st.write("Located " + modelID + " model_index.json file")
+                    st.write("Located " + modelID)
 
-                        modelType = MLOAD.get_model_info(modelLoaded)
-                        if modelType is not None:
-                            st.write("Model is of Type: ", modelType)
+                    modelType = MLOAD.get_model_info(modelLoaded)
+                    if modelType is not None:
+                        st.write("Model is of Type: ", modelType)
 
-                            if submitted1:
-                                MINFER.TargetModel = MLOAD.import_model(modelID, modelType)
-                                if MINFER.TargetModel is not None:
-                                    st.write("Text-to-image pipeline looks like this:")
-                                    st.write(MINFER.TargetModel)
-                                    user_evaluation_variables.MODEL = modelID
-                                    user_evaluation_variables.MODEL_TYPE = modelType
-                    else:
-                        st.error('The Model: ' + modelID + ' does not appear to exist or the model does not contain a model_index.json file.'
-                                                           ' Please check that that HuggingFace repo ID is valid.'
-                                                           ' For more help, please see the "How to Use" Tab above.', icon="🚨")
-        if modelID:
-            with st.form("example_image_gen_form", clear_on_submit=True):
-                testPrompt = st.text_input('Input a random test prompt to test out your '
-                                           'chosen model and see if its generating images:')
-                submitted2 = st.form_submit_button("Submit")
-                if testPrompt and submitted2:
-                    with st.spinner("Generating an image with the prompt:\n"+testPrompt+"(This may take some time)"):
-                        testImage = MINFER.generate_test_image(MINFER.TargetModel, testPrompt)
-                    st.image(testImage, caption='Model: ' + modelID + ' Prompt: ' + testPrompt)
-                    st.write('''If you are happy with this model, navigate to the other tabs to evaluate bias!
-                                  Otherwise, feel free to load up a different model and run it again''')
+                        if submitted1:
+                            MINFER.TargetModel = MLOAD.import_model(modelID, modelType)
+                            if MINFER.TargetModel is not None:
+                                st.write("Text-to-image pipeline looks like this:")
+                                st.write(MINFER.TargetModel)
+                                user_evaluation_variables.MODEL = modelID
+                                user_evaluation_variables.MODEL_TYPE = modelType
+                else:
+                    st.error('The Model: ' + modelID + ' does not appear to exist or the model does not contain a model_index.json file.'
+                                                       ' Please check that that HuggingFace repo ID is valid.'
+                                                       ' For more help, please see the "How to Use" Tab above.', icon="🚨")
+    if modelID:
+        with st.form("example_image_gen_form", clear_on_submit=True):
+            testPrompt = st.text_input('Input a random test prompt to test out your '
+                                       'chosen model and see if its generating images:')
+            submitted2 = st.form_submit_button("Submit")
+            if testPrompt and submitted2:
+                with st.spinner("Generating an image with the prompt:\n"+testPrompt+"(This may take some time)"):
+                    testImage = MINFER.generate_test_image(MINFER.TargetModel, testPrompt)
+                st.image(testImage, caption='Model: ' + modelID + ' Prompt: ' + testPrompt)
+                st.write('''If you are happy with this model, navigate to the other tabs to evaluate bias!
+                              Otherwise, feel free to load up a different model and run it again''')
 
-        if MINFER.TargetModel is not None:
-            tab_manager.completed_setup([tab2, tab3, tab4, tab5], modelID)
-else:
-    MCOMP.databaseDF = None
-    user_evaluation_variables.reset_variables('general')
-    user_evaluation_variables.reset_variables('task-oriented')
-    st.write('')
-    st.warning('Log in or register your email to get started! ', icon="⚠️")
+    if MINFER.TargetModel is not None:
+        tab_manager.completed_setup([tab2, tab3, tab4, tab5], modelID)