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import pandas as pd |
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import streamlit as st |
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from my_model.tabs.run_inference import InferenceRunner |
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from my_model.state_manager import StateManager |
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class UIManager(): |
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"""Manages the user interface for the Streamlit application.""" |
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def __init__(self): |
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"""Initializes the UIManager with predefined tabs.""" |
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self.tabs = { |
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"Home": self.display_home, |
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"Dataset Analysis": self.display_dataset_analysis, |
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"Finetuning and Evaluation Results": self.display_finetuning_evaluation, |
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"Run Inference": self.display_run_inference, |
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"Dissertation Report": self.display_dissertation_report, |
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"Code": self.display_code, |
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"More Pages will follow .. ": self.display_placeholder |
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} |
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state_manager = StateManager() |
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state_manager.initialize_state() |
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def add_tab(self, tab_name, display_function): |
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"""Adds a new tab to the UI.""" |
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self.tabs[tab_name] = display_function |
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def display_sidebar(self): |
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"""Displays the sidebar for navigation.""" |
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st.sidebar.title("Navigation") |
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selection = st.sidebar.radio("Go to", list(self.tabs.keys()), disabled=st.session_state['loading_in_progress']) |
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return selection |
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def display_selected_page(self, selection): |
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"""Displays the selected page based on user's choice.""" |
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if selection in self.tabs: |
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self.tabs[selection]() |
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def display_home(self): |
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"""Displays the Home page of the application.""" |
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st.title('MultiModal Learning for Visual Question Answering using World Knowledge') |
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st.text('') |
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st.header('(Knowledge-Based Visual Question Answering)') |
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st.text('') |
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st.text('') |
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st.text('') |
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st.write("""\n\n\n\nThis is an interactive application developed to demonstrate my project as part of the dissertation for Masters degree in Artificial Intelligence at the [University of Bath](https://www.bath.ac.uk/). |
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\n\n\nDeveloped by: [Mohammed H AlHaj](https://www.linkedin.com/in/m7mdal7aj) | Dissertation Supervisor: [Andreas Theophilou](https://researchportal.bath.ac.uk/en/persons/andreas-theophilou) |
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\n\nFurther details will be updated later . .""") |
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def display_dataset_analysis(self): |
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"""Displays the Dataset Analysis page.""" |
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st.title("OK-VQA Dataset Analysis") |
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st.write("This is a Place Holder until the contents are uploaded.") |
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def display_finetuning_evaluation(self): |
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"""Displays the Finetuning and Evaluation Results page.""" |
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st.title("Finetuning and Evaluation Results") |
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st.write("This is a Place Holder until the contents are uploaded.") |
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def display_run_inference(self): |
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"""Displays the Run Inference page.""" |
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st.title("Run Inference") |
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st.write("Please note that this is not a general purpose model, it is specifically trained on [OK-VQA Dataset](https://okvqa.allenai.org/) and desgined to give short and direct answers to the given questions about the given image.") |
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st.write("\n") |
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inference_runner = InferenceRunner() |
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inference_runner.run_inference() |
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def display_dissertation_report(self): |
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"""Displays the Dissertation Report page.""" |
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st.title("Dissertation Report") |
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st.write("Click the link below to view the PDF.") |
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st.download_button( |
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label="Download PDF", |
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data=open("Files/Dissertation Report.pdf", "rb"), |
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file_name="example.pdf", |
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mime="application/octet-stream" |
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) |
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def display_code(self): |
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"""Displays the Code page with a link to the project's code repository.""" |
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st.title("Code") |
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st.markdown("You can view the code for this project on HuggingFace Space files page.") |
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st.markdown("[View Code](https://huggingface.co/spaces/m7mdal7aj/Mohammed_Alhaj_PlayGround/tree/main)", unsafe_allow_html=True) |
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def display_placeholder(self): |
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"""Displays a placeholder for future content.""" |
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st.title("Stay Tuned") |
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st.write("This is a Place Holder until the contents are uploaded.") |
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