import pandas as pd import streamlit as st from my_model.tabs.run_inference import InferenceRunner from my_model.tabs.finetuning_evaluation import KBVQAEvaluator from my_model.state_manager import StateManager class UIManager(): """Manages the user interface for the Streamlit application.""" def __init__(self): """Initializes the UIManager with predefined tabs.""" self.tabs = { "Home": self.display_home, "Dataset Analysis": self.display_dataset_analysis, "Finetuning and Evaluation Results": self.display_finetuning_evaluation, "Run Inference": self.display_run_inference, "Dissertation Report": self.display_dissertation_report, "Code": self.display_code, "More Pages will follow .. ": self.display_placeholder } state_manager = StateManager() state_manager.initialize_state() def add_tab(self, tab_name, display_function): """Adds a new tab to the UI.""" self.tabs[tab_name] = display_function def display_sidebar(self): """Displays the sidebar for navigation.""" st.sidebar.title("Navigation") selection = st.sidebar.radio("Go to", list(self.tabs.keys()), disabled=st.session_state['loading_in_progress']) return selection def display_selected_page(self, selection): """Displays the selected page based on user's choice.""" if selection in self.tabs: self.tabs[selection]() def display_home(self): """Displays the Home page of the application.""" st.title('MultiModal Learning for Visual Question Answering using World Knowledge') st.text('') st.header('(Knowledge-Based Visual Question Answering)') st.text('') st.text('') st.text('') 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/). \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) \n\nFurther details will be updated later . .""") def display_dataset_analysis(self): """Displays the Dataset Analysis page.""" st.title("OK-VQA Dataset Analysis") st.write("This is a Place Holder until the contents are uploaded.") def display_finetuning_evaluation(self): """Displays the Finetuning and Evaluation Results page.""" st.title("Finetuning and Evaluation Results") st.write("This page demonstrates the fine-tuning and model evaluation results") st.write("\n") evaluator = KBVQAEvaluator() evaluator.run() def display_run_inference(self): """Displays the Run Inference page.""" st.title("Run Inference") 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.") st.write("\n") inference_runner = InferenceRunner() inference_runner.run_inference() def display_dissertation_report(self): """Displays the Dissertation Report page.""" st.title("Dissertation Report") st.write("Click the link below to view the PDF.") # Error handling for file access should be considered here st.download_button( label="Download PDF", data=open("Files/Dissertation Report.pdf", "rb"), file_name="example.pdf", mime="application/octet-stream" ) def display_code(self): """Displays the Code page with a link to the project's code repository.""" st.title("Code") st.markdown("You can view the code for this project on HuggingFace Space files page.") st.markdown("[View Code](https://huggingface.co/spaces/m7mdal7aj/Mohammed_Alhaj_PlayGround/tree/main)", unsafe_allow_html=True) def display_placeholder(self): """Displays a placeholder for future content.""" st.title("Stay Tuned") st.write("This is a Place Holder until the contents are uploaded.")