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| import streamlit as st | |
| import streamlit.components.v1 as components | |
| import pandas as pd | |
| from my_model.tabs.run_inference import InferenceRunner | |
| from my_model.tabs.results import run_demo | |
| from my_model.tabs.home import run_home | |
| from my_model.state_manager import StateManager | |
| from my_model.tabs.dataset_analysis import run_dataset_analyzer | |
| from my_model.tabs.model_arch import run_model_arch | |
| class UIManager(): | |
| """ | |
| Manages the user interface for the Streamlit application. | |
| This class handles the creation and navigation of various tabs in the Streamlit app. It provides methods to add new | |
| tabs, display the sidebar, and render the content of the selected tab. | |
| Attributes: | |
| tabs (dict): A dictionary mapping tab names to their corresponding display functions. | |
| """ | |
| def __init__(self)-> None: | |
| """ | |
| Initializes the UIManager with predefined tabs. | |
| This method sets up the initial tabs for the application and initializes the state manager. | |
| """ | |
| self.tabs = { | |
| "Home": self.display_home, | |
| "Dataset Analysis": self.display_dataset_analysis, | |
| "Model Architecture": self.display_model_arch, | |
| "Results": self.display_results, | |
| "Run Inference": self.display_run_inference, | |
| "Dissertation Report": self.display_dissertation_report, | |
| "Code": self.display_code | |
| } | |
| state_manager = StateManager() | |
| state_manager.initialize_state() | |
| def add_tab(self, tab_name: str, display_function: callable) -> None: | |
| """ | |
| Adds a new tab to the UI. | |
| Args: | |
| tab_name (str): The name of the new tab. | |
| display_function (callable): The function to be called when the tab is selected. | |
| Returns: | |
| None | |
| """ | |
| self.tabs[tab_name] = display_function | |
| def display_sidebar(self) -> str: | |
| """ | |
| Displays the sidebar for navigation. | |
| This method creates a sidebar with navigation options and returns the user's selection. | |
| Returns: | |
| str: The name of the selected tab. | |
| """ | |
| st.sidebar.image("Files/logo.jpg") | |
| st.sidebar.title("Navigation") | |
| selection = st.sidebar.radio("Go to", list(self.tabs.keys()), disabled=st.session_state['loading_in_progress']) | |
| st.sidebar.image("Files/mm.jpeg", use_column_width=True) | |
| st.sidebar.markdown( | |
| """ | |
| <div style="text-align: center;"> | |
| <a href="https://www.linkedin.com/in/m7mdal7aj" style="font-weight: bold; text-decoration: none;">Mohammed Bin Ali AlHaj</a> | |
| </div> | |
| """, | |
| unsafe_allow_html=True | |
| ) | |
| return selection | |
| def display_selected_page(self, selection: str) -> None: | |
| """ | |
| Displays the selected page based on the user's choice. | |
| Args: | |
| selection (str): The name of the selected tab. | |
| Returns: | |
| None | |
| """ | |
| if selection in self.tabs: | |
| self.tabs[selection]() | |
| def display_home(self) -> None: | |
| """ | |
| Displays the Home page of the application. | |
| Returns: | |
| None | |
| """ | |
| st.markdown("<h1 style='text-align: center;'>Multimodal Learning for Visual Question Answering using World Knowledge</h1>", unsafe_allow_html=True) | |
| st.markdown("<h2 style='text-align: center;'>Knowledge-Based Visual Question Answering - KBVQA</h2>", unsafe_allow_html=True) | |
| run_home() | |
| def display_dataset_analysis(self) -> None: | |
| """ | |
| Displays the Dataset Analysis page. | |
| This page provides an overview of various KB-VQA datasets and analyses of the OK-VQA dataset. | |
| Returns: | |
| None | |
| """ | |
| st.title("Dataset Analysis") | |
| st.write("""This page shows an overview of some of the KB-VQA datasets, and various analysis of | |
| the [OK-VQA Dataset](https://okvqa.allenai.org/) that this KB-VQA model was fine-tuned | |
| and evaluated on.""") | |
| run_dataset_analyzer() | |
| def display_results(self) -> None: | |
| """ | |
| Displays the Evaluation Results page. | |
| This page demonstrates the model evaluation results and analyses in an interactive way. | |
| Returns: | |
| None | |
| """ | |
| st.title("Evaluation Results & Analyses") | |
| st.write("This page demonstrates the model evaluation results and analyses in an interactive way.") | |
| st.write("\n") | |
| run_demo() | |
| def display_model_arch(self) -> None: | |
| """ | |
| Displays the Model Architecture page. | |
| This page provides detailed information about the model architecture. | |
| Returns: | |
| None | |
| """ | |
| st.title("Model Architecture") | |
| st.write("This page shows the detailed Model Architecture.") | |
| st.write("\n") | |
| run_model_arch() | |
| def display_run_inference(self) -> None: | |
| """ | |
| Displays the Run Inference page. | |
| This page allows users to run inference using the fine-tuned model on the OK-VQA dataset. | |
| Returns: | |
| None | |
| """ | |
| 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.\n""") | |
| st.write("""**Note:** To load and run this model, the space must be configured to run on a GPU. | |
| If the space is not set to run on a GPU, please contact me.""") | |
| inference_runner = InferenceRunner() | |
| inference_runner.run_inference() | |
| def display_dissertation_report(self) -> None: | |
| """ | |
| Displays the Dissertation Report page. | |
| This page provides a link to download the dissertation report PDF. | |
| Returns: | |
| None | |
| """ | |
| 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="KB-VQA Dissertation Report for Mohammed Bin Ali Alhaj.pdf", | |
| mime="application/octet-stream" | |
| ) | |
| def display_code(self) -> None: | |
| """ | |
| Displays the Code page with a link to the project's code repository. | |
| Returns: | |
| None | |
| """ | |
| st.title("Code") | |
| st.markdown("You can view the code for this project on HuggingFace repository.") | |
| st.markdown("[View Code](https://huggingface.co/spaces/m7mdal7aj/KB-VQA/tree/main)", unsafe_allow_html=True) | |
| def display_placeholder(self) -> None: | |
| """ | |
| Displays a placeholder for future content. | |
| Returns: | |
| None | |
| """ | |
| st.title("Stay Tuned") | |
| st.write("This is a Place Holder until the contents are uploaded.") | |