import streamlit as st from my_model.tabs.run_inference import run_inference class UIManager: def __init__(self): 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 } def add_tab(self, tab_name, display_function): self.tabs[tab_name] = display_function def display_sidebar(self): st.sidebar.title("Navigation") selection = st.sidebar.radio("Go to", list(self.tabs.keys())) st.sidebar.write("More Pages will follow .. ") return selection def display_selected_page(self, selection): if selection in self.tabs: self.tabs[selection]() def display_home(self): st.title("MultiModal Learning for Knowledge-Based Visual Question Answering") st.write("""This application is an interactive element of the project and prepared by Mohammed Alhaj as part of the dissertation for Masters degree in Artificial Intelligence at the University of Bath. Further details will be updated later""") def display_dataset_analysis(self): st.title("OK-VQA Dataset Analysis") st.write("This is a Place Holder until the contents are uploaded.") def display_finetuning_evaluation(self): st.title("Finetuning and Evaluation Results") st.write("This is a Place Holder until the contents are uploaded.") def display_run_inference(self): run_inference() def display_dissertation_report(self): st.title("Dissertation Report") st.write("Click the link below to view the PDF.") 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): st.title("Code") st.markdown("You can view the code for this project on the Hugging Face Space file page.") st.markdown("[View Code](https://huggingface.co/spaces/m7mdal7aj/Mohammed_Alhaj_PlayGround/tree/main)", unsafe_allow_html=True) def display_placeholder(self): st.title("Stay Tuned") st.write("This is a Place Holder until the contents are uploaded.") class StateManager: def __init__(self): self.reset_state() def reset_state(self): """Resets the state to its initial values.""" self.current_image = None self.qa_history = [] self.analysis_done = False self.answer_in_progress = False self.caption = "" self.detected_objects_str = "" def set_current_image(self, image): """Sets the current image and resets relevant state variables.""" try: self.current_image = image self.qa_history = [] self.analysis_done = False self.answer_in_progress = False self.caption = "" self.detected_objects_str = "" except Exception as e: print(f"Error setting current image: {e}") def add_to_qa_history(self, question, answer): """Adds a question-answer pair to the history.""" if question and answer: self.qa_history.append((question, answer)) else: print("Invalid question or answer. Cannot add to history.") def set_analysis_done(self, status=True): """Sets the analysis status.""" self.analysis_done = status def set_answer_in_progress(self, status=True): """Sets the answer in progress status.""" self.answer_in_progress = status def set_caption(self, caption): """Sets the image caption.""" if caption: self.caption = caption else: print("Invalid caption. Cannot set caption.") def set_detected_objects_str(self, detected_objects_str): """Sets the detected objects string.""" if detected_objects_str: self.detected_objects_str = detected_objects_str else: print("Invalid detected objects string. Cannot set detected objects.")