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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
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,
"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, 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'])
st.sidebar.image("Files/mm.jpeg", use_column_width=True)
st.sidebar.markdown("**[Mohammed H AlHaj](https://www.linkedin.com/in/m7mdal7aj)**")
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."""
run_home()
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_results(self):
"""Displays Evaluation Results page."""
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_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.\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_KB-VQA/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.")
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