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import clip
import json
import pandas as pd
import streamlit as st
import torch
import time
from utils import get_local_files
def preference_selection():
annotation_projects = get_local_files("annotations/", get_details=True)
if not annotation_projects:
st.warning("No annotated data found.")
return
annotation_projects_df = pd.DataFrame(annotation_projects)
annotation_projects_df['file_created'] = annotation_projects_df['file_created'].dt.strftime("%Y-%m-%d %H:%M:%S")
annotation_projects_df['display_text'] = annotation_projects_df.apply(lambda x: f"ID: {x['file_name']} | Time Created: ({x['file_created']})", axis=1)
annotation_project = st.selectbox("Select Annotation Project", options=annotation_projects_df['display_text'].tolist())
annotation_project = annotation_projects_df[annotation_projects_df['display_text'] == annotation_project].iloc[0]
with open(f"annotations/{annotation_project['file_name']}/annotations.json", "r") as f:
annotations_dict: dict = json.load(f)
annotations_df = pd.DataFrame(annotations_dict.items(), columns=['image_path', 'annotation'])
annotations_df['image_path'] = annotations_df['image_path'].apply(lambda x: x.split('/')[-1])
cols = st.columns(5)
for i, row in annotations_df.head(4).iterrows():
with cols[i]:
st.image(f"images/{row['image_path']}", caption=row['annotation'])
if len(annotations_df) > 4:
with cols[4]:
st.info(f"and more {len(annotations_df) - 4} images...")
save_preference = st.button("Save Preferences")
if save_preference:
st.session_state['selected_dataset'] = annotation_project['file_name']
st.success("Preferences Saved Successfully.")
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