mirror of
https://github.com/THU-MIG/yolov10.git
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Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com> Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com> Co-authored-by: Haixuan Xavier Tao <tao.xavier@outlook.com>
227 lines
8.8 KiB
Python
227 lines
8.8 KiB
Python
# Ultralytics YOLO 🚀, AGPL-3.0 license
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import time
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from threading import Thread
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import pandas as pd
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from ultralytics import Explorer
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from ultralytics.utils import ROOT, SETTINGS
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from ultralytics.utils.checks import check_requirements
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check_requirements(('streamlit>=1.29.0', 'streamlit-select>=0.2'))
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import streamlit as st
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from streamlit_select import image_select
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def _get_explorer():
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"""Initializes and returns an instance of the Explorer class."""
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exp = Explorer(data=st.session_state.get('dataset'), model=st.session_state.get('model'))
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thread = Thread(target=exp.create_embeddings_table,
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kwargs={'force': st.session_state.get('force_recreate_embeddings')})
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thread.start()
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progress_bar = st.progress(0, text='Creating embeddings table...')
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while exp.progress < 1:
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time.sleep(0.1)
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progress_bar.progress(exp.progress, text=f'Progress: {exp.progress * 100}%')
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thread.join()
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st.session_state['explorer'] = exp
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progress_bar.empty()
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def init_explorer_form():
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"""Initializes an Explorer instance and creates embeddings table with progress tracking."""
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datasets = ROOT / 'cfg' / 'datasets'
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ds = [d.name for d in datasets.glob('*.yaml')]
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models = [
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'yolov8n.pt', 'yolov8s.pt', 'yolov8m.pt', 'yolov8l.pt', 'yolov8x.pt', 'yolov8n-seg.pt', 'yolov8s-seg.pt',
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'yolov8m-seg.pt', 'yolov8l-seg.pt', 'yolov8x-seg.pt', 'yolov8n-pose.pt', 'yolov8s-pose.pt', 'yolov8m-pose.pt',
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'yolov8l-pose.pt', 'yolov8x-pose.pt']
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with st.form(key='explorer_init_form'):
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col1, col2 = st.columns(2)
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with col1:
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st.selectbox('Select dataset', ds, key='dataset', index=ds.index('coco128.yaml'))
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with col2:
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st.selectbox('Select model', models, key='model')
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st.checkbox('Force recreate embeddings', key='force_recreate_embeddings')
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st.form_submit_button('Explore', on_click=_get_explorer)
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def query_form():
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"""Sets up a form in Streamlit to initialize Explorer with dataset and model selection."""
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with st.form('query_form'):
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col1, col2 = st.columns([0.8, 0.2])
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with col1:
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st.text_input('Query',
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"WHERE labels LIKE '%person%' AND labels LIKE '%dog%'",
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label_visibility='collapsed',
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key='query')
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with col2:
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st.form_submit_button('Query', on_click=run_sql_query)
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def ai_query_form():
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"""Sets up a Streamlit form for user input to initialize Explorer with dataset and model selection."""
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with st.form('ai_query_form'):
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col1, col2 = st.columns([0.8, 0.2])
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with col1:
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st.text_input('Query', 'Show images with 1 person and 1 dog', label_visibility='collapsed', key='ai_query')
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with col2:
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st.form_submit_button('Ask AI', on_click=run_ai_query)
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def find_similar_imgs(imgs):
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"""Initializes a Streamlit form for AI-based image querying with custom input."""
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exp = st.session_state['explorer']
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similar = exp.get_similar(img=imgs, limit=st.session_state.get('limit'), return_type='arrow')
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paths = similar.to_pydict()['im_file']
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st.session_state['imgs'] = paths
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def similarity_form(selected_imgs):
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"""Initializes a form for AI-based image querying with custom input in Streamlit."""
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st.write('Similarity Search')
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with st.form('similarity_form'):
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subcol1, subcol2 = st.columns([1, 1])
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with subcol1:
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st.number_input('limit',
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min_value=None,
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max_value=None,
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value=25,
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label_visibility='collapsed',
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key='limit')
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with subcol2:
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disabled = not len(selected_imgs)
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st.write('Selected: ', len(selected_imgs))
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st.form_submit_button(
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'Search',
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disabled=disabled,
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on_click=find_similar_imgs,
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args=(selected_imgs, ),
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)
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if disabled:
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st.error('Select at least one image to search.')
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# def persist_reset_form():
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# with st.form("persist_reset"):
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# col1, col2 = st.columns([1, 1])
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# with col1:
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# st.form_submit_button("Reset", on_click=reset)
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#
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# with col2:
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# st.form_submit_button("Persist", on_click=update_state, args=("PERSISTING", True))
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def run_sql_query():
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"""Executes an SQL query and returns the results."""
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st.session_state['error'] = None
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query = st.session_state.get('query')
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if query.rstrip().lstrip():
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exp = st.session_state['explorer']
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res = exp.sql_query(query, return_type='arrow')
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st.session_state['imgs'] = res.to_pydict()['im_file']
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def run_ai_query():
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"""Execute SQL query and update session state with query results."""
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if not SETTINGS['openai_api_key']:
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st.session_state[
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'error'] = 'OpenAI API key not found in settings. Please run yolo settings openai_api_key="..."'
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return
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st.session_state['error'] = None
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query = st.session_state.get('ai_query')
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if query.rstrip().lstrip():
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exp = st.session_state['explorer']
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res = exp.ask_ai(query)
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if not isinstance(res, pd.DataFrame) or res.empty:
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st.session_state['error'] = 'No results found using AI generated query. Try another query or rerun it.'
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return
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st.session_state['imgs'] = res['im_file'].to_list()
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def reset_explorer():
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"""Resets the explorer to its initial state by clearing session variables."""
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st.session_state['explorer'] = None
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st.session_state['imgs'] = None
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st.session_state['error'] = None
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def utralytics_explorer_docs_callback():
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"""Resets the explorer to its initial state by clearing session variables."""
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with st.container(border=True):
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st.image('https://raw.githubusercontent.com/ultralytics/assets/main/logo/Ultralytics_Logotype_Original.svg',
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width=100)
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st.markdown(
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"<p>This demo is built using Ultralytics Explorer API. Visit <a href='https://docs.ultralytics.com/datasets/explorer/'>API docs</a> to try examples & learn more</p>",
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unsafe_allow_html=True,
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help=None)
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st.link_button('Ultrlaytics Explorer API', 'https://docs.ultralytics.com/datasets/explorer/')
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def layout():
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"""Resets explorer session variables and provides documentation with a link to API docs."""
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st.set_page_config(layout='wide', initial_sidebar_state='collapsed')
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st.markdown("<h1 style='text-align: center;'>Ultralytics Explorer Demo</h1>", unsafe_allow_html=True)
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if st.session_state.get('explorer') is None:
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init_explorer_form()
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return
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st.button(':arrow_backward: Select Dataset', on_click=reset_explorer)
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exp = st.session_state.get('explorer')
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col1, col2 = st.columns([0.75, 0.25], gap='small')
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imgs = []
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if st.session_state.get('error'):
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st.error(st.session_state['error'])
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else:
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imgs = st.session_state.get('imgs') or exp.table.to_lance().to_table(columns=['im_file']).to_pydict()['im_file']
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total_imgs, selected_imgs = len(imgs), []
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with col1:
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subcol1, subcol2, subcol3, subcol4, subcol5 = st.columns(5)
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with subcol1:
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st.write('Max Images Displayed:')
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with subcol2:
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num = st.number_input('Max Images Displayed',
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min_value=0,
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max_value=total_imgs,
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value=min(500, total_imgs),
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key='num_imgs_displayed',
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label_visibility='collapsed')
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with subcol3:
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st.write('Start Index:')
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with subcol4:
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start_idx = st.number_input('Start Index',
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min_value=0,
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max_value=total_imgs,
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value=0,
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key='start_index',
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label_visibility='collapsed')
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with subcol5:
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reset = st.button('Reset', use_container_width=False, key='reset')
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if reset:
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st.session_state['imgs'] = None
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st.experimental_rerun()
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query_form()
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ai_query_form()
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if total_imgs:
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imgs_displayed = imgs[start_idx:start_idx + num]
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selected_imgs = image_select(
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f'Total samples: {total_imgs}',
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images=imgs_displayed,
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use_container_width=False,
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# indices=[i for i in range(num)] if select_all else None,
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)
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with col2:
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similarity_form(selected_imgs)
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# display_labels = st.checkbox("Labels", value=False, key="display_labels")
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utralytics_explorer_docs_callback()
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if __name__ == '__main__':
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layout()
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