117 lines
3.7 KiB
Python
117 lines
3.7 KiB
Python
# streamlit_app.py
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import os
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import pandas as pd
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import streamlit as st
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from loguru import logger
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from bak.init_data import BatchDataRead
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from db_utils import BatchData, session
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BASE_CKPT_DIR = "./bak"
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RUN_MODE = {
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1: 'lbs模式',
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2: 'lbs优先模式',
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3: '不使用lbs'
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}
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PAGE_TITLE = "training data configer"
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st.set_page_config(
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page_title=PAGE_TITLE,
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page_icon="🧊",
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layout="wide",
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initial_sidebar_state="expanded",
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)
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@st.cache_data
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def list_ckpt_paths(dir_path):
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return os.listdir(dir_path)
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def get_data_from_db():
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logger.debug("init")
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db_objs = session.query(BatchData).all()
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return [BatchDataRead.from_orm(db_obj).dict() for db_obj in db_objs]
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st.session_state.setdefault('data_table', [])
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st.session_state.setdefault('username', '')
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st.session_state.setdefault('evolve_r', 0.2)
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st.session_state.setdefault('n_trail', 10)
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st.session_state.setdefault('n_epoch', 2)
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st.session_state.setdefault('ckpt_path', list_ckpt_paths(BASE_CKPT_DIR)[0])
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st.session_state.setdefault('mode', 2)
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st.session_state.setdefault('configs', {
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k: st.session_state[k] for k in ('evolve_r', 'n_trail', 'n_epoch', 'ckpt_path', 'mode')
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})
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if not st.session_state.data_table:
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st.session_state.data_table = get_data_from_db()
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df = pd.DataFrame(data=st.session_state.data_table)
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left_col, right_col = st.columns([3, 1])
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def train():
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st.session_state.configs['evolve_r'] = st.session_state.evolve_r
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def update_handler():
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edited_rows = st.session_state.edited_info.get('edited_rows')
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for id_, update_data in edited_rows.items():
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row_id = int(edited_df.loc[id_].id)
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row_db = session.query(BatchData).where(BatchData.id == row_id).first()
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logger.info(f"{row_id=}, {update_data=}")
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logger.debug(BatchDataRead.from_orm(row_db))
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for field in update_data:
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setattr(row_db, field, update_data[field])
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session.commit()
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def update_config(*args, **kwargs):
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return None
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with left_col:
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edited_df = st.data_editor(
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df, key="edited_info",
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num_rows="dynamic",
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height=600,
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hide_index=True,
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use_container_width=True,
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on_change=update_handler,
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column_order=(
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'id', 'year', 'census_batch', 'id_code', 'precision', 'is_train', 'is_validation', 'ann_file', 'ann_file_lbs', 'img_prefix',),
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column_config={
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"year": st.column_config.NumberColumn("年份", format="%d 年", ),
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'census_batch': "普查批次",
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'id_code': "编号",
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'precision': "精度",
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'is_train': "是否是训练集",
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'is_validation': "是否是验证集",
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'ann_file': st.column_config.Column("path", width='medium'),
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'ann_file_lbs': st.column_config.Column("lbs_path", width='medium'),
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'img_prefix': st.column_config.Column("img_prefix", width='medium'),
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})
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with right_col:
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st.slider(label='evolve_r', key='evolve_r',
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min_value=0.0, max_value=0.5, step=0.01,
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on_change=update_config)
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st.selectbox(label='n_trail', key='n_trail',
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options=(i for i in range(10, 51, 10)))
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st.selectbox(label='n_epoch', key='n_epoch',
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options=(i for i in range(1, 6)))
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st.selectbox(label='ckpt_path', key='ckpt_path',
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options=(list_ckpt_paths(BASE_CKPT_DIR)))
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st.selectbox(label='mode', key='mode',
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format_func=lambda x: RUN_MODE[x],
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options=RUN_MODE,
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on_change=update_config)
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st.json({
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k: st.session_state[k] for k in ('evolve_r', 'n_trail', 'n_epoch', 'ckpt_path', 'mode')
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})
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st.divider()
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st.button("启动", on_click=train)
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