| import gradio as gr |
| from dataclasses import dataclass |
| import sqlite3 |
| import random |
| from utils.git_utils.tsv_io import TSVFile |
| import json |
| from PIL import Image |
| import io |
| import base64 |
| import pandas as pd |
| import datetime |
| import os |
|
|
| db_path = "tmp/annotations.db" |
| |
| columns = [ |
| "caption", |
| "conf", |
| "area", |
| "image_area", |
| "clip_score", |
| "image_id", |
| "region_cnt", |
| "region_id", |
| "is_acceptable", |
| "created_at", |
| ] |
|
|
| conn = sqlite3.connect(db_path) |
| reviews = conn.execute("SELECT * FROM annotations").fetchall() |
| reviews = pd.DataFrame(reviews, columns=columns) |
|
|
| reviews.to_csv("tmp/annotations.csv", index=False) |
|
|
|
|
| """ |
| # How to get the table names? |
| import sqlite3 |
| |
| conn = sqlite3.connect('your_database_name.db') |
| cursor = conn.cursor() |
| |
| cursor.execute("SELECT name FROM sqlite_master WHERE type='table';") |
| |
| # Fetch all rows from the result set and extract the table names |
| tables_info = cursor.fetchall() |
| table_names = [info[0] for info in tables_info] |
| |
| print(table_names) |
| |
| conn.close() |
| |
| |
| # How to get the column names? |
| import sqlite3 |
| |
| conn = sqlite3.connect('your_database_name.db') |
| cursor = conn.cursor() |
| |
| table_name = 'your_table_name' |
| cursor.execute(f'PRAGMA table_info({table_name});') |
| |
| # Fetch all rows from the result set and extract the column names |
| columns_info = cursor.fetchall() |
| column_names = [info[1] for info in columns_info] |
| |
| print(column_names) |
| |
| conn.close() |
| """ |
|
|