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import os
import glob
import time
import pandas as pd
from sqlalchemy import create_engine, Table, Column, String, Integer, DateTime, Float, func
from sqlalchemy.orm import sessionmaker
from sqlalchemy.ext.declarative import declarative_base
from app.utils.file_utils import load_recipe, load_csv_safe
from app.settings import app_cfg as cfg
connection_url = "mysql+mysqlconnector://{}:{}@{}/{}?charset=utf8mb4".format(
os.getenv("DB_USER"),
os.getenv("DB_PASS"),
os.getenv("DB_HOST"),
os.getenv("DB_NAME")
)
loaded = False
Session = None
class FileRecord(self.base_model):
__tablename__ = self.name + "_file_record"
id = Column(Integer, primary_key=True)
ext = Column(String(3, convert_unicode=True), nullable=False)
fn = Column(String(36, convert_unicode=True), nullable=False)
identity_key = Column(String(36, convert_unicode=True), nullable=False)
sha256 = Column(String(36, convert_unicode=True), nullable=False)
def toJSON(self):
return {
'id': self.id,
'uuid': self.uuid,
'identity_id': self.identity_id,
}
def load_sql_datasets(replace=False, base_model=None):
global datasets, loaded, Session
if loaded:
return datasets
engine = create_engine(connection_url, encoding="utf-8", pool_recycle=3600)
# db.set_character_set('utf8')
# dbc = db.cursor()
# dbc.execute('SET NAMES utf8;')
# dbc.execute('SET CHARACTER SET utf8;')
# dbc.execute('SET character_set_connection=utf8;')
Session = sessionmaker(bind=engine)
for path in glob.iglob(os.path.join(cfg.DIR_FAISS_METADATA, "*")):
dataset = load_sql_dataset(path, replace, engine, base_model)
datasets[dataset.name] = dataset
loaded = True
return datasets
def load_sql_dataset(path, replace=False, engine=None, base_model=None):
name = os.path.basename(path)
dataset = SqlDataset(name, base_model=base_model)
for fn in glob.iglob(os.path.join(path, "*.csv")):
key = os.path.basename(fn).replace(".csv", "")
table = dataset.get_table(key)
if table is None:
continue
if replace:
print('loading dataset {}'.format(fn))
df = pd.read_csv(fn)
# fix columns that are named "index", a sql reserved word
df.reindex_axis(sorted(df.columns), axis=1)
columns = [column.name for column in table.__table__.columns]
df.columns = columns
df.to_sql(name=table.__tablename__, con=engine, if_exists='replace', index=False)
return dataset
class SqlDataset:
"""
Bridge between the facial information CSVs connected to the datasets, and MySQL
- each dataset should have files that can be loaded into these database models
- names will be fixed to work in SQL (index -> id)
- we can then have more generic models for fetching this info after doing a FAISS query
"""
def __init__(self, name, engine=None, base_model=None):
self.name = name
self.tables = {}
if base_model is None:
self.engine = create_engine(connection_url, encoding="utf-8", pool_recycle=3600)
base_model = declarative_base(engine)
self.base_model = base_model
def describe(self):
"""
List the available SQL tables for a given dataset.
"""
return {
'name': self.name,
'tables': list(self.tables.keys()),
}
def get_identity(self, id):
"""
Get an identity given an ID.
"""
# id += 1
file_record_table = self.get_table('file_record')
file_record = file_record_table.query.filter(file_record_table.id == id).first()
if not file_record:
return None
identity_table = self.get_table('identity')
identity = identity_table.query.filter(identity_table.id == file_record.identity_id).first()
if not identity:
return None
return {
'file_record': file_record.toJSON(),
'identity': identity.toJSON(),
'face_roi': self.select('face_roi', id),
'face_pose': self.select('face_pose', id),
}
def search_name(self, q):
"""
Find an identity by name.
"""
table = self.get_table('identity')
identity_list = table.query.filter(table.fullname.ilike(q)).order_by(table.fullname.desc()).limit(15)
return identity_list
def search_description(self, q):
"""
Find an identity by description.
"""
table = self.get_table('identity')
identity_list = table.query.filter(table.description.ilike(q)).order_by(table.description.desc()).limit(15)
return identity_list
def get_file_records_for_identities(self, identity_list):
"""
Given a list of identities, map these to file records.
"""
identities = []
file_record_table = self.get_table('file_record')
for row in identity_list:
file_record = file_record_table.query.filter(file_record_table.identity_id == row.id).first()
if file_record:
identities.append({
'file_record': file_record.toJSON(),
'identity': row.toJSON(),
})
return identities
def select(self, table, id):
"""
Perform a generic select.
"""
table = self.get_table(table)
if not table:
return None
session = Session()
# for obj in session.query(table).filter_by(id=id):
# print(table)
obj = session.query(table).filter(table.id == id).first()
session.close()
return obj.toJSON()
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