"""
Crop images to prepare for training
"""

import click

from app.settings import types
from app.utils import click_utils
from app.settings import app_cfg as cfg

@click.command()
@click.option('-i', '--input', 'opt_fp_in', required=True,
  help='Input directory')
@click.option('-r', '--records', 'opt_fp_records', required=True,
  help='Input directory')
@click.option('-o', '--output', 'opt_fp_out', required=True,
  help='Output JSON')
@click.option('-f', '--force', 'opt_force', is_flag=True,
  help='Force overwrite file')
@click.pass_context
def cli(ctx, opt_fp_in, opt_fp_records, opt_fp_out,opt_force):
  """Merges UUID with face vectors"""
  
  import sys
  import os
  from os.path import join
  from pathlib import Path
  
  from tqdm import tqdm
  import pandas as pd

  from app.utils import logger_utils, file_utils
  
  # -------------------------------------------------
  # init here

  log = logger_utils.Logger.getLogger()

  df_vecs = pd.read_csv(opt_fp_in)
  df_records = pd.read_csv(opt_fp_records)
  nrows = len(df_vecs)

  # face vecs
  uuid_vecs = {}

  for roi_idx, row in tqdm(df_vecs.iterrows(), total=nrows):
    # make image path
    record_id = int(row['id'])
    uuid = df_records.iloc[record_id]['uuid']
    vec = row['vec'].split(',')
    uuid_vecs[uuid] = vec

  # save as JSON
  file_utils.write_json(uuid_vecs, opt_fp_out)