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', default=None, required=True,
  help='Image filepath')
@click.option('-o', '--output', 'opt_fp_out', default=None,
  help='GIF output path')
@click.option('--size', 'opt_size', 
  type=(int, int), default=(300, 300),
  help='Output image size')
@click.option('-g', '--gpu', 'opt_gpu', default=0,
  help='GPU index')
@click.option('-f', '--force', 'opt_force', is_flag=True,
  help='Force overwrite file')
@click.option('--display/--no-display', 'opt_display', is_flag=True, default=False,
  help='Display detections to debug')
@click.pass_context
def cli(ctx, opt_fp_in, opt_fp_out, opt_gpu, opt_size, opt_force, opt_display):
  """Face detector demo"""
  
  import sys
  import os
  from os.path import join
  from pathlib import Path
  import time
  
  from tqdm import tqdm
  import numpy as np
  import pandas as pd
  import cv2 as cv
  import dlib

  from app.utils import logger_utils, file_utils, im_utils, display_utils, draw_utils
  from app.utils import plot_utils
  from app.processors import face_detector, face_beauty
  from app.models.data_store import DataStore
  

  log = logger_utils.Logger.getLogger()

  
  # -------------------------------------------------
  # load image

  im = cv.imread(opt_fp_in)
  im_resized = im_utils.resize(im, width=opt_size[0], height=opt_size[1])


  # TODO fix Keras CPU/GPU device selection issue
  # NB: GPU visibility issues with dlib/keras
  # Wrap this with cuda toggle and run before init dlib GPU

  device_cur = os.getenv('CUDA_VISIBLE_DEVICES', '')
  os.environ['CUDA_VISIBLE_DEVICES'] = ''
  beauty_predictor = face_beauty.FaceBeauty()
  os.environ['CUDA_VISIBLE_DEVICES'] = device_cur


  # ----------------------------------------------------------------------------
  # detect face

  face_detector = face_detector.DetectorDLIBCNN(gpu=opt_gpu)  # -1 for CPU
  bboxes = face_detector.detect(im_resized, largest=True)
  bbox = bboxes[0]
  dim = im_resized.shape[:2][::-1]
  bbox_dim = bbox.to_dim(dim)
  if not bbox:
    log.error('no face detected')
    return
  else:
    log.info(f'face detected: {bbox_dim.to_xyxy()}')

  # ----------------------------------------------------------------------------
  # beauty

  beauty_score = beauty_predictor.beauty(im_resized, bbox_dim)


  # ----------------------------------------------------------------------------
  # output
  
  log.info(f'Face coords: {bbox_dim} face')
  log.info(f'beauty score: {(100*beauty_score):.2f}')


  # ----------------------------------------------------------------------------
  # draw

  # draw 2d landmarks
  im_beauty = im_resized.copy()
  draw_utils.draw_bbox(im_beauty, bbox_dim)
  txt = f'Beauty score: {(100*beauty_score):.2f}'
  draw_utils.draw_text(im_beauty, bbox_dim.pt_tl, txt)


  # ----------------------------------------------------------------------------
  # save
  
  if opt_fp_out:
    # save pose only
    cv.imwrite(opt_fp_out, im_beauty)


  # ----------------------------------------------------------------------------
  # display

  if opt_display:
    # show all images here
    cv.imshow('Beauty', im_beauty)
    display_utils.handle_keyboard()