"""
Converts ROIs to pose: yaw, roll, pitch
"""

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_files', required=True,
  help='Input ROI CSV')
@click.option('-r', '--rois', 'opt_fp_rois', required=True,
  help='Input ROI CSV')
@click.option('-m', '--media', 'opt_dir_media', required=True,
  help='Input media directory')
@click.option('-o', '--output', 'opt_fp_out', required=True,
  help='Output CSV')
@click.option('--size', 'opt_size', 
  type=(int, int), default=(300, 300),
  help='Output image size')
@click.option('--slice', 'opt_slice', type=(int, int), default=(None, None),
  help='Slice list of files')
@click.option('-f', '--force', 'opt_force', is_flag=True,
  help='Force overwrite file')
@click.option('-d', '--display', 'opt_display', is_flag=True,
  help='Display image for debugging')
@click.pass_context
def cli(ctx, opt_fp_files, opt_fp_rois, opt_dir_media, opt_fp_out, opt_size, 
  opt_slice, opt_force, opt_display):
  """Converts ROIs to pose: roll, yaw, pitch"""
  
  import sys
  import os
  from os.path import join
  from pathlib import Path
  from glob import glob
  
  from tqdm import tqdm
  import numpy as np
  import dlib  # must keep a local reference for dlib
  import cv2 as cv
  import pandas as pd

  from app.models.bbox import BBox
  from app.utils import logger_utils, file_utils, im_utils
  from app.processors.face_landmarks import LandmarksDLIB
  from app.processors.face_pose import FacePoseDLIB

  # -------------------------------------------------
  # init here

  log = logger_utils.Logger.getLogger()

  # init face processors
  face_pose = FacePoseDLIB()
  face_landmarks = LandmarksDLIB()

  # load datra
  df_files = pd.read_csv(opt_fp_files)
  df_rois = pd.read_csv(opt_fp_rois)

  if not opt_force and Path(opt_fp_out).exists():
    log.error('File exists. Use "-f / --force" to overwite')
    return
  
  if opt_slice:
    df_rois = df_rois[opt_slice[0]:opt_slice[1]]
  
  # -------------------------------------------------
  # process here
  df_img_groups = df_rois.groupby('image_index')
  log.debug('processing {:,} groups'.format(len(df_img_groups)))


  poses = []

  # iterate 
  #for df_roi_group_idx, df_roi_group in tqdm(df_roi_groups):
  for image_index, df_img_group in tqdm(df_img_groups):
    # make fp
    #image_index = df_roi_group.image_index.values[0]
    pds_file = df_files.iloc[image_index]
    fp_im = join(opt_dir_media, pds_file.subdir, '{}.{}'.format(pds_file.fn, pds_file.ext))
    im = cv.imread(fp_im)
    # get bbox
    x = df_img_group.x.values[0]
    y = df_img_group.y.values[0]
    w = df_img_group.w.values[0]
    h = df_img_group.h.values[0]
    dim = im.shape[:2][::-1]
    bbox = BBox.from_xywh(x, y, w, h).to_dim(dim)
    # get pose
    landmarks = face_landmarks.landmarks(im, bbox)
    pose_data = face_pose.pose(landmarks, dim, project_points=opt_display)
    pose_degrees = pose_data['degrees']  # only keep the degrees data

    # use the project point data if display flag set
    if opt_display:
      pts_im = pose_data['points_image']
      pts_model = pose_data['points_model']
      pt_nose = pose_data['point_nose']
      dst = im.copy()
      face_pose.draw_pose(dst, pts_im, pts_model, pt_nose)
      face_pose.draw_degrees(dst, pose_degrees)
      # display to cv window
      cv.imshow('', dst)
      while True:
        k = cv.waitKey(1) & 0xFF
        if k == 27 or k == ord('q'):  # ESC
          cv.destroyAllWindows()
          sys.exit()
        elif k != 255:
          # any key to continue
          break

    # add image index and append to result CSV data
    pose_degrees['image_index'] = image_index
    poses.append(pose_degrees)


  # save date
  file_utils.mkdirs(opt_fp_out)
  df = pd.DataFrame.from_dict(poses)
  df.index.name = 'index'
  df.to_csv(opt_fp_out)