import sys
import os
from os.path import join
from pathlib import Path
import time

import numpy as np
import cv2 as cv
import dlib
from PIL import Image
import matplotlib.pyplot as plt

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_landmarks
from app.models.data_store import DataStore
  
@celery.task(bind=True)
def fullmonte_task(self, uuid_name):
  return

  # TOOD add selective testing
  opt_run_pose = True
  opt_run_2d_68 = True
  opt_run_3d_68 = True
  opt_run_3d_68 = True

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


  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])


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

  face_detector = face_detector.DetectorDLIBCNN(gpu=opt_gpu)  # -1 for CPU
  log.info('detecting face...')
  st = time.time()
  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'Detected face in {(time.time() - st):.2f}s')
  log.info('')


  # ----------------------------------------------------------------------------
  # detect 3D landmarks
  
  log.info('loading 3D landmark generator files...')
  landmark_detector_3d_68 = face_landmarks.FaceAlignment3D_68(gpu=opt_gpu)  # -1 for CPU
  log.info('generating 3D landmarks...')
  st = time.time()
  points_3d_68 = landmark_detector_3d_68.landmarks(im_resized, bbox_dim.to_xyxy())
  log.info(f'generated 3D landmarks in {(time.time() - st):.2f}s')
  log.info('')


  # ----------------------------------------------------------------------------
  # generate 3D GIF animation
  
  log.info('generating 3D animation...')
  if not opt_fp_out:
    fpp_im = Path(opt_fp_in)
    fp_out = join(fpp_im.parent, f'{fpp_im.stem}_anim.gif')
  else:
    fp_out = opt_fp_out
  st = time.time()
  plot_utils.generate_3d_landmark_anim(np.array(points_3d_68), fp_out, 
    size=opt_gif_size, num_frames=opt_gif_frames)
  log.info(f'Generated animation in {(time.time() - st):.2f}s')
  log.info(f'Saved to: {fp_out}')
  log.info('')


  # ----------------------------------------------------------------------------
  # generate face vectors, only to test if feature extraction works
  
  log.info('initialize face recognition model...')
  from app.processors import face_recognition
  face_rec = face_recognition.RecognitionDLIB()
  st = time.time()
  log.info('generating face vector...')
  vec = face_rec.vec(im_resized, bbox_dim)
  log.info(f'generated face vector in {(time.time() - st):.2f}s')
  log.info('')


  # ----------------------------------------------------------------------------
  # generate 68 point landmarks using dlib
  
  log.info('initializing face landmarks 68 dlib...')
  from app.processors import face_landmarks
  landmark_detector_2d_68 = face_landmarks.Dlib2D_68()
  log.info('generating 2D 68PT landmarks...')
  st = time.time()
  points_2d_68 = landmark_detector_2d_68.landmarks(im_resized, bbox_dim)
  log.info(f'generated 2D 68PT face landmarks in {(time.time() - st):.2f}s')
  log.info('')


  # ----------------------------------------------------------------------------
  # generate pose from 68 point 2D landmarks
  
  if opt_run_pose:
    log.info('initialize pose...')
    from app.processors import face_pose
    pose_detector = face_pose.FacePoseDLIB()
    log.info('generating pose...')
    st = time.time()
    pose_data = pose_detector.pose(points_2d_68, dim)
    log.info(f'generated pose {(time.time() - st):.2f}s')
    log.info('')


  # ----------------------------------------------------------------------------
  # generate pose from 68 point 2D landmarks

  # done
  self.log.debug('Add age real')
  self.log.debug('Add age apparent')
  self.log.debug('Add gender')
  
  
  # 3DDFA
  self.log.debug('Add depth')
  self.log.debug('Add pncc')

  # TODO
  self.log.debug('Add 3D face model')
  self.log.debug('Add face texture flat')
  self.log.debug('Add ethnicity')

  # display
  if opt_display:
    
    # draw bbox
    
    # draw 3d landmarks
    im_landmarks_3d_68 = im_resized.copy()
    draw_utils.draw_landmarks3D(im_landmarks_3d_68, points_3d_68)
    draw_utils.draw_bbox(im_landmarks_3d_68, bbox_dim)

    # draw 2d landmarks
    im_landmarks_2d_68 = im_resized.copy()
    draw_utils.draw_landmarks2D(im_landmarks_2d_68, points_2d_68)
    draw_utils.draw_bbox(im_landmarks_2d_68, bbox_dim)

    # draw pose
    if opt_run_pose:
      im_pose = im_resized.copy()
      draw_utils.draw_pose(im_pose, pose_data['point_nose'], pose_data['points'])
      draw_utils.draw_degrees(im_pose, pose_data)

    # draw animated GIF
    im = Image.open(fp_out)
    im_frames = []
    duration = im.info['duration']
    try:
      while True:
        im.seek(len(im_frames))
        mypalette = im.getpalette()
        im.putpalette(mypalette)
        im_jpg = Image.new("RGB", im.size)
        im_jpg.paste(im)
        im_np = im_utils.pil2np(im_jpg.copy())
        im_frames.append(im_np)
    except EOFError:
      pass # end of GIF sequence

    n_frames = len(im_frames)
    frame_number = 0

    while True:
      # show all images here
      cv.imshow('Original', im_resized)
      cv.imshow('2D 68PT Landmarks', im_landmarks_2d_68)
      cv.imshow('3D 68PT Landmarks', im_landmarks_3d_68)
      cv.imshow('Pose', im_pose)
      cv.imshow('3D 68pt GIF', im_frames[frame_number])
      frame_number = (frame_number + 1) % n_frames
      k = cv.waitKey(duration) & 0xFF
      if k == 27 or k == ord('q'):  # ESC
        cv.destroyAllWindows()
        sys.exit()
      elif k != 255:
        # any key to continue
        break