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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
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