1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
|
"""
Crop images to prepare for training
"""
import click
# from PIL import Image, ImageOps, ImageFilter, ImageDraw
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=True,
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 pose 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 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
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.DetectorCVDNN()
bboxes = face_detector.detect(im_resized, largest=True)
bbox_norm = bboxes[0]
dim = im_resized.shape[:2][::-1]
bbox_dim = bbox_norm.to_dim(dim)
if not bbox_norm:
log.error('no face detected')
return
# ----------------------------------------------------------------------------
# generate 68 point landmarks using dlib
from app.processors import face_landmarks
landmark_detector_2d_68 = face_landmarks.Dlib2D_68()
points_2d_68 = landmark_detector_2d_68.landmarks(im_resized, bbox_norm)
# ----------------------------------------------------------------------------
# generate pose from 68 point 2D landmarks
from app.processors import face_pose
pose_detector = face_pose.FacePoseDLIB()
pose_data = pose_detector.pose(points_2d_68, dim)
# ----------------------------------------------------------------------------
# output
log.info(f'Face coords: {bbox_dim} face')
log.info(f'pitch: {pose_data["pitch"]}, roll: {pose_data["roll"]}, yaw: {pose_data["yaw"]}')
# ----------------------------------------------------------------------------
# draw
# draw 2d landmarks
im_landmarks = im_resized.copy()
im_landmarks = draw_utils.draw_landmarks2D(im_landmarks, points_2d_68)
im_landmarks = draw_utils.draw_bbox(im_landmarks, bbox_norm)
# draw pose
im_pose = im_resized.copy()
im_pose = draw_utils.draw_pose(im_pose, pose_data['point_nose'], pose_data['points'])
im_pose = draw_utils.draw_degrees(im_pose, pose_data)
# ----------------------------------------------------------------------------
# save
if opt_fp_out:
# save pose only
cv.imwrite(opt_fp_out, im_pose)
# ----------------------------------------------------------------------------
# display
if opt_display:
# show all images here
cv.imshow('Original', im_resized)
cv.imshow('2D 68PT Landmarks', im_landmarks)
cv.imshow('Pose', im_pose)
display_utils.handle_keyboard()
|
