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
|
import click
from app.settings import types
from app.models.dataset import Dataset
from app.utils import click_utils
from app.settings import app_cfg as cfg
from app.utils.logger_utils import Logger
@click.command()
@click.option('-i', '--input', 'opt_fp_in', required=True,
help='Input face image')
@click.option('--data_store', 'opt_data_store',
type=cfg.DataStoreVar,
default=click_utils.get_default(types.DataStore.SSD),
show_default=True,
help=click_utils.show_help(types.Dataset))
@click.option('--dataset', 'opt_dataset',
type=cfg.DatasetVar,
required=True,
show_default=True,
help=click_utils.show_help(types.Dataset))
@click.option('--gpu', 'opt_gpu', default=0,
help='GPU index (use -1 for CPU)')
@click.pass_context
def cli(ctx, opt_fp_in, opt_data_store, opt_dataset, opt_gpu):
"""Display image info"""
import sys
from glob import glob
from os.path import join
from pathlib import Path
import time
import imutils
import pandas as pd
import cv2 as cv
import dlib
from tqdm import tqdm
from app.utils import file_utils, im_utils
from app.models.data_store import DataStore, DataStoreS3
from app.processors import face_detector
from app.processors import face_recognition
log = Logger.getLogger()
# init face detection
detector = face_detector.DetectorDLIBHOG()
# init face recognition
recognition = face_recognition.RecognitionDLIB(gpu=opt_gpu)
# load query image
im_query = cv.imread(opt_fp_in)
# get detection as BBox object
bboxes = detector.detect(im_query, largest=True)
bbox = bboxes[0]
dim = im_query.shape[:2][::-1]
bbox = bbox.to_dim(dim) # convert back to real dimensions
if not bbox:
log.error('No face detected. Exiting')
return
# extract the face vectors
vec_query = recognition.vec(im_query, bbox)
# load dataset CSVs
dataset = Dataset(opt_data_store, opt_dataset)
# find matches
image_records = dataset.find_matches(vec_query, n_results=5)
# summary
ims_match = [im_query]
for image_record in image_records:
image_record.summarize()
log.info(f'{image_record.filepath}')
im_match = cv.imread(image_record.filepath)
ims_match.append(im_match)
montages = imutils.build_montages(ims_match, (256, 256), (3,2))
for i, montage in enumerate(montages):
cv.imshow(f'{i}', montage)
# cv gui
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
|
