class GenderKernel(scannerpy.Kernel):
def __init__(self, config, protobufs):
self.protobufs = protobufs
self.rc = RudeCarnie(model_dir=model_dir)
def close(self):
pass
def execute(self, columns):
global i
[img, bboxes] = columns
img = cv2.cvtColor(img, cv2.COLOR_RGB2BGR)
[h, w] = img.shape[:2]
bboxes = readers.bboxes(bboxes, self.protobufs)
imgs = [
img[int(h * bbox.y1):int(h * bbox.y2),
int(w * bbox.x1):int(w * bbox.x2)] for bbox in bboxes
]
for img in imgs:
cv2.imwrite('/app/tmp/{:05d}.jpg'.format(i), img)
i += 1
genders = self.rc.get_gender_batch(imgs)
outputs = [
struct.pack('=cf', label, score) for [label, score] in genders
]
assert (len(outputs) == len(imgs))
return [''.join(outputs)]
def handle(self, *args, **options):
with open(options['path']) as f:
paths = [s.strip() for s in f.readlines()]
model_dir = '/app/deps/rude-carnie/inception_gender_checkpoint'
rc = RudeCarnie(model_dir=model_dir)
for path in paths:
self.handle_video(path, rc)
def handle(self, *args, **options):
with open(options['path']) as f:
paths = [s.strip() for s in f.readlines()]
model_dir = '/app/deps/rude-carnie/inception_gender_checkpoint'
rc = RudeCarnie(model_dir=model_dir)
for path in paths:
confident = 0
if path == '':
return
video = Video.objects.filter(path=path).get()
labelset = video.detected_labelset()
tracks = Track.objects.filter(first_frame__labelset=labelset).all()
for track in tracks:
if track.gender != '0':
print 'skipping_track', track.id
continue
faces = Face.objects.filter(track=track)
print track.id
print("len of faces for path {}, is {}".format(
path, len(faces)))
imgs = [
'./assets/thumbnails/{}_{}.jpg'.format(labelset.id, f.id)
for f in faces
]
best = rc.get_gender(imgs)
# Update each of the faces.
male_sum = 0.0
female_sum = 0.0
for i, face in enumerate(faces):
if best[i] is None:
# couldn't get gender output for some reason
continue
if best[i][0] == 'M':
male_sum += best[i][1]
elif best[i][0] == 'F':
female_sum += best[i][1]
track.gender = 'M' if male_sum > female_sum else 'F'
track.save()
def handle(self, *args, **options):
with open(options['path']) as f:
paths = [s.strip() for s in f.readlines()]
model_dir = '/app/deps/rude-carnie/inception_gender_checkpoint'
for i, path in enumerate(paths):
confident = 0
if path == '':
return
rc = RudeCarnie(model_dir=model_dir)
video = Video.objects.filter(path=path).get()
labelset = video.detected_labelset()
faces = Face.objects.filter(frame__labelset=labelset).all()
print(("len of faces for path {}, is {}".format(path, len(faces))))
faces = [f for f in faces if f.bbox.x2 - f.bbox.x1 >= .05]
imgs = [
'./assets/thumbnails/{}_{}.jpg'.format(video.id, f.id)
for f in faces
]
best = rc.get_gender(imgs, single_look=True)
for comb in zip(imgs, best):
print(('{} : {}'.format(comb[0], comb[1])))
# Update each of the faces.
for i, face in enumerate(faces):
if best[i] is None:
# couldn't get gender output for some reason
continue
if best[i][1] < 0.90:
# gender detector not confident.
face.gender = 'U'
else:
face.gender = best[i][0]
confident += 1
face.save()
print(('confident = {}, not confident = {}'.format(
confident,
len(faces) - confident)))
class DetectGender(scannerpy.Kernel):
def __init__(self, config):
from carnie_helper import RudeCarnie
self.config = config
self.rc = RudeCarnie(model_dir=config.args['model_dir'])
def execute(self, frame: FrameType, bboxes: bytes) -> bytes:
frame = cv2.cvtColor(frame, cv2.COLOR_RGB2BGR)
[h, w] = frame.shape[:2]
bboxes = readers.bboxes(bboxes, self.config.protobufs)
frames = [
frame[int(bbox.y1 * h):int(bbox.y2 * h),
int(bbox.x1 * w):int(bbox.x2 * w)] for bbox in bboxes
]
genders = self.rc.get_gender_batch(frames)
return pickle.dumps(genders)
class DetectGender(scannerpy.Kernel):
def fetch_resources(self):
download_temp_file(MODEL_FILE, untar=True)
def setup_with_resources(self):
from carnie_helper import RudeCarnie
self.rc = RudeCarnie(model_dir=os.path.join(temp_directory(), '21936'))
def execute(self, frame: FrameType, bboxes: BboxList) -> Any:
frame = cv2.cvtColor(frame, cv2.COLOR_RGB2BGR)
[h, w] = frame.shape[:2]
frames = [
frame[int(bbox.y1 * h):int(bbox.y2 * h),
int(bbox.x1 * w):int(bbox.x2 * w)] for bbox in bboxes
]
genders = self.rc.get_gender_batch(frames)
return genders
def __init__(self, config, protobufs):
self.protobufs = protobufs
self.rc = RudeCarnie(model_dir=model_dir)
def __init__(self, config):
from carnie_helper import RudeCarnie
self.config = config
self.rc = RudeCarnie(model_dir=config.args['model_dir'])
def setup_with_resources(self):
from carnie_helper import RudeCarnie
self.rc = RudeCarnie(model_dir=os.path.join(temp_directory(), '21936'))
from carnie_helper import RudeCarnie
import os
import random
def load_imgs(img_directory):
imgs = []
for root, subdirs, files in os.walk(img_directory):
for file in files:
if os.path.splitext(file)[1].lower() in ('.jpg', '.jpeg'):
imgs.append(os.path.join(root, file))
return imgs
rc = RudeCarnie()
data_dir = '/usr/src/app/assets/thumbnails'
files = load_imgs(data_dir)
files = random.sample(files, 30)
assert len(files) != 0, 'test'
best = rc.get_gender(files)
for comb in zip(files, best):
print('{} : {}'.format(comb[0], comb[1]))