def visual_indexer(self):
if IndexerTask._visual_indexer is None:
IndexerTask._visual_indexer = {
'inception': indexer.InceptionIndexer(),
'facenet': indexer.FacenetIndexer(),
'alexnet': indexer.AlexnetIndexer()
}
return IndexerTask._visual_indexer
def perform_face_indexing(video_id):
from dvaapp.models import Region,Frame,Video,IndexEntries
from dvalib import indexer,detector
from dvaapp.operations.video_processing import WFrame,WVideo
from django.conf import settings
from scipy import misc
face_indexer = indexer.FacenetIndexer()
dv = Video.objects.get(id=video_id)
video = WVideo(dv, settings.MEDIA_ROOT)
frames = Frame.objects.all().filter(video=dv)
wframes = [WFrame(video=video, frame_index=df.frame_index, primary_key=df.pk) for df in frames]
input_paths = {f.local_path(): f.primary_key for f in wframes}
faces_dir = '{}/{}/detections'.format(settings.MEDIA_ROOT, video_id)
indexes_dir = '{}/{}/indexes'.format(settings.MEDIA_ROOT, video_id)
face_detector = detector.FaceDetector()
aligned_paths = face_detector.detect(wframes)
logging.info(len(aligned_paths))
faces = []
faces_to_pk = {}
count = 0
for path, v in aligned_paths.iteritems():
for scaled_img, bb in v:
d = Region()
d.region_type = Region.DETECTION
d.video = dv
d.confidence = 100.0
d.frame_id = input_paths[path]
d.object_name = "mtcnn_face"
left, top, right, bottom = bb[0], bb[1], bb[2], bb[3]
d.y = top
d.x = left
d.w = right - left
d.h = bottom - top
d.save()
face_path = '{}/{}.jpg'.format(faces_dir, d.pk)
output_filename = os.path.join(faces_dir, face_path)
misc.imsave(output_filename, scaled_img)
faces.append(face_path)
faces_to_pk[face_path] = d.pk
count += 1
dv.refresh_from_db()
dv.detections = dv.detections + count
dv.save()
path_count, emb_array, entries, feat_fname, entries_fname = face_indexer.index_faces(faces, faces_to_pk,
indexes_dir, video_id)
i = IndexEntries()
i.video = dv
i.count = len(entries)
i.contains_frames = False
i.contains_detections = True
i.detection_name = "Face"
i.algorithm = 'facenet'
i.entries_file_name = entries_fname.split('/')[-1]
i.features_file_name = feat_fname.split('/')[-1]
i.save()
def visual_indexer(self):
if IndexerTask._visual_indexer is None:
# if IndexerTask._session is None:
# logging.info("Creating a global shared session")
# config = indexer.tf.ConfigProto()
# config.gpu_options.per_process_gpu_memory_fraction = 0.2
# IndexerTask._session = indexer.tf.Session()
IndexerTask._visual_indexer = {
'inception': indexer.InceptionIndexer(),
'facenet': indexer.FacenetIndexer(),
'vgg': indexer.VGGIndexer()
}
return IndexerTask._visual_indexer
def get_index(cls,di):
di.ensure()
if di.pk not in Indexers._visual_indexer:
iroot = "{}/models/".format(settings.MEDIA_ROOT)
if di.name == 'inception':
Indexers._visual_indexer[di.pk] = indexer.InceptionIndexer(iroot + "{}/network.pb".format(di.uuid))
elif di.name == 'facenet':
Indexers._visual_indexer[di.pk] = indexer.FacenetIndexer(iroot + "{}/facenet.pb".format(di.uuid))
elif di.algorithm == 'vgg':
Indexers._visual_indexer[di.pk] = indexer.VGGIndexer(iroot + "{}/{}".format(di.uuid,di.files[0]['filename']))
else:
raise ValueError,"unregistered indexer with id {}".format(di.pk)
return Indexers._visual_indexer[di.pk]
def perform_face_indexing(video_id):
face_indexer = indexer.FacenetIndexer()
dv = Video.objects.get(id=video_id)
video = entity.WVideo(dv, settings.MEDIA_ROOT)
frames = Frame.objects.all().filter(video=dv)
wframes = [
entity.WFrame(video=video,
frame_index=df.frame_index,
primary_key=df.pk) for df in frames
]
input_paths = {f.local_path(): f.primary_key for f in wframes}
faces_dir = '{}/{}/detections'.format(settings.MEDIA_ROOT, video_id)
indexes_dir = '{}/{}/indexes'.format(settings.MEDIA_ROOT, video_id)
face_detector = detector.FaceDetector()
aligned_paths = face_detector.detect(wframes)
logging.info(len(aligned_paths))
faces = []
faces_to_pk = {}
count = 0
for path, v in aligned_paths.iteritems():
for scaled_img, bb in v:
d = Detection()
d.video = dv
d.confidence = 100.0
d.frame_id = input_paths[path]
d.object_name = "mtcnn_face"
top, left, bottom, right = bb[0], bb[1], bb[2], bb[3]
d.y = top
d.x = left
d.w = right - left
d.h = bottom - top
d.save()
face_path = '{}/{}.jpg'.format(faces_dir, d.pk)
output_filename = os.path.join(faces_dir, face_path)
misc.imsave(output_filename, scaled_img)
faces.append(face_path)
faces_to_pk[face_path] = d.pk
count += 1
dv.detections = dv.detections + count
dv.save()
path_count, emb_array, entries = face_indexer.index_faces(
faces, faces_to_pk, indexes_dir, video_id)
i = IndexEntries()
i.video = dv
i.count = len(entries)
i.contains_frames = False
i.contains_detections = True
i.detection_name = "Face"
i.algorithm = 'facenet'
i.save()
def get_index(self, di):
if di.pk not in IndexerTask._visual_indexer:
iroot = "{}/models/".format(settings.MEDIA_ROOT)
if di.name == 'inception':
IndexerTask._visual_indexer[di.pk] = indexer.InceptionIndexer(
iroot + "{}/network.pb".format(di.pk))
elif di.name == 'facenet':
IndexerTask._visual_indexer[di.pk] = indexer.FacenetIndexer(
iroot + "{}/facenet.pb".format(di.pk))
elif di.name == 'vgg':
IndexerTask._visual_indexer[di.pk] = indexer.VGGIndexer(
iroot + "{}/vgg.pb".format(di.pk))
else:
raise ValueError, "unregistered indexer with id {}".format(
di.pk)
return IndexerTask._visual_indexer[di.pk]
def visual_indexer(self):
if IndexerTask._visual_indexer is None:
indexer_root_dir = "{}/indexers/".format(settings.MEDIA_ROOT)
# if IndexerTask._session is None:
# logging.info("Creating a global shared session")
# config = indexer.tf.ConfigProto()
# config.gpu_options.per_process_gpu_memory_fraction = 0.2
# IndexerTask._session = indexer.tf.Session()
IndexerTask._visual_indexer = {
'inception':
indexer.InceptionIndexer(indexer_root_dir +
"inception/network.pb"),
'facenet':
indexer.FacenetIndexer(indexer_root_dir +
"facenet/facenet.pb"),
'vgg':
indexer.VGGIndexer(indexer_root_dir + "vgg/vgg.pb")
}
return IndexerTask._visual_indexer
def detection_indexer(self):
if self._detection_indexer is None:
self._detection_indexer = {
'facenet': indexer.FacenetIndexer(),
}
return self._detection_indexer
