def generate_vdn(fast=False):
kill()
import django
sys.path.append(os.path.dirname(__file__))
os.environ.setdefault("DJANGO_SETTINGS_MODULE", "dva.settings")
django.setup()
from django.core.files.uploadedfile import SimpleUploadedFile
from dvaapp.views import handle_uploaded_file, handle_youtube_video
from dvaapp import models
from dvaapp.models import TEvent
from dvaapp.tasks import extract_frames, perform_face_detection_indexing_by_id, inception_index_by_id, \
perform_ssd_detection_by_id, perform_yolo_detection_by_id, inception_index_regions_by_id, \
export_video_by_id
dirname = get_coco_dirname()
local(
'wget https://www.dropbox.com/s/2dq085iu34y0hdv/coco_input.zip?dl=1 -O coco.zip'
)
local('unzip coco.zip')
with lcd(dirname):
local("zip coco_input.zip -r *.jpg")
fname = '{}/coco_input.zip'.format(dirname)
with open('{}/coco_sample_metadata.json'.format(dirname)) as datafile:
data = json.load(datafile)
f = SimpleUploadedFile("coco_input.zip",
file(fname).read(),
content_type="application/zip")
v = handle_uploaded_file(f, 'mscoco_sample_500')
extract_frames(TEvent.objects.create(video=v).pk)
video = v
models.Region.objects.all().filter(video=video).delete()
for frame in models.Frame.objects.all().filter(video=video):
frame_id = str(int(frame.name.split('_')[-1].split('.')[0]))
annotation = models.Region()
annotation.region_type = models.Region.ANNOTATION
annotation.video = v
annotation.frame = frame
annotation.full_frame = True
annotation.metadata_json = json.dumps(data[frame_id]['image'])
annotation.object_name = 'metadata'
annotation.save()
for frame in models.Frame.objects.all().filter(video=video):
frame_id = str(int(frame.name.split('_')[-1].split('.')[0]))
for a in data[frame_id][u'annotations']:
annotation = models.Region()
annotation.region_type = models.Region.ANNOTATION
annotation.video = v
annotation.frame = frame
annotation.metadata_json = json.dumps(a)
annotation.full_frame = False
annotation.x = a['bbox'][0]
annotation.y = a['bbox'][1]
annotation.w = a['bbox'][2]
annotation.h = a['bbox'][3]
annotation.object_name = 'coco_instance/{}/{}'.format(
a[u'category'][u'supercategory'], a[u'category'][u'name'])
annotation.save()
for a in data[frame_id][u'keypoints']:
annotation = models.Region()
annotation.region_type = models.Region.ANNOTATION
annotation.video = v
annotation.frame = frame
annotation.metadata_json = json.dumps(a)
annotation.x = a['bbox'][0]
annotation.y = a['bbox'][1]
annotation.w = a['bbox'][2]
annotation.h = a['bbox'][3]
annotation.object_name = 'coco_keypoints/{}/{}'.format(
a[u'category'][u'supercategory'], a[u'category'][u'name'])
annotation.save()
for caption in data[frame_id][u'captions']:
annotation = models.Region()
annotation.region_type = models.Region.ANNOTATION
annotation.video = v
annotation.frame = frame
annotation.metadata_text = caption['caption']
annotation.full_frame = True
annotation.object_name = 'caption'
annotation.save()
if not fast:
inception_index_by_id(TEvent.objects.create(video=v).pk)
perform_ssd_detection_by_id(TEvent.objects.create(video=v).pk)
perform_face_detection_indexing_by_id(
TEvent.objects.create(video=v).pk)
inception_index_regions_by_id(TEvent.objects.create(video=v).pk)
export_video_by_id(TEvent.objects.create(video=v).pk)
def generate_vdn(fast=False):
kill()
setup_django()
from django.core.files.uploadedfile import SimpleUploadedFile
from dvaapp.views import handle_uploaded_file, handle_youtube_video
from dvaapp import models
from dvaapp.models import TEvent
from dvaapp.tasks import extract_frames, perform_face_detection_indexing_by_id, inception_index_by_id, \
perform_ssd_detection_by_id, perform_yolo_detection_by_id, inception_index_regions_by_id, \
export_video_by_id
dirname = get_coco_dirname()
local('wget https://www.dropbox.com/s/2dq085iu34y0hdv/coco_input.zip?dl=1 -O coco.zip')
local('unzip coco.zip')
with lcd(dirname):
local("zip coco_input.zip -r *.jpg")
fname = '{}/coco_input.zip'.format(dirname)
with open('{}/coco_sample_metadata.json'.format(dirname)) as datafile:
data = json.load(datafile)
f = SimpleUploadedFile("coco_input.zip", file(fname).read(), content_type="application/zip")
v = handle_uploaded_file(f, 'mscoco_sample_500')
extract_frames(TEvent.objects.create(video=v).pk)
video = v
models.Region.objects.all().filter(video=video).delete()
for frame in models.Frame.objects.all().filter(video=video):
frame_id = str(int(frame.name.split('_')[-1].split('.')[0]))
annotation = models.Region()
annotation.region_type = models.Region.ANNOTATION
annotation.video = v
annotation.frame = frame
annotation.full_frame = True
annotation.metadata_json = json.dumps(data[frame_id]['image'])
annotation.object_name = 'metadata'
annotation.save()
for frame in models.Frame.objects.all().filter(video=video):
frame_id = str(int(frame.name.split('_')[-1].split('.')[0]))
for a in data[frame_id][u'annotations']:
annotation = models.Region()
annotation.region_type = models.Region.ANNOTATION
annotation.video = v
annotation.frame = frame
annotation.metadata_json = json.dumps(a)
annotation.full_frame = False
annotation.x = a['bbox'][0]
annotation.y = a['bbox'][1]
annotation.w = a['bbox'][2]
annotation.h = a['bbox'][3]
annotation.object_name = 'coco_instance/{}/{}'.format(a[u'category'][u'supercategory'], a[u'category'][u'name'])
annotation.save()
for a in data[frame_id][u'keypoints']:
annotation = models.Region()
annotation.region_type = models.Region.ANNOTATION
annotation.video = v
annotation.frame = frame
annotation.metadata_json = json.dumps(a)
annotation.x = a['bbox'][0]
annotation.y = a['bbox'][1]
annotation.w = a['bbox'][2]
annotation.h = a['bbox'][3]
annotation.object_name = 'coco_keypoints/{}/{}'.format(a[u'category'][u'supercategory'], a[u'category'][u'name'])
annotation.save()
for caption in data[frame_id][u'captions']:
annotation = models.Region()
annotation.region_type = models.Region.ANNOTATION
annotation.video = v
annotation.frame = frame
annotation.metadata_text = caption['caption']
annotation.full_frame = True
annotation.object_name = 'caption'
annotation.save()
if not fast:
inception_index_by_id(TEvent.objects.create(video=v).pk)
perform_ssd_detection_by_id(TEvent.objects.create(video=v).pk)
perform_face_detection_indexing_by_id(TEvent.objects.create(video=v).pk)
inception_index_regions_by_id(TEvent.objects.create(video=v).pk)
export_video_by_id(TEvent.objects.create(video=v).pk)