class DarknetTests(unittest.TestCase):
def setUp(self):
rmtree(TMP_DIR, ignore_errors=True)
self.wider = Wider(WIDER_DIR)
def test_sanity(self):
self.wider.export(TMP_DIR, 'darknet')
def create_dataset(dataset_name, data_dir):
if not dataset_name:
dataset_name = 'mafa'
if dataset_name == 'widerface':
from morghulis.widerface import Wider
ds = Wider(data_dir)
elif dataset_name == 'fddb':
from morghulis.fddb import FDDB
ds = FDDB(data_dir)
elif dataset_name == 'afw':
from morghulis.afw import AFW
ds = AFW(data_dir)
elif dataset_name == 'pascal_faces':
from morghulis.pascal_faces import PascalFaces
ds = PascalFaces(data_dir)
elif dataset_name == 'mafa':
from morghulis.mafa import Mafa
ds = Mafa(data_dir)
elif dataset_name == 'caltech':
from morghulis.caltech_faces import CaltechFaces
ds = CaltechFaces(data_dir)
elif dataset_name == 'ufdd':
from morghulis.ufdd import UFDD
ds = UFDD(data_dir)
else:
logging.error('Invalid dataset name %s', dataset_name)
raise ValueError('Invalid dataset name %s' % dataset_name)
return ds
def main():
parser = argparse.ArgumentParser()
parser.add_argument('--dataset',
dest='dataset',
action='store',
required=True,
help='widerface, fddb or afw')
parser.add_argument('--output_dir',
dest='output_dir',
action='store',
required=True,
help='')
args = parser.parse_args()
dataset = args.dataset
output_dir = args.output_dir
if dataset == 'widerface':
from morghulis.widerface import Wider
ds = Wider(output_dir)
elif dataset == 'fddb':
from morghulis.fddb import FDDB
ds = FDDB(output_dir)
elif dataset == 'afw':
from morghulis.afw import AFW
ds = AFW(output_dir)
elif dataset == 'pascal_faces':
from morghulis.pascal_faces import PascalFaces
ds = PascalFaces(output_dir)
else:
logging.error('Invalid dataset name %s', dataset)
raise ValueError('Invalid dataset name %s' % dataset)
ds.download()
def main():
parser = argparse.ArgumentParser()
parser.add_argument('--dataset', dest='dataset', action='store', required=True, help='widerface or fddb')
parser.add_argument('--format', dest='format', action='store', required=True, help='darknet, tensorflow, caffe or coco')
parser.add_argument('--data_dir', dest='data_dir', action='store', required=True, help='')
parser.add_argument('--output_dir', dest='output_dir', action='store', required=True, help='')
args = parser.parse_args()
dataset = args.dataset
_format = args.format
data_dir = args.data_dir
output_dir = args.output_dir
if dataset == 'widerface':
from morghulis.widerface import Wider
ds = Wider(data_dir)
elif dataset == 'fddb':
from morghulis.fddb import FDDB
ds = FDDB(data_dir)
elif dataset == 'afw':
from morghulis.afw import AFW
ds = AFW(data_dir)
else:
logging.error('Invalid dataset name %s', dataset)
ds.export(output_dir, _format)
def main():
parser = argparse.ArgumentParser()
parser.add_argument('--input',
dest='input',
action='store',
required=True,
help='input tf record containing the predictions')
parser.add_argument('--data_dir',
dest='data_dir',
action='store',
required=True,
help='')
parser.add_argument('--output_dir',
dest='output_dir',
action='store',
required=True,
help='')
args = parser.parse_args()
tfrecord = args.input
data_dir = args.data_dir
output_dir = args.output_dir
ds = Wider(data_dir)
events = ds.events()
for i in read_detections_from(tfrecord):
event_id = filename.split('_')[0]
event = events[event_id]
item_name = os.path.splitext(os.path.basename(filename))[0]
result_filename = '{}/{}.txt'.format(event, item_name)
target_file = os.path.join(output_dir, result_filename)
ensure_dir(target_file)
with open(target_file, 'w') as dest:
dest.write('{}\n'.format(item_name))
total = len(bboxes)
dest.write('{}\n'.format(total))
for bbox in bboxes:
dest.write('{} {} {} {} {}\n'.format(*bbox))
class WiderTests(unittest.TestCase):
def setUp(self):
self.wider = Wider(WIDER_DIR)
def test_train_set(self):
train_set = [image for image in self.wider.train_set()]
self.assertEqual(6, len(train_set))
def test_val_set(self):
val_set = [image for image in self.wider.val_set()]
self.assertEqual(4, len(val_set))
def test_faces(self):
soldier_drilling = [
image for image in self.wider.train_set()
if 'Soldier_Drilling' in image.filename
]
image = soldier_drilling[0]
self.assertEqual(4, len(image.faces))
def test_faces(self):
press_conference = [
image for image in self.wider.train_set()
if 'Press_Conference' in image.filename
]
image = press_conference[0]
self.assertEqual(1, len(image.faces))
face = image.faces[0]
self.assertEqual(400, face.x1)
self.assertEqual(150, face.y1)
self.assertEqual(208, face.w)
self.assertEqual(290, face.h)
self.assertEqual(0, face.blur)
self.assertEqual(1, face.expression)
self.assertEqual(2, face.illumination)
self.assertEqual(0, face.invalid)
self.assertEqual(4, face.occlusion)
self.assertEqual(5, face.pose)
def test_image(self):
soldier_drilling = [
image for image in self.wider.train_set()
if 'Soldier_Drilling' in image.filename
]
image = soldier_drilling[0]
self.assertEqual(1024, image.width)
self.assertEqual(682, image.height)
self.assertEqual('JPEG', image.format)
def test_events(self):
events = self.wider.events()
print(events)
self.assertEqual(6, len(events))
self.assertEqual('26--Soldier_Drilling', events['26'])
self.assertEqual('12--Group', events['12'])
def setUp(self):
rmtree(TMP_DIR, ignore_errors=True)
self.wider = Wider(WIDER_DIR)
self.caffeExporter = CaffeExporter(self.wider)
def setUp(self):
rmtree(TMP_DIR, ignore_errors=True)
self.wider = Wider(WIDER_DIR)
self.darknetExporter = DarknetExporter(self.wider)
def setUp(self):
self.wider = Wider(WIDER_DIR)
def setUp(self):
rmtree(TMP_DIR, ignore_errors=True)
self.wider = Wider(WIDER_DIR)
self.tfExporter = TensorflowExporter(self.wider)
def setUp(self):
rmtree(TMP_DIR, ignore_errors=True)
self.wider = Wider(WIDER_DIR)