def register_model(filename, a, b, thresh, viewpoint):
session = SESSION()
if viewpoint:
model = pydro.io.LoadModel(filename)
for i in xrange(16):
model.start.rules[i].metadata = {"angle": (math.pi - i * math.pi / 8) % (2 * math.pi)}
pydro.io.SaveModel(filename, model)
model = Model(filename=filename, a=a, b=b, thresh=thresh, release="pydro")
session.add(model)
session.commit()
def register_model(filename, a, b, thresh, viewpoint):
session = SESSION()
if viewpoint:
model = pydro.io.LoadModel(filename)
for i in xrange(16):
model.start.rules[i].metadata = {
'angle': (math.pi - i * math.pi / 8) % (2 * math.pi)
}
pydro.io.SaveModel(filename, model)
model = Model(
filename=filename,
a=a,
b=b,
thresh=thresh,
release='pydro',
)
session.add(model)
session.commit()
def detect(pid, model_filename):
"""Runs DPM and computes 3D pose."""
logger = logging.getLogger('detect')
logger.info((pid, model_filename))
session = SESSION()
try:
# pylint: disable-msg=E1101
num_detections, = session.query(func.count(Detection.id)) \
.join(Model) \
.filter(Detection.pid == pid) \
.filter(Model.filename == model_filename) \
.one()
if num_detections > 0:
logger.info('Already computed')
return pid
model = session.query(Model) \
.filter_by(filename=model_filename) \
.one()
photo = session.query(Photo) \
.options(joinedload('dataset')) \
.filter_by(id=pid) \
.one()
vehicle_types = session.query(VehicleType) \
.filter(VehicleType.id.in_([202, 8, 150, 63, 123, 16]))
pydro_model = pydro.io.LoadModel(model.filename)
image = scipy.misc.imread(
os.path.join(IMAGE_DIR, photo.filename))
pyramid = pydro.features.BuildPyramid(image, model=pydro_model)
filtered_model = pydro_model.Filter(pyramid)
parse_trees = list(filtered_model.Parse(model.thresh))
# make sure we use at least one entry so we know we tried
if len(parse_trees) == 0:
parse_trees = list(
itertools.islice(filtered_model.Parse(-numpy.inf), 1))
assert len(parse_trees) > 0
bbox_tuple = namedtuple('bbox_tuple', 'x1,x2,y1,y2')
for tree in parse_trees:
bbox = bbox_tuple(
x1=tree.x1 / image.shape[1],
x2=tree.x2 / image.shape[1],
y1=tree.y1 / image.shape[0],
y2=tree.y2 / image.shape[0],
)
score = tree.s
angle = tree.child.rule.metadata.get('angle', None)
if bbox.x1 > bbox.x2 or bbox.y1 > bbox.y2:
continue
car_pose_generator = compute_car_pose(
photo,
bbox,
angle,
vehicle_types
)
for lla, geom, vehicle_type, world_angle in car_pose_generator:
det = Detection(
photo=photo,
x1=float(bbox.x1),
y1=float(bbox.y1),
x2=float(bbox.x2),
y2=float(bbox.y2),
score=float(score),
prob=float(
1.0 / (1.0 + math.exp(model.a * score + model.b))),
model=model,
angle=angle,
lla=lla,
geom=geom,
world_angle=float(world_angle),
vehicle_type=vehicle_type,
)
session.add(det)
session.commit()
return pid
except Exception:
session.rollback()
raise
finally:
session.close()