def get_lazy_dataset(self):
from shapenet.core.point_clouds import get_point_cloud_dataset
from util3d.point_cloud import sample_points
from template_ffd.model import get_builder
from template_ffd.inference.predictions import get_predictions_dataset
builder = get_builder(self._model_id)
cat_id = builder.cat_id
template_ids = builder.template_ids
clouds = []
def sample_fn(cloud):
return sample_points(np.array(cloud), self._n_samples)
gt_clouds = get_point_cloud_dataset(
cat_id, builder.n_samples).map(sample_fn)
with gt_clouds:
for example_id in template_ids:
clouds.append(np.array(gt_clouds[example_id]))
predictions = get_predictions_dataset(self._model_id)
inf_cloud_ds = predictions.map(lambda i: clouds[i].copy())
return _get_lazy_emd_dataset(inf_cloud_ds, cat_id, self._n_samples)
def get_lazy_dataset(self):
from shapenet.core.point_clouds import get_point_cloud_dataset
from util3d.point_cloud import sample_points
from template_ffd.model import get_builder
from template_ffd.inference.predictions import get_predictions_dataset
builder = get_builder(self._model_id)
cat_id = builder.cat_id
template_ids = builder.template_ids
clouds = []
def sample_fn(cloud):
return sample_points(np.array(cloud), self._n_samples)
gt_clouds = get_point_cloud_dataset(
cat_id, builder.n_samples).map(sample_fn)
with gt_clouds:
for example_id in template_ids:
clouds.append(np.array(gt_clouds[example_id]))
predictions = get_predictions_dataset(self._model_id)
inf_cloud_ds = predictions.map(lambda i: clouds[i].copy())
return _get_lazy_emd_dataset(inf_cloud_ds, cat_id, self._n_samples)