def main():
parser = OptionParser([SceneOps(), AlgorithmOps(), ThresholdOps()])
scenes, algorithms, threshold = parser.parse_args()
# delay imports to speed up usage response
from toolkit.evaluations import error_heatmaps
error_heatmaps.plot(algorithms, scenes, thresh=threshold)
def main():
parser = OptionParser([SceneOps(), AlgorithmOps(with_gt=True), MetaAlgorithmOps(default=[])])
scenes, algorithms, meta_algorithms, compute_meta_algos = parser.parse_args()
# delay imports to speed up usage response
from toolkit import settings
from toolkit.algorithms import MetaAlgorithm
from toolkit.utils import log, misc, point_cloud
if compute_meta_algos and meta_algorithms:
MetaAlgorithm.prepare_meta_algorithms(meta_algorithms, algorithms, scenes)
algorithms += meta_algorithms
for scene in scenes:
center_view = scene.get_center_view()
for algorithm in algorithms:
if algorithm.get_name() == "gt":
disp_map = scene.get_gt()
else:
disp_map = misc.get_algo_result(algorithm, scene)
log.info("Creating point cloud for scene '%s' with '%s' disparity map." %
(scene.get_name(), algorithm.get_name()))
pc = point_cloud.convert(scene, disp_map, center_view)
file_name = "%s_%s.ply" % (scene.get_name(), algorithm.get_name())
file_path = op.join(settings.EVAL_PATH, "point_clouds", file_name)
log.info("Saving point cloud to: %s" % file_path)
point_cloud.save(pc, file_path)
def main():
parser = OptionParser([
SceneOps(),
AlgorithmOps(),
MetricOps(),
VisualizationOps(),
OverwriteOps(),
MetaAlgorithmOps(default=[])
])
scenes, algorithms, metrics, with_vis, add_to_existing, meta_algorithms, compute_meta_algos = parser.parse_args(
)
# delay import to speed up usage response
from toolkit import settings
from toolkit.algorithms import MetaAlgorithm
from toolkit.evaluations import submission_evaluation
from toolkit.utils import misc
if compute_meta_algos and meta_algorithms:
MetaAlgorithm.prepare_meta_algorithms(meta_algorithms, algorithms,
scenes)
algorithms += meta_algorithms
for algorithm in algorithms:
evaluation_output_path = op.join(settings.ALGO_EVAL_PATH,
algorithm.get_name())
algorithm_input_path = misc.get_path_to_algo_data(algorithm)
submission_evaluation.evaluate(
scenes=scenes,
metrics=metrics,
visualize=with_vis,
evaluation_output_path=evaluation_output_path,
algorithm_input_path=algorithm_input_path,
add_to_existing_results=add_to_existing)
def main():
parser = OptionParser([
AlgorithmOps(),
SceneOps(),
MetaAlgorithmOps(with_load_argument=False)
])
algorithms, scenes, meta_algorithms = parser.parse_args()
from toolkit.algorithms import MetaAlgorithm
MetaAlgorithm.prepare_meta_algorithms(meta_algorithms, algorithms, scenes)
def main():
parser = OptionParser([SceneOps(), AlgorithmOps(), MetaAlgorithmOps(default=[])])
scenes, algorithms, meta_algorithms, compute_meta_algos = parser.parse_args()
# delay imports to speed up usage response
from toolkit.algorithms import MetaAlgorithm
from toolkit.evaluations import bad_pix_series
if compute_meta_algos and meta_algorithms:
MetaAlgorithm.prepare_meta_algorithms(meta_algorithms, algorithms, scenes)
bad_pix_series.plot(algorithms+meta_algorithms, scenes)
def main():
parser = OptionParser([SceneOps(), AlgorithmOps(), MetricOps(), MetaAlgorithmOps(default=[])])
scenes, algorithms, metrics, meta_algorithms, compute_meta_algos = parser.parse_args()
# delay imports to speed up usage response
from toolkit.algorithms import MetaAlgorithm
from toolkit.evaluations import metric_overviews
if compute_meta_algos and meta_algorithms:
MetaAlgorithm.prepare_meta_algorithms(meta_algorithms, algorithms, scenes)
metric_overviews.plot_general_overview(algorithms+meta_algorithms, scenes, metrics)
def main():
parser = OptionParser([SceneOps(), AlgorithmOps(), MetaAlgorithmOps()])
scenes, algorithms, meta_algorithms, compute_meta_algos = parser.parse_args(
)
# delay imports to speed up usage response
from toolkit.algorithms import MetaAlgorithm
from toolkit.evaluations import meta_algo_comparisons
if compute_meta_algos and meta_algorithms:
MetaAlgorithm.prepare_meta_algorithms(meta_algorithms, algorithms,
scenes)
for meta_algorithm in meta_algorithms:
meta_algo_comparisons.plot(algorithms, scenes, meta_algorithm)
def main():
parser = OptionParser(
[AlgorithmOps(),
SceneOps(), MetaAlgorithmOps(default=[])])
algorithms, scenes, meta_algorithms, compute_meta_algos = parser.parse_args(
)
# delay imports to speed up usage response
from toolkit.algorithms import MetaAlgorithm
from toolkit.evaluations import pairwise_algo_comparisons
if compute_meta_algos and meta_algorithms:
MetaAlgorithm.prepare_meta_algorithms(meta_algorithms, algorithms,
scenes)
pairwise_algo_comparisons.plot_pairwise_comparisons(
algorithms + meta_algorithms, scenes)
def main():
scenes = OptionParser([SceneOps()]).parse_args()
for scene in scenes:
offset = scene.compute_offset()
print "%s: %0.3f" % (scene, offset)