def do_reval(dataset_name, output_dir, args):
dataset = JsonDataset(dataset_name)
dets = load_object(os.path.join(output_dir, 'detections.pkl'))
# Override config with the one saved in the detections file
if args.cfg_file is not None:
core_config.merge_cfg_from_cfg(core_config.load_cfg(dets['cfg']))
else:
core_config._merge_a_into_b(core_config.load_cfg(dets['cfg']), cfg)
# re-filter on score threshold:
dets['all_boxes'] = \
[
[
im[im[:,4] > cfg.TEST.SCORE_THRESH,:] if len(im) != 0 else []
for im in cls
]
for cls in dets['all_boxes']
]
results = task_evaluation.evaluate_all(dataset,
dets['all_boxes'],
dets['all_segms'],
dets['all_keyps'],
output_dir,
use_matlab=args.matlab_eval)
task_evaluation.log_copy_paste_friendly_results(results)
def do_reval(dataset_name, output_dir, args):
dataset = JsonDataset(dataset_name)
dets = load_object(os.path.join(output_dir, 'detections.pkl'))
# Override config with the one saved in the detections file
if args.cfg_file is not None:
core_config.merge_cfg_from_cfg(core_config.load_cfg(dets['cfg']))
else:
core_config._merge_a_into_b(core_config.load_cfg(dets['cfg']), cfg)
results = task_evaluation.evaluate_all(dataset,
dets['all_boxes'],
dets['all_segms'],
dets['all_keyps'],
output_dir,
use_matlab=args.matlab_eval)
task_evaluation.log_copy_paste_friendly_results(results)
def do_reval(dataset_name, output_dir, args):
dataset = JsonDataset(dataset_name)
dets = load_object(os.path.join(output_dir, 'detections.pkl'))
# Override config with the one saved in the detections file
if args.cfg_file is not None:
core_config.merge_cfg_from_cfg(core_config.load_cfg(dets['cfg']))
else:
core_config._merge_a_into_b(core_config.load_cfg(dets['cfg']), cfg)
results = task_evaluation.evaluate_all(
dataset,
dets['all_boxes'],
dets['all_segms'],
dets['all_keyps'],
output_dir,
use_matlab=args.matlab_eval
)
task_evaluation.log_copy_paste_friendly_results(results)
def do_reval(dataset_name, output_dir, args):
dataset = JsonDataset(dataset_name)
with open(os.path.join(output_dir, 'detections.pkl'), 'rb') as f:
dets = pickle.load(f)
# Override config with the one saved in the detections file
if args.cfg_file is not None:
# bug: loads only already stored cfg
# core_config.merge_cfg_from_cfg(core_config.load_cfg(dets['cfg']))
# merge config from passed config file!!
core_config.merge_cfg_from_file(args.cfg_file)
else:
core_config._merge_a_into_b(core_config.load_cfg(dets['cfg']), cfg)
results = task_evaluation.evaluate_all(dataset,
dets['all_boxes'],
dets['all_segms'],
dets['all_keyps'],
output_dir,
use_matlab=args.matlab_eval)
task_evaluation.log_copy_paste_friendly_results(results)
