Esempi in Python per read_test_labels

Esempio n. 1

File: evaluate_submission.py Progetto: neouuid/dsb3

def leaderboard_performance(submission_file_path):
    real = utils_lung.read_test_labels(pathfinder.TEST_LABELS_PATH)
    pred = parse_predictions(submission_file_path)

    real = collections.OrderedDict(sorted(real.iteritems()))
    pred = collections.OrderedDict(sorted(pred.iteritems()))

    check_validity(real, pred)

    return log_loss(real.values(), pred.values())

Esempio n. 2

File: evaluate_submission.py Progetto: ericsolo/python

def leaderboard_performance(submission_file_path):
    real = utils_lung.read_test_labels(pathfinder.TEST_LABELS_PATH)
    pred = parse_predictions(submission_file_path)

    real = collections.OrderedDict(sorted(real.iteritems()))
    pred = collections.OrderedDict(sorted(pred.iteritems()))

    check_validity(real, pred)

    return log_loss(real.values(), pred.values())

Esempio n. 3

File: dsb_a_eliasq13_mal2_s5_p8a1.py Progetto: neouuid/dsb3

    if n_selection:
        all_candidates = all_candidates[:n_selection]
    return all_candidates


# data iterators
batch_size = 1

train_valid_ids = utils.load_pkl(pathfinder.VALIDATION_SPLIT_PATH)
train_pids, valid_pids, test_pids = train_valid_ids[
    'training'], train_valid_ids['validation'], train_valid_ids['test']
print('n train', len(train_pids))
print('n valid', len(valid_pids))

id2label = utils_lung.read_labels(pathfinder.LABELS_PATH)
id2label_test = utils_lung.read_test_labels(pathfinder.TEST_LABELS_PATH)
id2label_all = id2label.copy()
id2label_all.update(id2label_test)

train_data_iterator = data_iterators.DSBPatientsDataGenerator(
    data_path=pathfinder.DATA_PATH,
    batch_size=batch_size,
    transform_params=p_transform,
    n_candidates_per_patient=n_candidates_per_patient,
    data_prep_fun=data_prep_function_train,
    candidates_prep_fun=candidates_prep_function,
    id2candidates_path=id2candidates_path,
    id2label=id2label_all,
    rng=rng,
    patient_ids=train_pids,
    random=True,

Esempio n. 4

File: dsb_a_eliasq11_mal2_s5_p8a1_all.py Progetto: ericsolo/python

    if n_selection:
        all_candidates = all_candidates[:n_selection]
    return all_candidates

# data iterators
batch_size = 1
train_valid_ids = utils.load_pkl(pathfinder.VALIDATION_SPLIT_PATH)
train_pids, valid_pids, test_pids, stage2_pids = train_valid_ids['training'], train_valid_ids['validation'], train_valid_ids['test'], train_valid_ids['test_stage2']
print 'n train', len(train_pids)
print 'n valid', len(valid_pids)
print 'n test', len(test_pids)
all_pids = train_pids + valid_pids + test_pids


id2label = utils_lung.read_labels(pathfinder.LABELS_PATH)
id2label_test = utils_lung.read_test_labels(pathfinder.TEST_LABELS_PATH)


id2label_all = id2label.copy()
id2label_all.update(id2label_test)


train_data_iterator = data_iterators.DSBPatientsDataGenerator(data_path=pathfinder.DATA_PATH,
                                                              batch_size=batch_size,
                                                              transform_params=p_transform,
                                                              n_candidates_per_patient=n_candidates_per_patient,
                                                              data_prep_fun=data_prep_function_train,
                                                              candidates_prep_fun = candidates_prep_function,
                                                              id2candidates_path=id2candidates_path,
                                                              id2label = id2label_all,
                                                              rng=rng,