def get_performance_wrap(run_path, det_file, beta=2):
config = loadfile(os.path.join(run_path, 'config.yaml'))
config = proc_config(config)
detections_test_file = os.path.join(run_path, det_file)
thresh, fppi, miss_rate, recall, precision = \
get_perform_measures_from_file(
os.path.join(config['data_path'], config['detect_test_set']),
detections_test_file,
overlap=config['overlap_threshold'])
fscore = get_fscore(recall, precision, beta=beta)
precision_recall_auc = metrics.auc(
recall, precision, reorder=True)
logavg_miss_rate = get_avg_miss_rate(fppi, miss_rate)
return dict(
precision_recall_auc=precision_recall_auc,
logavg_miss_rate=logavg_miss_rate,
thresh=thresh,
fppi=fppi,
miss_rate=miss_rate,
recall=recall,
precision=precision,
fscore=fscore,
)
def test_on_patches():
config = loadfile('config.yaml')
config['flag_debug'] = True
config = proc_config(config)
X_train_init, y_train_init, X_valid_init, y_valid_init = \
load_initial_data_wrap(config)
train_img_list = recover_image_from_vector(X_train_init)
valid_img_list = recover_image_from_vector(X_valid_init)
bowsvm = BowSvm(kernel='linear', C=100.)
time_start = time.time()
print 'training...'
bowsvm.fit(train_img_list, y_train_init)
print time.time() - time_start
time_start = time.time()
labels_pred_train = bowsvm.predict(train_img_list)
labels_pred_valid = bowsvm.predict(valid_img_list)
print time.time() - time_start
print accuracy_score(y_train_init, labels_pred_train)
print accuracy_score(y_valid_init, labels_pred_valid)
def get_image_level_performance_wrap(run_path, det_file, overlap=0.5, beta=2.):
config = loadfile(os.path.join(run_path, 'config.yaml'))
config = proc_config(config)
detections_test_file = os.path.join(run_path, det_file)
return get_image_level_performance_from_file(os.path.join(
config['data_path'], config['detect_test_set']),
detections_test_file,
overlap=overlap,
beta=beta)
x_cat = np.concatenate([
np.concatenate(x_pad[ind * num_row:(ind + 1) * num_row], axis=0)
for ind in range(num_col)
],
axis=1)
return x_cat
path = '/mnt/data/wding/tmp/bugs/bug_run_2015-04-14_20-58-36_39_single/misdetects0.pkl'
_, x_new_neg = loadfile(path)
config = loadfile('config.yaml')
config['flag_debug'] = True
config = proc_config(config)
config['dist_trans_list'] = (-5, 0, 5)
config['write_path'] = \
'/mnt/data/wding/tmp/bugs/bug_run_2015-04-14_20-58-36_39_single'
x, y, _, _ = load_initial_data_wrap(config)
# x_new_neg, _ = load_misclf_data_wrap(config, ind_round=1, data_set='train')
_, x_new_neg = loadfile(path)
x_new_neg = np.array(x_new_neg) / 255.
x_reshaped = np.rollaxis(x.reshape((-1, 3, 28, 28)), 1, 4) / 255.
x_pos = x_reshaped[y.astype(bool)]
num_unique = x_pos.shape[0] / 72
ind_unique = 1
indices = []