INNER CODE UNIT · Python
normalize_labels
idealo/image-quality-assessment · contrib/tf_serving/tfs_sample_client.py:14
def normalize_labels(labels):
labels_np = np.array(labels)
return labels_np / labels_np.sum()
def calc_mean_score(score_dist):
score_dist = normalize_labels(score_dist)
return (score_dist * np.arange(1, 11)).sum()
def get_image_quality_predictions(image_path, model_name):
# Load and preprocess image
image = utils.load_image(image_path, target_size=(224, 224))
image = keras.applications.mobilenet.preprocess_input(image)
# Run through model
target = f'{TFS_HOST}:{TFS_PORT}'
channel = grpc.insecure_channel(target)