def predict_image(model_path: str, image: np.ndarray, show: bool = False):
pred = Prediction(model_path=model_path,
output_path=None,
patch_size=train_params['patch_size'],
batch_size=train_params['batch_size'],
offset=2 * train_params["n_layers"],
n_classes=len(classes_mask.keys()),
n_filters=train_params["n_filters"],
n_layers=train_params["n_layers"])
# image = np.array(Image.open(image)).astype(np.float32) / 255
predicted = pred.__predict_image__(image)
predicted = np.argmax(predicted, axis=2)
if show:
Image.fromarray(
colorize_mask(np.dstack((predicted, predicted, predicted)),
n_classes=pred.n_classes)).show()
return predicted
