def get_faces(result): assert len(result.tensors) == 1 tensor = result.tensors['embeddings'] print(utils.shape_tuple(tensor.shape)) # assert utils.shape_tuple(tensor.shape) == (1, 1, 1, 2024) return tuple(tensor.data)
def _get_probs(result): assert len(result.tensors) == 1 tensor = result.tensors[_OUTPUT_TENSOR_NAME_MAP[result.model_name]] assert utils.shape_tuple(tensor.shape) == (1, 1, 1, len(CLASSES)) return tuple(tensor.data)
def _get_probs(result): assert len(result.tensors) == 1 tensor = result.tensors['result/Softmax'] assert utils.shape_tuple(tensor.shape) == (1, 1, 1, len(_CLASSES)) return tuple(tensor.data)
def _get_probs(result): assert len(result.tensors) == 1 tensor = result.tensors['MobilenetV1/Predictions/Softmax'] assert utils.shape_tuple(tensor.shape) == (1, 1, 1, 2024) return tuple(tensor.data)
def _get_probs(result): assert len(result.tensors) == 1 tensor = result.tensors['MobilenetV1/Predictions/Softmax'] assert utils.shape_tuple(tensor.shape) == (1, 1, 1, 2024) return tuple(tensor.data)