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)