Removed MatrixData dataclass and used NumPy to represent Matrix
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kinaryml
parent
9aea1be6f9
commit
2753c79fde
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@ -82,15 +82,6 @@ py_library(
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],
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)
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py_library(
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name = "matrix_data",
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srcs = ["matrix_data.py"],
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deps = [
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"//mediapipe/framework/formats:matrix_data_py_pb2",
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"//mediapipe/tasks/python/core:optional_dependencies",
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],
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)
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py_library(
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name = "detections",
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srcs = ["detections.py"],
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@ -1,81 +0,0 @@
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# Copyright 2022 The MediaPipe Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""Matrix data data class."""
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import dataclasses
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import enum
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from typing import Any, Optional
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import numpy as np
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from mediapipe.framework.formats import matrix_data_pb2
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from mediapipe.tasks.python.core.optional_dependencies import doc_controls
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_MatrixDataProto = matrix_data_pb2.MatrixData
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class Layout(enum.Enum):
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COLUMN_MAJOR = 0
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ROW_MAJOR = 1
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@dataclasses.dataclass
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class MatrixData:
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"""This stores the Matrix data.
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Here the data is stored in column-major order by default.
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Attributes:
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rows: The number of rows in the matrix.
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cols: The number of columns in the matrix.
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data: The data stored in the matrix as a NumPy array.
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layout: The order in which the data are stored. Defaults to COLUMN_MAJOR.
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"""
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rows: int = None
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cols: int = None
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data: np.ndarray = None
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layout: Optional[Layout] = Layout.COLUMN_MAJOR
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@doc_controls.do_not_generate_docs
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def to_pb2(self) -> _MatrixDataProto:
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"""Generates a MatrixData protobuf object."""
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return _MatrixDataProto(
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rows=self.rows,
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cols=self.cols,
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packed_data=self.data,
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layout=self.layout.value)
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@classmethod
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@doc_controls.do_not_generate_docs
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def create_from_pb2(cls, pb2_obj: _MatrixDataProto) -> 'MatrixData':
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"""Creates a `MatrixData` object from the given protobuf object."""
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return MatrixData(
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rows=pb2_obj.rows,
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cols=pb2_obj.cols,
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data=np.array(pb2_obj.packed_data),
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layout=Layout(pb2_obj.layout))
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def __eq__(self, other: Any) -> bool:
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"""Checks if this object is equal to the given object.
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Args:
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other: The object to be compared with.
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Returns:
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True if the objects are equal.
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"""
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if not isinstance(other, MatrixData):
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return False
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return self.to_pb2().__eq__(other.to_pb2())
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@ -153,7 +153,6 @@ py_test(
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"//mediapipe/tasks/python/components/containers:category",
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"//mediapipe/tasks/python/components/containers:landmark",
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"//mediapipe/tasks/python/components/containers:rect",
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"//mediapipe/tasks/python/components/containers:matrix_data",
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"//mediapipe/tasks/python/core:base_options",
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"//mediapipe/tasks/python/test:test_utils",
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"//mediapipe/tasks/python/vision:face_landmarker",
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@ -26,7 +26,6 @@ from mediapipe.framework.formats import classification_pb2
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from mediapipe.python._framework_bindings import image as image_module
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from mediapipe.tasks.python.components.containers import category as category_module
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from mediapipe.tasks.python.components.containers import landmark as landmark_module
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from mediapipe.tasks.python.components.containers import matrix_data as matrix_data_module
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from mediapipe.tasks.python.components.containers import rect as rect_module
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from mediapipe.tasks.python.core import base_options as base_options_module
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from mediapipe.tasks.python.test import test_utils
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@ -39,7 +38,6 @@ _BaseOptions = base_options_module.BaseOptions
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_Category = category_module.Category
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_Rect = rect_module.Rect
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_Landmark = landmark_module.Landmark
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_MatrixData = matrix_data_module.MatrixData
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_NormalizedLandmark = landmark_module.NormalizedLandmark
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_Image = image_module.Image
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_FaceLandmarker = face_landmarker.FaceLandmarker
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@ -90,14 +88,12 @@ def _get_expected_face_blendshapes(file_path: str):
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def _make_expected_facial_transformation_matrixes():
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data = np.array([[0.9995292, -0.005092691, 0.030254554, -0.37340546],
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matrix = np.array([[0.9995292, -0.005092691, 0.030254554, -0.37340546],
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[0.0072318087, 0.99744856, -0.07102106, 22.212194],
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[-0.029815676, 0.07120642, 0.9970159, -64.76358],
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[0, 0, 0, 1]])
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rows, cols = len(data), len(data[0])
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facial_transformation_matrixes_results = []
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facial_transformation_matrix = _MatrixData(rows, cols, data.flatten())
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facial_transformation_matrixes_results.append(facial_transformation_matrix)
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facial_transformation_matrixes_results.append(matrix)
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return facial_transformation_matrixes_results
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@ -145,11 +141,13 @@ class FaceLandmarkerTest(parameterized.TestCase):
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self.assertLen(actual_matrix_list, len(expected_matrix_list))
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for i, rename_me in enumerate(actual_matrix_list):
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self.assertEqual(rename_me.rows, expected_matrix_list[i].rows)
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self.assertEqual(rename_me.cols, expected_matrix_list[i].cols)
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self.assertEqual(rename_me.shape[0],
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expected_matrix_list[i].shape[0])
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self.assertEqual(rename_me.shape[1],
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expected_matrix_list[i].shape[1])
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self.assertAlmostEqual(
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rename_me.data.all(),
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expected_matrix_list[i].data.all(),
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rename_me.all(),
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expected_matrix_list[i].all(),
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delta=_FACIAL_TRANSFORMATION_MATRIX_DIFF_MARGIN)
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def test_create_from_file_succeeds_with_valid_model_path(self):
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@ -189,7 +189,6 @@ py_library(
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"//mediapipe/tasks/cc/vision/face_geometry/proto:face_geometry_py_pb2",
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"//mediapipe/tasks/python/components/containers:category",
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"//mediapipe/tasks/python/components/containers:landmark",
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"//mediapipe/tasks/python/components/containers:matrix_data",
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"//mediapipe/tasks/python/core:base_options",
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"//mediapipe/tasks/python/core:optional_dependencies",
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"//mediapipe/tasks/python/core:task_info",
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@ -17,6 +17,7 @@ import dataclasses
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import enum
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from typing import Callable, Mapping, Optional, List
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import numpy as np
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from mediapipe.framework.formats import classification_pb2
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from mediapipe.framework.formats import landmark_pb2
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from mediapipe.framework.formats import matrix_data_pb2
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@ -29,7 +30,6 @@ from mediapipe.tasks.cc.vision.face_landmarker.proto import face_landmarker_grap
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from mediapipe.tasks.cc.vision.face_geometry.proto import face_geometry_pb2
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from mediapipe.tasks.python.components.containers import category as category_module
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from mediapipe.tasks.python.components.containers import landmark as landmark_module
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from mediapipe.tasks.python.components.containers import matrix_data as matrix_data_module
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from mediapipe.tasks.python.core import base_options as base_options_module
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from mediapipe.tasks.python.core import task_info as task_info_module
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from mediapipe.tasks.python.core.optional_dependencies import doc_controls
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@ -39,6 +39,7 @@ from mediapipe.tasks.python.vision.core import vision_task_running_mode as runni
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_BaseOptions = base_options_module.BaseOptions
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_FaceLandmarkerGraphOptionsProto = face_landmarker_graph_options_pb2.FaceLandmarkerGraphOptions
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_LayoutEnum = matrix_data_pb2.MatrixData.Layout
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_RunningMode = running_mode_module.VisionTaskRunningMode
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_ImageProcessingOptions = image_processing_options_module.ImageProcessingOptions
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_TaskInfo = task_info_module.TaskInfo
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@ -126,7 +127,7 @@ class FaceLandmarkerResult:
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face_landmarks: List[List[landmark_module.NormalizedLandmark]]
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face_blendshapes: List[List[category_module.Category]]
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facial_transformation_matrixes: List[matrix_data_module.MatrixData]
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facial_transformation_matrixes: List[np.ndarray]
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def _build_landmarker_result(
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@ -170,7 +171,9 @@ def _build_landmarker_result(
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if proto.pose_transform_matrix:
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matrix_data = matrix_data_pb2.MatrixData()
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matrix_data.MergeFrom(proto.pose_transform_matrix)
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matrix = matrix_data_module.MatrixData.create_from_pb2(matrix_data)
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order = 'C' if matrix_data.layout == _LayoutEnum.ROW_MAJOR else 'F'
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data = np.array(matrix_data.packed_data, order=order)
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matrix = data.reshape((matrix_data.rows, matrix_data.cols))
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facial_transformation_matrixes_results.append(matrix)
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return FaceLandmarkerResult(face_landmarks_results, face_blendshapes_results,
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