Project import generated by Copybara.
GitOrigin-RevId: 1610e588e497817fae2d9a458093ab6a370e2972
This commit is contained in:
MediaPipe Team
@@ -224,6 +224,7 @@ class SolutionBase:
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calculator_params is not allowed to be modified.
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e) If the calculator options field is a repeated field but the field
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value to be set is not iterable.
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f) If not all calculator params are valid.
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"""
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if bool(binary_graph_path) == bool(graph_config):
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raise ValueError(
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@@ -499,6 +500,8 @@ class SolutionBase:
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# have been visited.
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if num_modified == len(nested_calculator_params):
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break
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if num_modified < len(nested_calculator_params):
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raise ValueError('Not all calculator params are valid.')
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def _make_packet(self, packet_data_type: _PacketDataType,
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data: Any) -> packet.Packet:
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@@ -18,7 +18,9 @@ import mediapipe.python.solutions.drawing_styles
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import mediapipe.python.solutions.drawing_utils
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import mediapipe.python.solutions.face_detection
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import mediapipe.python.solutions.face_mesh
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import mediapipe.python.solutions.face_mesh_connections
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import mediapipe.python.solutions.hands
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import mediapipe.python.solutions.hands_connections
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import mediapipe.python.solutions.holistic
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import mediapipe.python.solutions.objectron
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import mediapipe.python.solutions.pose
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@@ -15,17 +15,21 @@
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from typing import Mapping, Tuple
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from mediapipe.python.solutions import face_mesh_connections
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from mediapipe.python.solutions import hands_connections
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from mediapipe.python.solutions.drawing_utils import DrawingSpec
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from mediapipe.python.solutions.hands import HandLandmark
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from mediapipe.python.solutions.pose import PoseLandmark
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_RADIUS = 5
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_RED = (54, 67, 244)
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_GREEN = (118, 230, 0)
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_RED = (48, 48, 255)
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_GREEN = (48, 255, 48)
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_BLUE = (192, 101, 21)
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_YELLOW = (0, 204, 255)
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_GRAY = (174, 164, 144)
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_GRAY = (128, 128, 128)
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_PURPLE = (128, 64, 128)
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_PEACH = (180, 229, 255)
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_WHITE = (224, 224, 224)
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# Hands
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_THICKNESS_WRIST_MCP = 3
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@@ -70,60 +74,69 @@ _HAND_LANDMARK_STYLE = {
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color=_BLUE, thickness=_THICKNESS_DOT, circle_radius=_RADIUS),
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}
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# Hand connections
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_PALM_CONNECTIONS = ((HandLandmark.WRIST, HandLandmark.THUMB_CMC),
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(HandLandmark.WRIST, HandLandmark.INDEX_FINGER_MCP),
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(HandLandmark.MIDDLE_FINGER_MCP,
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HandLandmark.RING_FINGER_MCP),
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(HandLandmark.RING_FINGER_MCP, HandLandmark.PINKY_MCP),
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(HandLandmark.INDEX_FINGER_MCP,
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HandLandmark.MIDDLE_FINGER_MCP), (HandLandmark.WRIST,
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HandLandmark.PINKY_MCP))
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_THUMB_CONNECTIONS = ((HandLandmark.THUMB_CMC, HandLandmark.THUMB_MCP),
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(HandLandmark.THUMB_MCP, HandLandmark.THUMB_IP),
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(HandLandmark.THUMB_IP, HandLandmark.THUMB_TIP))
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_INDEX_FINGER_CONNECTIONS = ((HandLandmark.INDEX_FINGER_MCP,
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HandLandmark.INDEX_FINGER_PIP),
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(HandLandmark.INDEX_FINGER_PIP,
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HandLandmark.INDEX_FINGER_DIP),
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(HandLandmark.INDEX_FINGER_DIP,
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HandLandmark.INDEX_FINGER_TIP))
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_MIDDLE_FINGER_CONNECTIONS = ((HandLandmark.MIDDLE_FINGER_MCP,
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HandLandmark.MIDDLE_FINGER_PIP),
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(HandLandmark.MIDDLE_FINGER_PIP,
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HandLandmark.MIDDLE_FINGER_DIP),
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(HandLandmark.MIDDLE_FINGER_DIP,
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HandLandmark.MIDDLE_FINGER_TIP))
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_RING_FINGER_CONNECTIONS = ((HandLandmark.RING_FINGER_MCP,
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HandLandmark.RING_FINGER_PIP),
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(HandLandmark.RING_FINGER_PIP,
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HandLandmark.RING_FINGER_DIP),
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(HandLandmark.RING_FINGER_DIP,
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HandLandmark.RING_FINGER_TIP))
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_PINKY_FINGER_CONNECTIONS = ((HandLandmark.PINKY_MCP, HandLandmark.PINKY_PIP),
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(HandLandmark.PINKY_PIP, HandLandmark.PINKY_DIP),
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(HandLandmark.PINKY_DIP, HandLandmark.PINKY_TIP))
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# Hands connections
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_HAND_CONNECTION_STYLE = {
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_PALM_CONNECTIONS:
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hands_connections.HAND_PALM_CONNECTIONS:
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DrawingSpec(color=_GRAY, thickness=_THICKNESS_WRIST_MCP),
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_THUMB_CONNECTIONS:
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hands_connections.HAND_THUMB_CONNECTIONS:
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DrawingSpec(color=_PEACH, thickness=_THICKNESS_FINGER),
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_INDEX_FINGER_CONNECTIONS:
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hands_connections.HAND_INDEX_FINGER_CONNECTIONS:
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DrawingSpec(color=_PURPLE, thickness=_THICKNESS_FINGER),
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_MIDDLE_FINGER_CONNECTIONS:
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hands_connections.HAND_MIDDLE_FINGER_CONNECTIONS:
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DrawingSpec(color=_YELLOW, thickness=_THICKNESS_FINGER),
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_RING_FINGER_CONNECTIONS:
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hands_connections.HAND_RING_FINGER_CONNECTIONS:
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DrawingSpec(color=_GREEN, thickness=_THICKNESS_FINGER),
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_PINKY_FINGER_CONNECTIONS:
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hands_connections.HAND_PINKY_FINGER_CONNECTIONS:
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DrawingSpec(color=_BLUE, thickness=_THICKNESS_FINGER)
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}
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# FaceMesh connections
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_THICKNESS_TESSELATION = 1
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_THICKNESS_CONTOURS = 2
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_FACEMESH_CONTOURS_CONNECTION_STYLE = {
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face_mesh_connections.FACEMESH_LIPS:
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DrawingSpec(color=_WHITE, thickness=_THICKNESS_CONTOURS),
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face_mesh_connections.FACEMESH_LEFT_EYE:
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DrawingSpec(color=_GREEN, thickness=_THICKNESS_CONTOURS),
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face_mesh_connections.FACEMESH_LEFT_EYEBROW:
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DrawingSpec(color=_GREEN, thickness=_THICKNESS_CONTOURS),
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face_mesh_connections.FACEMESH_RIGHT_EYE:
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DrawingSpec(color=_RED, thickness=_THICKNESS_CONTOURS),
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face_mesh_connections.FACEMESH_RIGHT_EYEBROW:
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DrawingSpec(color=_RED, thickness=_THICKNESS_CONTOURS),
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face_mesh_connections.FACEMESH_FACE_OVAL:
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DrawingSpec(color=_WHITE, thickness=_THICKNESS_CONTOURS)
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}
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def get_default_hand_landmark_style() -> Mapping[int, DrawingSpec]:
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"""Returns the default hand landmark drawing style.
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# Pose
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_THICKNESS_POSE_LANDMARKS = 2
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_POSE_LANDMARKS_LEFT = frozenset([
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PoseLandmark.LEFT_EYE_INNER, PoseLandmark.LEFT_EYE,
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PoseLandmark.LEFT_EYE_OUTER, PoseLandmark.LEFT_EAR, PoseLandmark.MOUTH_LEFT,
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PoseLandmark.LEFT_SHOULDER, PoseLandmark.LEFT_ELBOW,
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PoseLandmark.LEFT_WRIST, PoseLandmark.LEFT_PINKY, PoseLandmark.LEFT_INDEX,
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PoseLandmark.LEFT_THUMB, PoseLandmark.LEFT_HIP, PoseLandmark.LEFT_KNEE,
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PoseLandmark.LEFT_ANKLE, PoseLandmark.LEFT_HEEL,
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PoseLandmark.LEFT_FOOT_INDEX
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])
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_POSE_LANDMARKS_RIGHT = frozenset([
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PoseLandmark.RIGHT_EYE_INNER, PoseLandmark.RIGHT_EYE,
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PoseLandmark.RIGHT_EYE_OUTER, PoseLandmark.RIGHT_EAR,
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PoseLandmark.MOUTH_RIGHT, PoseLandmark.RIGHT_SHOULDER,
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PoseLandmark.RIGHT_ELBOW, PoseLandmark.RIGHT_WRIST,
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PoseLandmark.RIGHT_PINKY, PoseLandmark.RIGHT_INDEX,
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PoseLandmark.RIGHT_THUMB, PoseLandmark.RIGHT_HIP, PoseLandmark.RIGHT_KNEE,
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PoseLandmark.RIGHT_ANKLE, PoseLandmark.RIGHT_HEEL,
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PoseLandmark.RIGHT_FOOT_INDEX
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])
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def get_default_hand_landmarks_style() -> Mapping[int, DrawingSpec]:
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"""Returns the default hand landmarks drawing style.
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Returns:
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A mapping from each hand landmark to the default drawing spec.
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A mapping from each hand landmark to its default drawing spec.
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"""
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hand_landmark_style = {}
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for k, v in _HAND_LANDMARK_STYLE.items():
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@@ -132,15 +145,59 @@ def get_default_hand_landmark_style() -> Mapping[int, DrawingSpec]:
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return hand_landmark_style
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def get_default_hand_connection_style(
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def get_default_hand_connections_style(
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) -> Mapping[Tuple[int, int], DrawingSpec]:
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"""Returns the default hand connection drawing style.
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"""Returns the default hand connections drawing style.
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Returns:
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A mapping from each hand connection to the default drawing spec.
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A mapping from each hand connection to its default drawing spec.
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"""
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hand_connection_style = {}
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for k, v in _HAND_CONNECTION_STYLE.items():
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for connection in k:
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hand_connection_style[connection] = v
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return hand_connection_style
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def get_default_face_mesh_contours_style(
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) -> Mapping[Tuple[int, int], DrawingSpec]:
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"""Returns the default face mesh contours drawing style.
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Returns:
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A mapping from each face mesh contours connection to its default drawing
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spec.
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"""
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face_mesh_contours_connection_style = {}
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for k, v in _FACEMESH_CONTOURS_CONNECTION_STYLE.items():
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for connection in k:
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face_mesh_contours_connection_style[connection] = v
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return face_mesh_contours_connection_style
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def get_default_face_mesh_tesselation_style() -> DrawingSpec:
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"""Returns the default face mesh tesselation drawing style.
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Returns:
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A DrawingSpec.
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"""
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return DrawingSpec(color=_GRAY, thickness=_THICKNESS_TESSELATION)
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def get_default_pose_landmarks_style() -> Mapping[int, DrawingSpec]:
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"""Returns the default pose landmarks drawing style.
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Returns:
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A mapping from each pose landmark to its default drawing spec.
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"""
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pose_landmark_style = {}
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left_spec = DrawingSpec(
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color=(0, 138, 255), thickness=_THICKNESS_POSE_LANDMARKS)
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right_spec = DrawingSpec(
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color=(231, 217, 0), thickness=_THICKNESS_POSE_LANDMARKS)
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for landmark in _POSE_LANDMARKS_LEFT:
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pose_landmark_style[landmark] = left_spec
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for landmark in _POSE_LANDMARKS_RIGHT:
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pose_landmark_style[landmark] = right_spec
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pose_landmark_style[PoseLandmark.NOSE] = DrawingSpec(
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color=_WHITE, thickness=_THICKNESS_POSE_LANDMARKS)
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return pose_landmark_style
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@@ -26,19 +26,21 @@ from mediapipe.framework.formats import detection_pb2
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from mediapipe.framework.formats import location_data_pb2
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from mediapipe.framework.formats import landmark_pb2
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PRESENCE_THRESHOLD = 0.5
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RGB_CHANNELS = 3
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_PRESENCE_THRESHOLD = 0.5
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_VISIBILITY_THRESHOLD = 0.5
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_RGB_CHANNELS = 3
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WHITE_COLOR = (224, 224, 224)
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BLACK_COLOR = (0, 0, 0)
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RED_COLOR = (0, 0, 255)
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GREEN_COLOR = (0, 128, 0)
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BLUE_COLOR = (255, 0, 0)
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VISIBILITY_THRESHOLD = 0.5
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@dataclasses.dataclass
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class DrawingSpec:
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# Color for drawing the annotation. Default to the green color.
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color: Tuple[int, int, int] = (0, 255, 0)
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# Color for drawing the annotation. Default to the white color.
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color: Tuple[int, int, int] = WHITE_COLOR
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# Thickness for drawing the annotation. Default to 2 pixels.
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thickness: int = 2
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# Circle radius. Default to 2 pixels.
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@@ -86,7 +88,7 @@ def draw_detection(
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"""
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if not detection.location_data:
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return
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if image.shape[2] != RGB_CHANNELS:
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if image.shape[2] != _RGB_CHANNELS:
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raise ValueError('Input image must contain three channel rgb data.')
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image_rows, image_cols, _ = image.shape
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@@ -147,15 +149,15 @@ def draw_landmarks(
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"""
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if not landmark_list:
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return
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if image.shape[2] != RGB_CHANNELS:
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if image.shape[2] != _RGB_CHANNELS:
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raise ValueError('Input image must contain three channel rgb data.')
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image_rows, image_cols, _ = image.shape
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idx_to_coordinates = {}
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for idx, landmark in enumerate(landmark_list.landmark):
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if ((landmark.HasField('visibility') and
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landmark.visibility < VISIBILITY_THRESHOLD) or
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landmark.visibility < _VISIBILITY_THRESHOLD) or
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(landmark.HasField('presence') and
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landmark.presence < PRESENCE_THRESHOLD)):
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landmark.presence < _PRESENCE_THRESHOLD)):
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continue
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landmark_px = _normalized_to_pixel_coordinates(landmark.x, landmark.y,
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image_cols, image_rows)
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@@ -178,11 +180,18 @@ def draw_landmarks(
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drawing_spec.thickness)
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# Draws landmark points after finishing the connection lines, which is
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# aesthetically better.
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for idx, landmark_px in idx_to_coordinates.items():
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drawing_spec = landmark_drawing_spec[idx] if isinstance(
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landmark_drawing_spec, Mapping) else landmark_drawing_spec
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cv2.circle(image, landmark_px, drawing_spec.circle_radius,
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drawing_spec.color, drawing_spec.thickness)
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if landmark_drawing_spec:
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for idx, landmark_px in idx_to_coordinates.items():
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drawing_spec = landmark_drawing_spec[idx] if isinstance(
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landmark_drawing_spec, Mapping) else landmark_drawing_spec
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# White circle border
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circle_border_radius = max(drawing_spec.circle_radius + 1,
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int(drawing_spec.circle_radius * 1.2))
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cv2.circle(image, landmark_px, circle_border_radius, WHITE_COLOR,
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drawing_spec.thickness)
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# Fill color into the circle
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cv2.circle(image, landmark_px, drawing_spec.circle_radius,
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drawing_spec.color, drawing_spec.thickness)
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def draw_axis(
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@@ -209,7 +218,7 @@ def draw_axis(
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ValueError: If one of the followings:
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a) If the input image is not three channel RGB.
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"""
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if image.shape[2] != RGB_CHANNELS:
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if image.shape[2] != _RGB_CHANNELS:
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raise ValueError('Input image must contain three channel rgb data.')
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image_rows, image_cols, _ = image.shape
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# Create axis points in camera coordinate frame.
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@@ -231,8 +240,7 @@ def draw_axis(
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x_axis = (x_im[1], y_im[1])
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y_axis = (x_im[2], y_im[2])
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z_axis = (x_im[3], y_im[3])
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cv2.arrowedLine(image, origin, x_axis, RED_COLOR,
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axis_drawing_spec.thickness)
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cv2.arrowedLine(image, origin, x_axis, RED_COLOR, axis_drawing_spec.thickness)
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cv2.arrowedLine(image, origin, y_axis, GREEN_COLOR,
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axis_drawing_spec.thickness)
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cv2.arrowedLine(image, origin, z_axis, BLUE_COLOR,
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@@ -274,9 +282,9 @@ def plot_landmarks(landmark_list: landmark_pb2.NormalizedLandmarkList,
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plotted_landmarks = {}
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for idx, landmark in enumerate(landmark_list.landmark):
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if ((landmark.HasField('visibility') and
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landmark.visibility < VISIBILITY_THRESHOLD) or
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landmark.visibility < _VISIBILITY_THRESHOLD) or
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(landmark.HasField('presence') and
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landmark.presence < PRESENCE_THRESHOLD)):
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landmark.presence < _PRESENCE_THRESHOLD)):
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continue
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ax.scatter3D(
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xs=[-landmark.z],
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@@ -29,6 +29,7 @@ DEFAULT_BBOX_DRAWING_SPEC = drawing_utils.DrawingSpec()
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DEFAULT_CONNECTION_DRAWING_SPEC = drawing_utils.DrawingSpec()
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DEFAULT_CIRCLE_DRAWING_SPEC = drawing_utils.DrawingSpec(color=(0, 0, 255))
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DEFAULT_AXIS_DRAWING_SPEC = drawing_utils.DrawingSpec()
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DEFAULT_CYCLE_BORDER_COLOR = (224, 224, 224)
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class DrawingUtilTest(parameterized.TestCase):
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@@ -104,6 +105,10 @@ class DrawingUtilTest(parameterized.TestCase):
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landmark_pb2.NormalizedLandmarkList())
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image = np.zeros((100, 100, 3), np.uint8)
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expected_result = np.copy(image)
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cv2.circle(expected_result, (10, 10),
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DEFAULT_CIRCLE_DRAWING_SPEC.circle_radius + 1,
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DEFAULT_CYCLE_BORDER_COLOR,
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DEFAULT_CIRCLE_DRAWING_SPEC.thickness)
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cv2.circle(expected_result, (10, 10),
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DEFAULT_CIRCLE_DRAWING_SPEC.circle_radius,
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DEFAULT_CIRCLE_DRAWING_SPEC.color,
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@@ -127,6 +132,14 @@ class DrawingUtilTest(parameterized.TestCase):
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cv2.line(expected_result, start_point, end_point,
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DEFAULT_CONNECTION_DRAWING_SPEC.color,
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DEFAULT_CONNECTION_DRAWING_SPEC.thickness)
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cv2.circle(expected_result, start_point,
|
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DEFAULT_CIRCLE_DRAWING_SPEC.circle_radius + 1,
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DEFAULT_CYCLE_BORDER_COLOR,
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DEFAULT_CIRCLE_DRAWING_SPEC.thickness)
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cv2.circle(expected_result, end_point,
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DEFAULT_CIRCLE_DRAWING_SPEC.circle_radius + 1,
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DEFAULT_CYCLE_BORDER_COLOR,
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||||
DEFAULT_CIRCLE_DRAWING_SPEC.thickness)
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cv2.circle(expected_result, start_point,
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DEFAULT_CIRCLE_DRAWING_SPEC.circle_radius,
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DEFAULT_CIRCLE_DRAWING_SPEC.color,
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||||
@@ -187,6 +200,14 @@ class DrawingUtilTest(parameterized.TestCase):
|
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cv2.line(expected_result, start_point, end_point,
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||||
DEFAULT_CONNECTION_DRAWING_SPEC.color,
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||||
DEFAULT_CONNECTION_DRAWING_SPEC.thickness)
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||||
cv2.circle(expected_result, start_point,
|
||||
DEFAULT_CIRCLE_DRAWING_SPEC.circle_radius + 1,
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||||
DEFAULT_CYCLE_BORDER_COLOR,
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||||
DEFAULT_CIRCLE_DRAWING_SPEC.thickness)
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||||
cv2.circle(expected_result, end_point,
|
||||
DEFAULT_CIRCLE_DRAWING_SPEC.circle_radius + 1,
|
||||
DEFAULT_CYCLE_BORDER_COLOR,
|
||||
DEFAULT_CIRCLE_DRAWING_SPEC.thickness)
|
||||
cv2.circle(expected_result, start_point,
|
||||
DEFAULT_CIRCLE_DRAWING_SPEC.circle_radius,
|
||||
DEFAULT_CIRCLE_DRAWING_SPEC.color,
|
||||
@@ -213,6 +234,12 @@ class DrawingUtilTest(parameterized.TestCase):
|
||||
end_point = (80, 80)
|
||||
cv2.line(expected_result, start_point, end_point,
|
||||
connection_drawing_spec.color, connection_drawing_spec.thickness)
|
||||
cv2.circle(expected_result, start_point,
|
||||
landmark_drawing_spec.circle_radius + 1,
|
||||
DEFAULT_CYCLE_BORDER_COLOR, landmark_drawing_spec.thickness)
|
||||
cv2.circle(expected_result, end_point,
|
||||
landmark_drawing_spec.circle_radius + 1,
|
||||
DEFAULT_CYCLE_BORDER_COLOR, landmark_drawing_spec.thickness)
|
||||
cv2.circle(expected_result, start_point,
|
||||
landmark_drawing_spec.circle_radius, landmark_drawing_spec.color,
|
||||
landmark_drawing_spec.thickness)
|
||||
|
||||
@@ -36,140 +36,19 @@ from mediapipe.calculators.util import rect_transformation_calculator_pb2
|
||||
from mediapipe.calculators.util import thresholding_calculator_pb2
|
||||
# pylint: enable=unused-import
|
||||
from mediapipe.python.solution_base import SolutionBase
|
||||
# pylint: disable=unused-import
|
||||
from mediapipe.python.solutions.face_mesh_connections import FACEMESH_CONTOURS
|
||||
from mediapipe.python.solutions.face_mesh_connections import FACEMESH_FACE_OVAL
|
||||
from mediapipe.python.solutions.face_mesh_connections import FACEMESH_LEFT_EYE
|
||||
from mediapipe.python.solutions.face_mesh_connections import FACEMESH_LEFT_EYEBROW
|
||||
from mediapipe.python.solutions.face_mesh_connections import FACEMESH_LIPS
|
||||
from mediapipe.python.solutions.face_mesh_connections import FACEMESH_RIGHT_EYE
|
||||
from mediapipe.python.solutions.face_mesh_connections import FACEMESH_RIGHT_EYEBROW
|
||||
from mediapipe.python.solutions.face_mesh_connections import FACEMESH_TESSELATION
|
||||
# pylint: enable=unused-import
|
||||
|
||||
|
||||
BINARYPB_FILE_PATH = 'mediapipe/modules/face_landmark/face_landmark_front_cpu.binarypb'
|
||||
FACE_CONNECTIONS = frozenset([
|
||||
# Lips.
|
||||
(61, 146),
|
||||
(146, 91),
|
||||
(91, 181),
|
||||
(181, 84),
|
||||
(84, 17),
|
||||
(17, 314),
|
||||
(314, 405),
|
||||
(405, 321),
|
||||
(321, 375),
|
||||
(375, 291),
|
||||
(61, 185),
|
||||
(185, 40),
|
||||
(40, 39),
|
||||
(39, 37),
|
||||
(37, 0),
|
||||
(0, 267),
|
||||
(267, 269),
|
||||
(269, 270),
|
||||
(270, 409),
|
||||
(409, 291),
|
||||
(78, 95),
|
||||
(95, 88),
|
||||
(88, 178),
|
||||
(178, 87),
|
||||
(87, 14),
|
||||
(14, 317),
|
||||
(317, 402),
|
||||
(402, 318),
|
||||
(318, 324),
|
||||
(324, 308),
|
||||
(78, 191),
|
||||
(191, 80),
|
||||
(80, 81),
|
||||
(81, 82),
|
||||
(82, 13),
|
||||
(13, 312),
|
||||
(312, 311),
|
||||
(311, 310),
|
||||
(310, 415),
|
||||
(415, 308),
|
||||
# Left eye.
|
||||
(263, 249),
|
||||
(249, 390),
|
||||
(390, 373),
|
||||
(373, 374),
|
||||
(374, 380),
|
||||
(380, 381),
|
||||
(381, 382),
|
||||
(382, 362),
|
||||
(263, 466),
|
||||
(466, 388),
|
||||
(388, 387),
|
||||
(387, 386),
|
||||
(386, 385),
|
||||
(385, 384),
|
||||
(384, 398),
|
||||
(398, 362),
|
||||
# Left eyebrow.
|
||||
(276, 283),
|
||||
(283, 282),
|
||||
(282, 295),
|
||||
(295, 285),
|
||||
(300, 293),
|
||||
(293, 334),
|
||||
(334, 296),
|
||||
(296, 336),
|
||||
# Right eye.
|
||||
(33, 7),
|
||||
(7, 163),
|
||||
(163, 144),
|
||||
(144, 145),
|
||||
(145, 153),
|
||||
(153, 154),
|
||||
(154, 155),
|
||||
(155, 133),
|
||||
(33, 246),
|
||||
(246, 161),
|
||||
(161, 160),
|
||||
(160, 159),
|
||||
(159, 158),
|
||||
(158, 157),
|
||||
(157, 173),
|
||||
(173, 133),
|
||||
# Right eyebrow.
|
||||
(46, 53),
|
||||
(53, 52),
|
||||
(52, 65),
|
||||
(65, 55),
|
||||
(70, 63),
|
||||
(63, 105),
|
||||
(105, 66),
|
||||
(66, 107),
|
||||
# Face oval.
|
||||
(10, 338),
|
||||
(338, 297),
|
||||
(297, 332),
|
||||
(332, 284),
|
||||
(284, 251),
|
||||
(251, 389),
|
||||
(389, 356),
|
||||
(356, 454),
|
||||
(454, 323),
|
||||
(323, 361),
|
||||
(361, 288),
|
||||
(288, 397),
|
||||
(397, 365),
|
||||
(365, 379),
|
||||
(379, 378),
|
||||
(378, 400),
|
||||
(400, 377),
|
||||
(377, 152),
|
||||
(152, 148),
|
||||
(148, 176),
|
||||
(176, 149),
|
||||
(149, 150),
|
||||
(150, 136),
|
||||
(136, 172),
|
||||
(172, 58),
|
||||
(58, 132),
|
||||
(132, 93),
|
||||
(93, 234),
|
||||
(234, 127),
|
||||
(127, 162),
|
||||
(162, 21),
|
||||
(21, 54),
|
||||
(54, 103),
|
||||
(103, 67),
|
||||
(67, 109),
|
||||
(109, 10)
|
||||
])
|
||||
|
||||
|
||||
class FaceMesh(SolutionBase):
|
||||
@@ -213,7 +92,7 @@ class FaceMesh(SolutionBase):
|
||||
.ConstantSidePacketCalculatorOptions.ConstantSidePacket(
|
||||
bool_value=not static_image_mode)
|
||||
],
|
||||
'facedetectionshortrangecpu__TensorsToDetectionsCalculator.min_score_thresh':
|
||||
'facedetectionshortrangecpu__facedetectionshortrangecommon__TensorsToDetectionsCalculator.min_score_thresh':
|
||||
min_detection_confidence,
|
||||
'facelandmarkcpu__ThresholdingCalculator.threshold':
|
||||
min_tracking_confidence,
|
||||
|
||||
@@ -0,0 +1,485 @@
|
||||
# Copyright 2021 The MediaPipe Authors.
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
#
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
"""MediaPipe FaceMesh connections."""
|
||||
|
||||
FACEMESH_LIPS = frozenset([(61, 146), (146, 91), (91, 181), (181, 84), (84, 17),
|
||||
(17, 314), (314, 405), (405, 321), (321, 375),
|
||||
(375, 291), (61, 185), (185, 40), (40, 39), (39, 37),
|
||||
(37, 0), (0, 267),
|
||||
(267, 269), (269, 270), (270, 409), (409, 291),
|
||||
(78, 95), (95, 88), (88, 178), (178, 87), (87, 14),
|
||||
(14, 317), (317, 402), (402, 318), (318, 324),
|
||||
(324, 308), (78, 191), (191, 80), (80, 81), (81, 82),
|
||||
(82, 13), (13, 312), (312, 311), (311, 310),
|
||||
(310, 415), (415, 308)])
|
||||
|
||||
FACEMESH_LEFT_EYE = frozenset([(263, 249), (249, 390), (390, 373), (373, 374),
|
||||
(374, 380), (380, 381), (381, 382), (382, 362),
|
||||
(263, 466), (466, 388), (388, 387), (387, 386),
|
||||
(386, 385), (385, 384), (384, 398), (398, 362)])
|
||||
|
||||
FACEMESH_LEFT_EYEBROW = frozenset([(276, 283), (283, 282), (282, 295),
|
||||
(295, 285), (300, 293), (293, 334),
|
||||
(334, 296), (296, 336)])
|
||||
|
||||
FACEMESH_RIGHT_EYE = frozenset([(33, 7), (7, 163), (163, 144), (144, 145),
|
||||
(145, 153), (153, 154), (154, 155), (155, 133),
|
||||
(33, 246), (246, 161), (161, 160), (160, 159),
|
||||
(159, 158), (158, 157), (157, 173), (173, 133)])
|
||||
|
||||
FACEMESH_RIGHT_EYEBROW = frozenset([(46, 53), (53, 52), (52, 65), (65, 55),
|
||||
(70, 63), (63, 105), (105, 66), (66, 107)])
|
||||
|
||||
FACEMESH_FACE_OVAL = frozenset([(10, 338), (338, 297), (297, 332), (332, 284),
|
||||
(284, 251), (251, 389), (389, 356), (356, 454),
|
||||
(454, 323), (323, 361), (361, 288), (288, 397),
|
||||
(397, 365), (365, 379), (379, 378), (378, 400),
|
||||
(400, 377), (377, 152), (152, 148), (148, 176),
|
||||
(176, 149), (149, 150), (150, 136), (136, 172),
|
||||
(172, 58), (58, 132), (132, 93), (93, 234),
|
||||
(234, 127), (127, 162), (162, 21), (21, 54),
|
||||
(54, 103), (103, 67), (67, 109), (109, 10)])
|
||||
|
||||
FACEMESH_CONTOURS = frozenset().union(*[
|
||||
FACEMESH_LIPS, FACEMESH_LEFT_EYE, FACEMESH_LEFT_EYEBROW, FACEMESH_RIGHT_EYE,
|
||||
FACEMESH_RIGHT_EYEBROW, FACEMESH_FACE_OVAL
|
||||
])
|
||||
|
||||
FACEMESH_TESSELATION = frozenset([
|
||||
(127, 34), (34, 139), (139, 127), (11, 0), (0, 37), (37, 11),
|
||||
(232, 231), (231, 120), (120, 232), (72, 37), (37, 39), (39, 72),
|
||||
(128, 121), (121, 47), (47, 128), (232, 121), (121, 128), (128, 232),
|
||||
(104, 69), (69, 67), (67, 104), (175, 171), (171, 148), (148, 175),
|
||||
(118, 50), (50, 101), (101, 118), (73, 39), (39, 40), (40, 73),
|
||||
(9, 151), (151, 108), (108, 9), (48, 115), (115, 131), (131, 48),
|
||||
(194, 204), (204, 211), (211, 194), (74, 40), (40, 185), (185, 74),
|
||||
(80, 42), (42, 183), (183, 80), (40, 92), (92, 186), (186, 40),
|
||||
(230, 229), (229, 118), (118, 230), (202, 212), (212, 214), (214, 202),
|
||||
(83, 18), (18, 17), (17, 83), (76, 61), (61, 146), (146, 76),
|
||||
(160, 29), (29, 30), (30, 160), (56, 157), (157, 173), (173, 56),
|
||||
(106, 204), (204, 194), (194, 106), (135, 214), (214, 192), (192, 135),
|
||||
(203, 165), (165, 98), (98, 203), (21, 71), (71, 68), (68, 21),
|
||||
(51, 45), (45, 4), (4, 51), (144, 24), (24, 23), (23, 144),
|
||||
(77, 146), (146, 91), (91, 77), (205, 50), (50, 187), (187, 205),
|
||||
(201, 200), (200, 18), (18, 201), (91, 106), (106, 182), (182, 91),
|
||||
(90, 91), (91, 181), (181, 90), (85, 84), (84, 17), (17, 85),
|
||||
(206, 203), (203, 36), (36, 206), (148, 171), (171, 140), (140, 148),
|
||||
(92, 40), (40, 39), (39, 92), (193, 189), (189, 244), (244, 193),
|
||||
(159, 158), (158, 28), (28, 159), (247, 246), (246, 161), (161, 247),
|
||||
(236, 3), (3, 196), (196, 236), (54, 68), (68, 104), (104, 54),
|
||||
(193, 168), (168, 8), (8, 193), (117, 228), (228, 31), (31, 117),
|
||||
(189, 193), (193, 55), (55, 189), (98, 97), (97, 99), (99, 98),
|
||||
(126, 47), (47, 100), (100, 126), (166, 79), (79, 218), (218, 166),
|
||||
(155, 154), (154, 26), (26, 155), (209, 49), (49, 131), (131, 209),
|
||||
(135, 136), (136, 150), (150, 135), (47, 126), (126, 217), (217, 47),
|
||||
(223, 52), (52, 53), (53, 223), (45, 51), (51, 134), (134, 45),
|
||||
(211, 170), (170, 140), (140, 211), (67, 69), (69, 108), (108, 67),
|
||||
(43, 106), (106, 91), (91, 43), (230, 119), (119, 120), (120, 230),
|
||||
(226, 130), (130, 247), (247, 226), (63, 53), (53, 52), (52, 63),
|
||||
(238, 20), (20, 242), (242, 238), (46, 70), (70, 156), (156, 46),
|
||||
(78, 62), (62, 96), (96, 78), (46, 53), (53, 63), (63, 46),
|
||||
(143, 34), (34, 227), (227, 143), (123, 117), (117, 111), (111, 123),
|
||||
(44, 125), (125, 19), (19, 44), (236, 134), (134, 51), (51, 236),
|
||||
(216, 206), (206, 205), (205, 216), (154, 153), (153, 22), (22, 154),
|
||||
(39, 37), (37, 167), (167, 39), (200, 201), (201, 208), (208, 200),
|
||||
(36, 142), (142, 100), (100, 36), (57, 212), (212, 202), (202, 57),
|
||||
(20, 60), (60, 99), (99, 20), (28, 158), (158, 157), (157, 28),
|
||||
(35, 226), (226, 113), (113, 35), (160, 159), (159, 27), (27, 160),
|
||||
(204, 202), (202, 210), (210, 204), (113, 225), (225, 46), (46, 113),
|
||||
(43, 202), (202, 204), (204, 43), (62, 76), (76, 77), (77, 62),
|
||||
(137, 123), (123, 116), (116, 137), (41, 38), (38, 72), (72, 41),
|
||||
(203, 129), (129, 142), (142, 203), (64, 98), (98, 240), (240, 64),
|
||||
(49, 102), (102, 64), (64, 49), (41, 73), (73, 74), (74, 41),
|
||||
(212, 216), (216, 207), (207, 212), (42, 74), (74, 184), (184, 42),
|
||||
(169, 170), (170, 211), (211, 169), (170, 149), (149, 176), (176, 170),
|
||||
(105, 66), (66, 69), (69, 105), (122, 6), (6, 168), (168, 122),
|
||||
(123, 147), (147, 187), (187, 123), (96, 77), (77, 90), (90, 96),
|
||||
(65, 55), (55, 107), (107, 65), (89, 90), (90, 180), (180, 89),
|
||||
(101, 100), (100, 120), (120, 101), (63, 105), (105, 104), (104, 63),
|
||||
(93, 137), (137, 227), (227, 93), (15, 86), (86, 85), (85, 15),
|
||||
(129, 102), (102, 49), (49, 129), (14, 87), (87, 86), (86, 14),
|
||||
(55, 8), (8, 9), (9, 55), (100, 47), (47, 121), (121, 100),
|
||||
(145, 23), (23, 22), (22, 145), (88, 89), (89, 179), (179, 88),
|
||||
(6, 122), (122, 196), (196, 6), (88, 95), (95, 96), (96, 88),
|
||||
(138, 172), (172, 136), (136, 138), (215, 58), (58, 172), (172, 215),
|
||||
(115, 48), (48, 219), (219, 115), (42, 80), (80, 81), (81, 42),
|
||||
(195, 3), (3, 51), (51, 195), (43, 146), (146, 61), (61, 43),
|
||||
(171, 175), (175, 199), (199, 171), (81, 82), (82, 38), (38, 81),
|
||||
(53, 46), (46, 225), (225, 53), (144, 163), (163, 110), (110, 144),
|
||||
(52, 65), (65, 66), (66, 52), (229, 228), (228, 117), (117, 229),
|
||||
(34, 127), (127, 234), (234, 34), (107, 108), (108, 69), (69, 107),
|
||||
(109, 108), (108, 151), (151, 109), (48, 64), (64, 235), (235, 48),
|
||||
(62, 78), (78, 191), (191, 62), (129, 209), (209, 126), (126, 129),
|
||||
(111, 35), (35, 143), (143, 111), (117, 123), (123, 50), (50, 117),
|
||||
(222, 65), (65, 52), (52, 222), (19, 125), (125, 141), (141, 19),
|
||||
(221, 55), (55, 65), (65, 221), (3, 195), (195, 197), (197, 3),
|
||||
(25, 7), (7, 33), (33, 25), (220, 237), (237, 44), (44, 220),
|
||||
(70, 71), (71, 139), (139, 70), (122, 193), (193, 245), (245, 122),
|
||||
(247, 130), (130, 33), (33, 247), (71, 21), (21, 162), (162, 71),
|
||||
(170, 169), (169, 150), (150, 170), (188, 174), (174, 196), (196, 188),
|
||||
(216, 186), (186, 92), (92, 216), (2, 97), (97, 167), (167, 2),
|
||||
(141, 125), (125, 241), (241, 141), (164, 167), (167, 37), (37, 164),
|
||||
(72, 38), (38, 12), (12, 72), (38, 82), (82, 13), (13, 38),
|
||||
(63, 68), (68, 71), (71, 63), (226, 35), (35, 111), (111, 226),
|
||||
(101, 50), (50, 205), (205, 101), (206, 92), (92, 165), (165, 206),
|
||||
(209, 198), (198, 217), (217, 209), (165, 167), (167, 97), (97, 165),
|
||||
(220, 115), (115, 218), (218, 220), (133, 112), (112, 243), (243, 133),
|
||||
(239, 238), (238, 241), (241, 239), (214, 135), (135, 169), (169, 214),
|
||||
(190, 173), (173, 133), (133, 190), (171, 208), (208, 32), (32, 171),
|
||||
(125, 44), (44, 237), (237, 125), (86, 87), (87, 178), (178, 86),
|
||||
(85, 86), (86, 179), (179, 85), (84, 85), (85, 180), (180, 84),
|
||||
(83, 84), (84, 181), (181, 83), (201, 83), (83, 182), (182, 201),
|
||||
(137, 93), (93, 132), (132, 137), (76, 62), (62, 183), (183, 76),
|
||||
(61, 76), (76, 184), (184, 61), (57, 61), (61, 185), (185, 57),
|
||||
(212, 57), (57, 186), (186, 212), (214, 207), (207, 187), (187, 214),
|
||||
(34, 143), (143, 156), (156, 34), (79, 239), (239, 237), (237, 79),
|
||||
(123, 137), (137, 177), (177, 123), (44, 1), (1, 4), (4, 44),
|
||||
(201, 194), (194, 32), (32, 201), (64, 102), (102, 129), (129, 64),
|
||||
(213, 215), (215, 138), (138, 213), (59, 166), (166, 219), (219, 59),
|
||||
(242, 99), (99, 97), (97, 242), (2, 94), (94, 141), (141, 2),
|
||||
(75, 59), (59, 235), (235, 75), (24, 110), (110, 228), (228, 24),
|
||||
(25, 130), (130, 226), (226, 25), (23, 24), (24, 229), (229, 23),
|
||||
(22, 23), (23, 230), (230, 22), (26, 22), (22, 231), (231, 26),
|
||||
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||||
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|
||||
(147, 123), (123, 177), (177, 147), (45, 44), (44, 4), (4, 45),
|
||||
(208, 201), (201, 32), (32, 208), (98, 64), (64, 129), (129, 98),
|
||||
(192, 213), (213, 138), (138, 192), (235, 59), (59, 219), (219, 235),
|
||||
(141, 242), (242, 97), (97, 141), (97, 2), (2, 141), (141, 97),
|
||||
(240, 75), (75, 235), (235, 240), (229, 24), (24, 228), (228, 229),
|
||||
(31, 25), (25, 226), (226, 31), (230, 23), (23, 229), (229, 230),
|
||||
(231, 22), (22, 230), (230, 231), (232, 26), (26, 231), (231, 232),
|
||||
(233, 112), (112, 232), (232, 233), (244, 189), (189, 243), (243, 244),
|
||||
(189, 221), (221, 190), (190, 189), (222, 28), (28, 221), (221, 222),
|
||||
(223, 27), (27, 222), (222, 223), (224, 29), (29, 223), (223, 224),
|
||||
(225, 30), (30, 224), (224, 225), (113, 247), (247, 225), (225, 113),
|
||||
(99, 60), (60, 240), (240, 99), (213, 147), (147, 215), (215, 213),
|
||||
(60, 20), (20, 166), (166, 60), (192, 187), (187, 213), (213, 192),
|
||||
(243, 112), (112, 244), (244, 243), (244, 233), (233, 245), (245, 244),
|
||||
(245, 128), (128, 188), (188, 245), (188, 114), (114, 174), (174, 188),
|
||||
(134, 131), (131, 220), (220, 134), (174, 217), (217, 236), (236, 174),
|
||||
(236, 198), (198, 134), (134, 236), (215, 177), (177, 58), (58, 215),
|
||||
(156, 143), (143, 124), (124, 156), (25, 110), (110, 7), (7, 25),
|
||||
(31, 228), (228, 25), (25, 31), (264, 356), (356, 368), (368, 264),
|
||||
(0, 11), (11, 267), (267, 0), (451, 452), (452, 349), (349, 451),
|
||||
(267, 302), (302, 269), (269, 267), (350, 357), (357, 277), (277, 350),
|
||||
(350, 452), (452, 357), (357, 350), (299, 333), (333, 297), (297, 299),
|
||||
(396, 175), (175, 377), (377, 396), (280, 347), (347, 330), (330, 280),
|
||||
(269, 303), (303, 270), (270, 269), (151, 9), (9, 337), (337, 151),
|
||||
(344, 278), (278, 360), (360, 344), (424, 418), (418, 431), (431, 424),
|
||||
(270, 304), (304, 409), (409, 270), (272, 310), (310, 407), (407, 272),
|
||||
(322, 270), (270, 410), (410, 322), (449, 450), (450, 347), (347, 449),
|
||||
(432, 422), (422, 434), (434, 432), (18, 313), (313, 17), (17, 18),
|
||||
(291, 306), (306, 375), (375, 291), (259, 387), (387, 260), (260, 259),
|
||||
(424, 335), (335, 418), (418, 424), (434, 364), (364, 416), (416, 434),
|
||||
(391, 423), (423, 327), (327, 391), (301, 251), (251, 298), (298, 301),
|
||||
(275, 281), (281, 4), (4, 275), (254, 373), (373, 253), (253, 254),
|
||||
(375, 307), (307, 321), (321, 375), (280, 425), (425, 411), (411, 280),
|
||||
(200, 421), (421, 18), (18, 200), (335, 321), (321, 406), (406, 335),
|
||||
(321, 320), (320, 405), (405, 321), (314, 315), (315, 17), (17, 314),
|
||||
(423, 426), (426, 266), (266, 423), (396, 377), (377, 369), (369, 396),
|
||||
(270, 322), (322, 269), (269, 270), (413, 417), (417, 464), (464, 413),
|
||||
(385, 386), (386, 258), (258, 385), (248, 456), (456, 419), (419, 248),
|
||||
(298, 284), (284, 333), (333, 298), (168, 417), (417, 8), (8, 168),
|
||||
(448, 346), (346, 261), (261, 448), (417, 413), (413, 285), (285, 417),
|
||||
(326, 327), (327, 328), (328, 326), (277, 355), (355, 329), (329, 277),
|
||||
(309, 392), (392, 438), (438, 309), (381, 382), (382, 256), (256, 381),
|
||||
(279, 429), (429, 360), (360, 279), (365, 364), (364, 379), (379, 365),
|
||||
(355, 277), (277, 437), (437, 355), (282, 443), (443, 283), (283, 282),
|
||||
(281, 275), (275, 363), (363, 281), (395, 431), (431, 369), (369, 395),
|
||||
(299, 297), (297, 337), (337, 299), (335, 273), (273, 321), (321, 335),
|
||||
(348, 450), (450, 349), (349, 348), (359, 446), (446, 467), (467, 359),
|
||||
(283, 293), (293, 282), (282, 283), (250, 458), (458, 462), (462, 250),
|
||||
(300, 276), (276, 383), (383, 300), (292, 308), (308, 325), (325, 292),
|
||||
(283, 276), (276, 293), (293, 283), (264, 372), (372, 447), (447, 264),
|
||||
(346, 352), (352, 340), (340, 346), (354, 274), (274, 19), (19, 354),
|
||||
(363, 456), (456, 281), (281, 363), (426, 436), (436, 425), (425, 426),
|
||||
(380, 381), (381, 252), (252, 380), (267, 269), (269, 393), (393, 267),
|
||||
(421, 200), (200, 428), (428, 421), (371, 266), (266, 329), (329, 371),
|
||||
(432, 287), (287, 422), (422, 432), (290, 250), (250, 328), (328, 290),
|
||||
(385, 258), (258, 384), (384, 385), (446, 265), (265, 342), (342, 446),
|
||||
(386, 387), (387, 257), (257, 386), (422, 424), (424, 430), (430, 422),
|
||||
(445, 342), (342, 276), (276, 445), (422, 273), (273, 424), (424, 422),
|
||||
(306, 292), (292, 307), (307, 306), (352, 366), (366, 345), (345, 352),
|
||||
(268, 271), (271, 302), (302, 268), (358, 423), (423, 371), (371, 358),
|
||||
(327, 294), (294, 460), (460, 327), (331, 279), (279, 294), (294, 331),
|
||||
(303, 271), (271, 304), (304, 303), (436, 432), (432, 427), (427, 436),
|
||||
(304, 272), (272, 408), (408, 304), (395, 394), (394, 431), (431, 395),
|
||||
(378, 395), (395, 400), (400, 378), (296, 334), (334, 299), (299, 296),
|
||||
(6, 351), (351, 168), (168, 6), (376, 352), (352, 411), (411, 376),
|
||||
(307, 325), (325, 320), (320, 307), (285, 295), (295, 336), (336, 285),
|
||||
(320, 319), (319, 404), (404, 320), (329, 330), (330, 349), (349, 329),
|
||||
(334, 293), (293, 333), (333, 334), (366, 323), (323, 447), (447, 366),
|
||||
(316, 15), (15, 315), (315, 316), (331, 358), (358, 279), (279, 331),
|
||||
(317, 14), (14, 316), (316, 317), (8, 285), (285, 9), (9, 8),
|
||||
(277, 329), (329, 350), (350, 277), (253, 374), (374, 252), (252, 253),
|
||||
(319, 318), (318, 403), (403, 319), (351, 6), (6, 419), (419, 351),
|
||||
(324, 318), (318, 325), (325, 324), (397, 367), (367, 365), (365, 397),
|
||||
(288, 435), (435, 397), (397, 288), (278, 344), (344, 439), (439, 278),
|
||||
(310, 272), (272, 311), (311, 310), (248, 195), (195, 281), (281, 248),
|
||||
(375, 273), (273, 291), (291, 375), (175, 396), (396, 199), (199, 175),
|
||||
(312, 311), (311, 268), (268, 312), (276, 283), (283, 445), (445, 276),
|
||||
(390, 373), (373, 339), (339, 390), (295, 282), (282, 296), (296, 295),
|
||||
(448, 449), (449, 346), (346, 448), (356, 264), (264, 454), (454, 356),
|
||||
(337, 336), (336, 299), (299, 337), (337, 338), (338, 151), (151, 337),
|
||||
(294, 278), (278, 455), (455, 294), (308, 292), (292, 415), (415, 308),
|
||||
(429, 358), (358, 355), (355, 429), (265, 340), (340, 372), (372, 265),
|
||||
(352, 346), (346, 280), (280, 352), (295, 442), (442, 282), (282, 295),
|
||||
(354, 19), (19, 370), (370, 354), (285, 441), (441, 295), (295, 285),
|
||||
(195, 248), (248, 197), (197, 195), (457, 440), (440, 274), (274, 457),
|
||||
(301, 300), (300, 368), (368, 301), (417, 351), (351, 465), (465, 417),
|
||||
(251, 301), (301, 389), (389, 251), (394, 395), (395, 379), (379, 394),
|
||||
(399, 412), (412, 419), (419, 399), (410, 436), (436, 322), (322, 410),
|
||||
(326, 2), (2, 393), (393, 326), (354, 370), (370, 461), (461, 354),
|
||||
(393, 164), (164, 267), (267, 393), (268, 302), (302, 12), (12, 268),
|
||||
(312, 268), (268, 13), (13, 312), (298, 293), (293, 301), (301, 298),
|
||||
(265, 446), (446, 340), (340, 265), (280, 330), (330, 425), (425, 280),
|
||||
(322, 426), (426, 391), (391, 322), (420, 429), (429, 437), (437, 420),
|
||||
(393, 391), (391, 326), (326, 393), (344, 440), (440, 438), (438, 344),
|
||||
(458, 459), (459, 461), (461, 458), (364, 434), (434, 394), (394, 364),
|
||||
(428, 396), (396, 262), (262, 428), (274, 354), (354, 457), (457, 274),
|
||||
(317, 316), (316, 402), (402, 317), (316, 315), (315, 403), (403, 316),
|
||||
(315, 314), (314, 404), (404, 315), (314, 313), (313, 405), (405, 314),
|
||||
(313, 421), (421, 406), (406, 313), (323, 366), (366, 361), (361, 323),
|
||||
(292, 306), (306, 407), (407, 292), (306, 291), (291, 408), (408, 306),
|
||||
(291, 287), (287, 409), (409, 291), (287, 432), (432, 410), (410, 287),
|
||||
(427, 434), (434, 411), (411, 427), (372, 264), (264, 383), (383, 372),
|
||||
(459, 309), (309, 457), (457, 459), (366, 352), (352, 401), (401, 366),
|
||||
(1, 274), (274, 4), (4, 1), (418, 421), (421, 262), (262, 418),
|
||||
(331, 294), (294, 358), (358, 331), (435, 433), (433, 367), (367, 435),
|
||||
(392, 289), (289, 439), (439, 392), (328, 462), (462, 326), (326, 328),
|
||||
(94, 2), (2, 370), (370, 94), (289, 305), (305, 455), (455, 289),
|
||||
(339, 254), (254, 448), (448, 339), (359, 255), (255, 446), (446, 359),
|
||||
(254, 253), (253, 449), (449, 254), (253, 252), (252, 450), (450, 253),
|
||||
(252, 256), (256, 451), (451, 252), (256, 341), (341, 452), (452, 256),
|
||||
(414, 413), (413, 463), (463, 414), (286, 441), (441, 414), (414, 286),
|
||||
(286, 258), (258, 441), (441, 286), (258, 257), (257, 442), (442, 258),
|
||||
(257, 259), (259, 443), (443, 257), (259, 260), (260, 444), (444, 259),
|
||||
(260, 467), (467, 445), (445, 260), (309, 459), (459, 250), (250, 309),
|
||||
(305, 289), (289, 290), (290, 305), (305, 290), (290, 460), (460, 305),
|
||||
(401, 376), (376, 435), (435, 401), (309, 250), (250, 392), (392, 309),
|
||||
(376, 411), (411, 433), (433, 376), (453, 341), (341, 464), (464, 453),
|
||||
(357, 453), (453, 465), (465, 357), (343, 357), (357, 412), (412, 343),
|
||||
(437, 343), (343, 399), (399, 437), (344, 360), (360, 440), (440, 344),
|
||||
(420, 437), (437, 456), (456, 420), (360, 420), (420, 363), (363, 360),
|
||||
(361, 401), (401, 288), (288, 361), (265, 372), (372, 353), (353, 265),
|
||||
(390, 339), (339, 249), (249, 390), (339, 448), (448, 255), (255, 339)])
|
||||
@@ -26,6 +26,7 @@ import numpy.testing as npt
|
||||
|
||||
# resources dependency
|
||||
# undeclared dependency
|
||||
from mediapipe.python.solutions import drawing_styles
|
||||
from mediapipe.python.solutions import drawing_utils as mp_drawing
|
||||
from mediapipe.python.solutions import face_mesh as mp_faces
|
||||
|
||||
@@ -70,12 +71,21 @@ EYE_INDICES_TO_LANDMARKS = {
|
||||
class FaceMeshTest(parameterized.TestCase):
|
||||
|
||||
def _annotate(self, frame: np.ndarray, results: NamedTuple, idx: int):
|
||||
drawing_spec = mp_drawing.DrawingSpec(thickness=1, circle_radius=1)
|
||||
for face_landmarks in results.multi_face_landmarks:
|
||||
mp_drawing.draw_landmarks(
|
||||
image=frame,
|
||||
landmark_list=face_landmarks,
|
||||
landmark_drawing_spec=drawing_spec)
|
||||
frame,
|
||||
face_landmarks,
|
||||
mp_faces.FACEMESH_TESSELATION,
|
||||
landmark_drawing_spec=None,
|
||||
connection_drawing_spec=drawing_styles
|
||||
.get_default_face_mesh_tesselation_style())
|
||||
mp_drawing.draw_landmarks(
|
||||
frame,
|
||||
face_landmarks,
|
||||
mp_faces.FACEMESH_CONTOURS,
|
||||
landmark_drawing_spec=None,
|
||||
connection_drawing_spec=drawing_styles
|
||||
.get_default_face_mesh_contours_style())
|
||||
path = os.path.join(tempfile.gettempdir(), self.id().split('.')[-1] +
|
||||
'_frame_{}.png'.format(idx))
|
||||
cv2.imwrite(path, frame)
|
||||
|
||||
@@ -37,6 +37,9 @@ from mediapipe.calculators.util import rect_transformation_calculator_pb2
|
||||
from mediapipe.calculators.util import thresholding_calculator_pb2
|
||||
# pylint: enable=unused-import
|
||||
from mediapipe.python.solution_base import SolutionBase
|
||||
# pylint: disable=unused-import
|
||||
from mediapipe.python.solutions.hands_connections import HAND_CONNECTIONS
|
||||
# pylint: enable=unused-import
|
||||
|
||||
|
||||
class HandLandmark(enum.IntEnum):
|
||||
@@ -65,29 +68,6 @@ class HandLandmark(enum.IntEnum):
|
||||
|
||||
|
||||
BINARYPB_FILE_PATH = 'mediapipe/modules/hand_landmark/hand_landmark_tracking_cpu.binarypb'
|
||||
HAND_CONNECTIONS = frozenset([
|
||||
(HandLandmark.WRIST, HandLandmark.THUMB_CMC),
|
||||
(HandLandmark.THUMB_CMC, HandLandmark.THUMB_MCP),
|
||||
(HandLandmark.THUMB_MCP, HandLandmark.THUMB_IP),
|
||||
(HandLandmark.THUMB_IP, HandLandmark.THUMB_TIP),
|
||||
(HandLandmark.WRIST, HandLandmark.INDEX_FINGER_MCP),
|
||||
(HandLandmark.INDEX_FINGER_MCP, HandLandmark.INDEX_FINGER_PIP),
|
||||
(HandLandmark.INDEX_FINGER_PIP, HandLandmark.INDEX_FINGER_DIP),
|
||||
(HandLandmark.INDEX_FINGER_DIP, HandLandmark.INDEX_FINGER_TIP),
|
||||
(HandLandmark.INDEX_FINGER_MCP, HandLandmark.MIDDLE_FINGER_MCP),
|
||||
(HandLandmark.MIDDLE_FINGER_MCP, HandLandmark.MIDDLE_FINGER_PIP),
|
||||
(HandLandmark.MIDDLE_FINGER_PIP, HandLandmark.MIDDLE_FINGER_DIP),
|
||||
(HandLandmark.MIDDLE_FINGER_DIP, HandLandmark.MIDDLE_FINGER_TIP),
|
||||
(HandLandmark.MIDDLE_FINGER_MCP, HandLandmark.RING_FINGER_MCP),
|
||||
(HandLandmark.RING_FINGER_MCP, HandLandmark.RING_FINGER_PIP),
|
||||
(HandLandmark.RING_FINGER_PIP, HandLandmark.RING_FINGER_DIP),
|
||||
(HandLandmark.RING_FINGER_DIP, HandLandmark.RING_FINGER_TIP),
|
||||
(HandLandmark.RING_FINGER_MCP, HandLandmark.PINKY_MCP),
|
||||
(HandLandmark.WRIST, HandLandmark.PINKY_MCP),
|
||||
(HandLandmark.PINKY_MCP, HandLandmark.PINKY_PIP),
|
||||
(HandLandmark.PINKY_PIP, HandLandmark.PINKY_DIP),
|
||||
(HandLandmark.PINKY_DIP, HandLandmark.PINKY_TIP)
|
||||
])
|
||||
|
||||
|
||||
class Hands(SolutionBase):
|
||||
|
||||
@@ -0,0 +1,32 @@
|
||||
# Copyright 2021 The MediaPipe Authors.
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
#
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
"""MediaPipe Hands connections."""
|
||||
|
||||
HAND_PALM_CONNECTIONS = ((0, 1), (0, 5), (9, 13), (13, 17), (5, 9), (0, 17))
|
||||
|
||||
HAND_THUMB_CONNECTIONS = ((1, 2), (2, 3), (3, 4))
|
||||
|
||||
HAND_INDEX_FINGER_CONNECTIONS = ((5, 6), (6, 7), (7, 8))
|
||||
|
||||
HAND_MIDDLE_FINGER_CONNECTIONS = ((9, 10), (10, 11), (11, 12))
|
||||
|
||||
HAND_RING_FINGER_CONNECTIONS = ((13, 14), (14, 15), (15, 16))
|
||||
|
||||
HAND_PINKY_FINGER_CONNECTIONS = ((17, 18), (18, 19), (19, 20))
|
||||
|
||||
HAND_CONNECTIONS = frozenset().union(*[
|
||||
HAND_PALM_CONNECTIONS, HAND_THUMB_CONNECTIONS,
|
||||
HAND_INDEX_FINGER_CONNECTIONS, HAND_MIDDLE_FINGER_CONNECTIONS,
|
||||
HAND_RING_FINGER_CONNECTIONS, HAND_PINKY_FINGER_CONNECTIONS
|
||||
])
|
||||
@@ -30,6 +30,7 @@ from mediapipe.python.solutions import drawing_styles
|
||||
from mediapipe.python.solutions import drawing_utils as mp_drawing
|
||||
from mediapipe.python.solutions import hands as mp_hands
|
||||
|
||||
|
||||
TEST_IMAGE_PATH = 'mediapipe/python/solutions/testdata'
|
||||
DIFF_THRESHOLD = 15 # pixels
|
||||
EXPECTED_HAND_COORDINATES_PREDICTION = [[[144, 345], [211, 323], [257, 286],
|
||||
@@ -54,8 +55,8 @@ class HandsTest(parameterized.TestCase):
|
||||
for hand_landmarks in results.multi_hand_landmarks:
|
||||
mp_drawing.draw_landmarks(
|
||||
frame, hand_landmarks, mp_hands.HAND_CONNECTIONS,
|
||||
drawing_styles.get_default_hand_landmark_style(),
|
||||
drawing_styles.get_default_hand_connection_style())
|
||||
drawing_styles.get_default_hand_landmarks_style(),
|
||||
drawing_styles.get_default_hand_connections_style())
|
||||
path = os.path.join(tempfile.gettempdir(), self.id().split('.')[-1] +
|
||||
'_frame_{}.png'.format(idx))
|
||||
cv2.imwrite(path, frame)
|
||||
|
||||
@@ -41,11 +41,12 @@ from mediapipe.modules.holistic_landmark.calculators import roi_tracking_calcula
|
||||
from mediapipe.python.solution_base import SolutionBase
|
||||
from mediapipe.python.solutions import download_utils
|
||||
# pylint: disable=unused-import
|
||||
from mediapipe.python.solutions.face_mesh import FACE_CONNECTIONS
|
||||
from mediapipe.python.solutions.hands import HAND_CONNECTIONS
|
||||
from mediapipe.python.solutions.face_mesh_connections import FACEMESH_CONTOURS
|
||||
from mediapipe.python.solutions.face_mesh_connections import FACEMESH_TESSELATION
|
||||
from mediapipe.python.solutions.hands import HandLandmark
|
||||
from mediapipe.python.solutions.pose import POSE_CONNECTIONS
|
||||
from mediapipe.python.solutions.hands_connections import HAND_CONNECTIONS
|
||||
from mediapipe.python.solutions.pose import PoseLandmark
|
||||
from mediapipe.python.solutions.pose_connections import POSE_CONNECTIONS
|
||||
# pylint: enable=unused-import
|
||||
|
||||
BINARYPB_FILE_PATH = 'mediapipe/modules/holistic_landmark/holistic_landmark_cpu.binarypb'
|
||||
@@ -103,6 +104,7 @@ class Holistic(SolutionBase):
|
||||
side_inputs={
|
||||
'model_complexity': model_complexity,
|
||||
'smooth_landmarks': smooth_landmarks and not static_image_mode,
|
||||
'smooth_segmentation': not static_image_mode,
|
||||
},
|
||||
calculator_params={
|
||||
'poselandmarkcpu__ConstantSidePacketCalculator.packet': [
|
||||
@@ -112,7 +114,7 @@ class Holistic(SolutionBase):
|
||||
],
|
||||
'poselandmarkcpu__posedetectioncpu__TensorsToDetectionsCalculator.min_score_thresh':
|
||||
min_detection_confidence,
|
||||
'poselandmarkcpu__poselandmarkbyroicpu__ThresholdingCalculator.threshold':
|
||||
'poselandmarkcpu__poselandmarkbyroicpu__tensorstoposelandmarksandsegmentation__ThresholdingCalculator.threshold':
|
||||
min_tracking_confidence,
|
||||
},
|
||||
outputs=[
|
||||
|
||||
@@ -25,6 +25,7 @@ import numpy.testing as npt
|
||||
|
||||
# resources dependency
|
||||
# undeclared dependency
|
||||
from mediapipe.python.solutions import drawing_styles
|
||||
from mediapipe.python.solutions import drawing_utils as mp_drawing
|
||||
from mediapipe.python.solutions import holistic as mp_holistic
|
||||
|
||||
@@ -69,17 +70,18 @@ class PoseTest(parameterized.TestCase):
|
||||
npt.assert_array_less(np.abs(array1 - array2), threshold)
|
||||
|
||||
def _annotate(self, frame: np.ndarray, results: NamedTuple, idx: int):
|
||||
drawing_spec = mp_drawing.DrawingSpec(thickness=1, circle_radius=1)
|
||||
mp_drawing.draw_landmarks(
|
||||
image=frame,
|
||||
landmark_list=results.face_landmarks,
|
||||
landmark_drawing_spec=drawing_spec)
|
||||
mp_drawing.draw_landmarks(frame, results.left_hand_landmarks,
|
||||
mp_holistic.HAND_CONNECTIONS)
|
||||
mp_drawing.draw_landmarks(frame, results.right_hand_landmarks,
|
||||
mp_holistic.HAND_CONNECTIONS)
|
||||
mp_drawing.draw_landmarks(frame, results.pose_landmarks,
|
||||
mp_holistic.POSE_CONNECTIONS)
|
||||
frame,
|
||||
results.face_landmarks,
|
||||
mp_holistic.FACEMESH_TESSELATION,
|
||||
landmark_drawing_spec=None,
|
||||
connection_drawing_spec=drawing_styles
|
||||
.get_default_face_mesh_tesselation_style())
|
||||
mp_drawing.draw_landmarks(
|
||||
frame,
|
||||
results.pose_landmarks,
|
||||
mp_holistic.POSE_CONNECTIONS,
|
||||
landmark_drawing_spec=drawing_styles.get_default_pose_landmarks_style())
|
||||
path = os.path.join(tempfile.gettempdir(), self.id().split('.')[-1] +
|
||||
'_frame_{}.png'.format(idx))
|
||||
cv2.imwrite(path, frame)
|
||||
|
||||
@@ -25,11 +25,13 @@ from mediapipe.calculators.core import constant_side_packet_calculator_pb2
|
||||
# pylint: disable=unused-import
|
||||
from mediapipe.calculators.core import gate_calculator_pb2
|
||||
from mediapipe.calculators.core import split_vector_calculator_pb2
|
||||
from mediapipe.calculators.image import warp_affine_calculator_pb2
|
||||
from mediapipe.calculators.tensor import image_to_tensor_calculator_pb2
|
||||
from mediapipe.calculators.tensor import inference_calculator_pb2
|
||||
from mediapipe.calculators.tensor import tensors_to_classification_calculator_pb2
|
||||
from mediapipe.calculators.tensor import tensors_to_detections_calculator_pb2
|
||||
from mediapipe.calculators.tensor import tensors_to_landmarks_calculator_pb2
|
||||
from mediapipe.calculators.tensor import tensors_to_segmentation_calculator_pb2
|
||||
from mediapipe.calculators.tflite import ssd_anchors_calculator_pb2
|
||||
from mediapipe.calculators.util import detections_to_rects_calculator_pb2
|
||||
from mediapipe.calculators.util import landmarks_smoothing_calculator_pb2
|
||||
@@ -41,9 +43,11 @@ from mediapipe.calculators.util import thresholding_calculator_pb2
|
||||
from mediapipe.calculators.util import visibility_smoothing_calculator_pb2
|
||||
from mediapipe.framework.tool import switch_container_pb2
|
||||
# pylint: enable=unused-import
|
||||
|
||||
from mediapipe.python.solution_base import SolutionBase
|
||||
from mediapipe.python.solutions import download_utils
|
||||
# pylint: disable=unused-import
|
||||
from mediapipe.python.solutions.pose_connections import POSE_CONNECTIONS
|
||||
# pylint: enable=unused-import
|
||||
|
||||
|
||||
class PoseLandmark(enum.IntEnum):
|
||||
@@ -82,44 +86,8 @@ class PoseLandmark(enum.IntEnum):
|
||||
LEFT_FOOT_INDEX = 31
|
||||
RIGHT_FOOT_INDEX = 32
|
||||
|
||||
|
||||
BINARYPB_FILE_PATH = 'mediapipe/modules/pose_landmark/pose_landmark_cpu.binarypb'
|
||||
POSE_CONNECTIONS = frozenset([
|
||||
(PoseLandmark.NOSE, PoseLandmark.RIGHT_EYE_INNER),
|
||||
(PoseLandmark.RIGHT_EYE_INNER, PoseLandmark.RIGHT_EYE),
|
||||
(PoseLandmark.RIGHT_EYE, PoseLandmark.RIGHT_EYE_OUTER),
|
||||
(PoseLandmark.RIGHT_EYE_OUTER, PoseLandmark.RIGHT_EAR),
|
||||
(PoseLandmark.NOSE, PoseLandmark.LEFT_EYE_INNER),
|
||||
(PoseLandmark.LEFT_EYE_INNER, PoseLandmark.LEFT_EYE),
|
||||
(PoseLandmark.LEFT_EYE, PoseLandmark.LEFT_EYE_OUTER),
|
||||
(PoseLandmark.LEFT_EYE_OUTER, PoseLandmark.LEFT_EAR),
|
||||
(PoseLandmark.MOUTH_RIGHT, PoseLandmark.MOUTH_LEFT),
|
||||
(PoseLandmark.RIGHT_SHOULDER, PoseLandmark.LEFT_SHOULDER),
|
||||
(PoseLandmark.RIGHT_SHOULDER, PoseLandmark.RIGHT_ELBOW),
|
||||
(PoseLandmark.RIGHT_ELBOW, PoseLandmark.RIGHT_WRIST),
|
||||
(PoseLandmark.RIGHT_WRIST, PoseLandmark.RIGHT_PINKY),
|
||||
(PoseLandmark.RIGHT_WRIST, PoseLandmark.RIGHT_INDEX),
|
||||
(PoseLandmark.RIGHT_WRIST, PoseLandmark.RIGHT_THUMB),
|
||||
(PoseLandmark.RIGHT_PINKY, PoseLandmark.RIGHT_INDEX),
|
||||
(PoseLandmark.LEFT_SHOULDER, PoseLandmark.LEFT_ELBOW),
|
||||
(PoseLandmark.LEFT_ELBOW, PoseLandmark.LEFT_WRIST),
|
||||
(PoseLandmark.LEFT_WRIST, PoseLandmark.LEFT_PINKY),
|
||||
(PoseLandmark.LEFT_WRIST, PoseLandmark.LEFT_INDEX),
|
||||
(PoseLandmark.LEFT_WRIST, PoseLandmark.LEFT_THUMB),
|
||||
(PoseLandmark.LEFT_PINKY, PoseLandmark.LEFT_INDEX),
|
||||
(PoseLandmark.RIGHT_SHOULDER, PoseLandmark.RIGHT_HIP),
|
||||
(PoseLandmark.LEFT_SHOULDER, PoseLandmark.LEFT_HIP),
|
||||
(PoseLandmark.RIGHT_HIP, PoseLandmark.LEFT_HIP),
|
||||
(PoseLandmark.RIGHT_HIP, PoseLandmark.RIGHT_KNEE),
|
||||
(PoseLandmark.LEFT_HIP, PoseLandmark.LEFT_KNEE),
|
||||
(PoseLandmark.RIGHT_KNEE, PoseLandmark.RIGHT_ANKLE),
|
||||
(PoseLandmark.LEFT_KNEE, PoseLandmark.LEFT_ANKLE),
|
||||
(PoseLandmark.RIGHT_ANKLE, PoseLandmark.RIGHT_HEEL),
|
||||
(PoseLandmark.LEFT_ANKLE, PoseLandmark.LEFT_HEEL),
|
||||
(PoseLandmark.RIGHT_HEEL, PoseLandmark.RIGHT_FOOT_INDEX),
|
||||
(PoseLandmark.LEFT_HEEL, PoseLandmark.LEFT_FOOT_INDEX),
|
||||
(PoseLandmark.RIGHT_ANKLE, PoseLandmark.RIGHT_FOOT_INDEX),
|
||||
(PoseLandmark.LEFT_ANKLE, PoseLandmark.LEFT_FOOT_INDEX),
|
||||
])
|
||||
|
||||
|
||||
def _download_oss_pose_landmark_model(model_complexity):
|
||||
@@ -147,6 +115,8 @@ class Pose(SolutionBase):
|
||||
static_image_mode=False,
|
||||
model_complexity=1,
|
||||
smooth_landmarks=True,
|
||||
enable_segmentation=False,
|
||||
smooth_segmentation=True,
|
||||
min_detection_confidence=0.5,
|
||||
min_tracking_confidence=0.5):
|
||||
"""Initializes a MediaPipe Pose object.
|
||||
@@ -160,6 +130,11 @@ class Pose(SolutionBase):
|
||||
smooth_landmarks: Whether to filter landmarks across different input
|
||||
images to reduce jitter. See details in
|
||||
https://solutions.mediapipe.dev/pose#smooth_landmarks.
|
||||
enable_segmentation: Whether to predict segmentation mask. See details in
|
||||
https://solutions.mediapipe.dev/pose#enable_segmentation.
|
||||
smooth_segmentation: Whether to filter segmentation across different input
|
||||
images to reduce jitter. See details in
|
||||
https://solutions.mediapipe.dev/pose#smooth_segmentation.
|
||||
min_detection_confidence: Minimum confidence value ([0.0, 1.0]) for person
|
||||
detection to be considered successful. See details in
|
||||
https://solutions.mediapipe.dev/pose#min_detection_confidence.
|
||||
@@ -173,6 +148,9 @@ class Pose(SolutionBase):
|
||||
side_inputs={
|
||||
'model_complexity': model_complexity,
|
||||
'smooth_landmarks': smooth_landmarks and not static_image_mode,
|
||||
'enable_segmentation': enable_segmentation,
|
||||
'smooth_segmentation':
|
||||
smooth_segmentation and not static_image_mode,
|
||||
},
|
||||
calculator_params={
|
||||
'ConstantSidePacketCalculator.packet': [
|
||||
@@ -180,12 +158,12 @@ class Pose(SolutionBase):
|
||||
.ConstantSidePacketCalculatorOptions.ConstantSidePacket(
|
||||
bool_value=not static_image_mode)
|
||||
],
|
||||
'poselandmarkcpu__posedetectioncpu__TensorsToDetectionsCalculator.min_score_thresh':
|
||||
'posedetectioncpu__TensorsToDetectionsCalculator.min_score_thresh':
|
||||
min_detection_confidence,
|
||||
'poselandmarkcpu__poselandmarkbyroicpu__ThresholdingCalculator.threshold':
|
||||
'poselandmarkbyroicpu__tensorstoposelandmarksandsegmentation__ThresholdingCalculator.threshold':
|
||||
min_tracking_confidence,
|
||||
},
|
||||
outputs=['pose_landmarks', 'pose_world_landmarks'])
|
||||
outputs=['pose_landmarks', 'pose_world_landmarks', 'segmentation_mask'])
|
||||
|
||||
def process(self, image: np.ndarray) -> NamedTuple:
|
||||
"""Processes an RGB image and returns the pose landmarks on the most prominent person detected.
|
||||
|
||||
@@ -0,0 +1,22 @@
|
||||
# Copyright 2021 The MediaPipe Authors.
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
#
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
"""MediaPipe Pose connections."""
|
||||
|
||||
POSE_CONNECTIONS = frozenset([(0, 1), (1, 2), (2, 3), (3, 7), (0, 4), (4, 5),
|
||||
(5, 6), (6, 8), (9, 10), (11, 12), (11, 13),
|
||||
(13, 15), (15, 17), (15, 19), (15, 21), (17, 19),
|
||||
(12, 14), (14, 16), (16, 18), (16, 20), (16, 22),
|
||||
(18, 20), (11, 23), (12, 24), (23, 24), (23, 25),
|
||||
(24, 26), (25, 27), (26, 28), (27, 29), (28, 30),
|
||||
(29, 31), (30, 32), (27, 31), (28, 32)])
|
||||
@@ -15,7 +15,9 @@
|
||||
|
||||
import json
|
||||
import os
|
||||
# pylint: disable=unused-import
|
||||
import tempfile
|
||||
# pylint: enable=unused-import
|
||||
from typing import NamedTuple
|
||||
|
||||
from absl.testing import absltest
|
||||
@@ -23,9 +25,11 @@ from absl.testing import parameterized
|
||||
import cv2
|
||||
import numpy as np
|
||||
import numpy.testing as npt
|
||||
from PIL import Image
|
||||
|
||||
# resources dependency
|
||||
# undeclared dependency
|
||||
from mediapipe.python.solutions import drawing_styles
|
||||
from mediapipe.python.solutions import drawing_utils as mp_drawing
|
||||
from mediapipe.python.solutions import pose as mp_pose
|
||||
|
||||
@@ -56,6 +60,7 @@ EXPECTED_POSE_WORLD_LANDMARKS = np.array([
|
||||
[0.69, 0.49, -0.04], [-0.48, 0.47, -0.02], [0.72, 0.52, -0.04],
|
||||
[-0.48, 0.51, -0.02], [0.8, 0.5, -0.14], [-0.59, 0.52, -0.11],
|
||||
])
|
||||
IOU_THRESHOLD = 0.85 # percents
|
||||
|
||||
|
||||
class PoseTest(parameterized.TestCase):
|
||||
@@ -72,13 +77,64 @@ class PoseTest(parameterized.TestCase):
|
||||
def _assert_diff_less(self, array1, array2, threshold):
|
||||
npt.assert_array_less(np.abs(array1 - array2), threshold)
|
||||
|
||||
def _get_output_path(self, name):
|
||||
return os.path.join(tempfile.gettempdir(), self.id().split('.')[-1] + name)
|
||||
|
||||
def _annotate(self, frame: np.ndarray, results: NamedTuple, idx: int):
|
||||
mp_drawing.draw_landmarks(frame, results.pose_landmarks,
|
||||
mp_pose.POSE_CONNECTIONS)
|
||||
path = os.path.join(tempfile.gettempdir(), self.id().split('.')[-1] +
|
||||
'_frame_{}.png'.format(idx))
|
||||
mp_drawing.draw_landmarks(
|
||||
frame,
|
||||
results.pose_landmarks,
|
||||
mp_pose.POSE_CONNECTIONS,
|
||||
landmark_drawing_spec=drawing_styles.get_default_pose_landmarks_style())
|
||||
path = self._get_output_path('_frame_{}.png'.format(idx))
|
||||
cv2.imwrite(path, frame)
|
||||
|
||||
def _annotate_segmentation(self, segmentation, expected_segmentation,
|
||||
idx: int):
|
||||
path = self._get_output_path('_segmentation_{}.png'.format(idx))
|
||||
self._segmentation_to_rgb(segmentation).save(path)
|
||||
path = self._get_output_path('_segmentation_diff_{}.png'.format(idx))
|
||||
self._segmentation_diff_to_rgb(
|
||||
expected_segmentation, segmentation).save(path)
|
||||
|
||||
def _rgb_to_segmentation(self, img, back_color=(255, 0, 0),
|
||||
front_color=(0, 0, 255)):
|
||||
img = np.array(img)
|
||||
# Check all pixels are either front or back.
|
||||
is_back = (img == back_color).all(axis=2)
|
||||
is_front = (img == front_color).all(axis=2)
|
||||
np.logical_or(is_back, is_front).all()
|
||||
segm = np.zeros(img.shape[:2], dtype=np.uint8)
|
||||
segm[is_front] = 1
|
||||
return segm
|
||||
|
||||
def _segmentation_to_rgb(self, segm, back_color=(255, 0, 0),
|
||||
front_color=(0, 0, 255)):
|
||||
height, width = segm.shape
|
||||
img = np.zeros((height, width, 3), dtype=np.uint8)
|
||||
img[:, :] = back_color
|
||||
img[segm == 1] = front_color
|
||||
return Image.fromarray(img)
|
||||
|
||||
def _segmentation_iou(self, segm_expected, segm_actual):
|
||||
intersection = segm_expected * segm_actual
|
||||
expected_dot = segm_expected * segm_expected
|
||||
actual_dot = segm_actual * segm_actual
|
||||
eps = np.finfo(np.float32).eps
|
||||
result = intersection.sum() / (expected_dot.sum() +
|
||||
actual_dot.sum() -
|
||||
intersection.sum() + eps)
|
||||
return result
|
||||
|
||||
def _segmentation_diff_to_rgb(self, segm_expected, segm_actual,
|
||||
expected_color=(0, 255, 0),
|
||||
actual_color=(255, 0, 0)):
|
||||
height, width = segm_expected.shape
|
||||
img = np.zeros((height, width, 3), dtype=np.uint8)
|
||||
img[np.logical_and(segm_expected == 1, segm_actual == 0)] = expected_color
|
||||
img[np.logical_and(segm_expected == 0, segm_actual == 1)] = actual_color
|
||||
return Image.fromarray(img)
|
||||
|
||||
def test_invalid_image_shape(self):
|
||||
with mp_pose.Pose() as pose:
|
||||
with self.assertRaisesRegex(
|
||||
@@ -86,11 +142,12 @@ class PoseTest(parameterized.TestCase):
|
||||
pose.process(np.arange(36, dtype=np.uint8).reshape(3, 3, 4))
|
||||
|
||||
def test_blank_image(self):
|
||||
with mp_pose.Pose() as pose:
|
||||
with mp_pose.Pose(enable_segmentation=True) as pose:
|
||||
image = np.zeros([100, 100, 3], dtype=np.uint8)
|
||||
image.fill(255)
|
||||
results = pose.process(image)
|
||||
self.assertIsNone(results.pose_landmarks)
|
||||
self.assertIsNone(results.segmentation_mask)
|
||||
|
||||
@parameterized.named_parameters(('static_lite', True, 0, 3),
|
||||
('static_full', True, 1, 3),
|
||||
@@ -100,13 +157,23 @@ class PoseTest(parameterized.TestCase):
|
||||
('video_heavy', False, 2, 3))
|
||||
def test_on_image(self, static_image_mode, model_complexity, num_frames):
|
||||
image_path = os.path.join(os.path.dirname(__file__), 'testdata/pose.jpg')
|
||||
expected_segmentation_path = os.path.join(
|
||||
os.path.dirname(__file__), 'testdata/pose_segmentation.png')
|
||||
image = cv2.imread(image_path)
|
||||
expected_segmentation = self._rgb_to_segmentation(
|
||||
Image.open(expected_segmentation_path).convert('RGB'))
|
||||
|
||||
with mp_pose.Pose(static_image_mode=static_image_mode,
|
||||
model_complexity=model_complexity) as pose:
|
||||
model_complexity=model_complexity,
|
||||
enable_segmentation=True) as pose:
|
||||
for idx in range(num_frames):
|
||||
results = pose.process(cv2.cvtColor(image, cv2.COLOR_BGR2RGB))
|
||||
segmentation = results.segmentation_mask.round().astype(np.uint8)
|
||||
|
||||
# TODO: Add rendering of world 3D when supported.
|
||||
self._annotate(image.copy(), results, idx)
|
||||
self._annotate_segmentation(segmentation, expected_segmentation, idx)
|
||||
|
||||
self._assert_diff_less(
|
||||
self._landmarks_list_to_array(results.pose_landmarks,
|
||||
image.shape)[:, :2],
|
||||
@@ -114,13 +181,14 @@ class PoseTest(parameterized.TestCase):
|
||||
self._assert_diff_less(
|
||||
self._world_landmarks_list_to_array(results.pose_world_landmarks),
|
||||
EXPECTED_POSE_WORLD_LANDMARKS, WORLD_DIFF_THRESHOLD)
|
||||
self.assertGreaterEqual(
|
||||
self._segmentation_iou(expected_segmentation, segmentation),
|
||||
IOU_THRESHOLD)
|
||||
|
||||
@parameterized.named_parameters(
|
||||
('full', 1, 'pose_squats.full.npz'))
|
||||
def test_on_video(self, model_complexity, expected_name):
|
||||
"""Tests pose models on a video."""
|
||||
# If set to `True` will dump actual predictions to .npz and JSON files.
|
||||
dump_predictions = False
|
||||
# Set threshold for comparing actual and expected predictions in pixels.
|
||||
diff_threshold = 15
|
||||
world_diff_threshold = 0.1
|
||||
@@ -160,21 +228,18 @@ class PoseTest(parameterized.TestCase):
|
||||
actual = np.array(actual_per_frame)
|
||||
actual_world = np.array(actual_world_per_frame)
|
||||
|
||||
if dump_predictions:
|
||||
# Dump .npz
|
||||
with tempfile.NamedTemporaryFile(delete=False) as tmp_file:
|
||||
np.savez(tmp_file, predictions=actual, predictions_world=actual_world)
|
||||
print('Predictions saved as .npz to {}'.format(tmp_file.name))
|
||||
# Dump actual .npz.
|
||||
npz_path = self._get_output_path(expected_name)
|
||||
np.savez(npz_path, predictions=actual, predictions_world=actual_world)
|
||||
|
||||
# Dump JSON
|
||||
with tempfile.NamedTemporaryFile(delete=False) as tmp_file:
|
||||
with open(tmp_file.name, 'w') as fl:
|
||||
dump_data = {
|
||||
'predictions': np.around(actual, 3).tolist(),
|
||||
'predictions_world': np.around(actual_world, 3).tolist()
|
||||
}
|
||||
fl.write(json.dumps(dump_data, indent=2, separators=(',', ': ')))
|
||||
print('Predictions saved as JSON to {}'.format(tmp_file.name))
|
||||
# Dump actual JSON.
|
||||
json_path = self._get_output_path(expected_name.replace('.npz', '.json'))
|
||||
with open(json_path, 'w') as fl:
|
||||
dump_data = {
|
||||
'predictions': np.around(actual, 3).tolist(),
|
||||
'predictions_world': np.around(actual_world, 3).tolist()
|
||||
}
|
||||
fl.write(json.dumps(dump_data, indent=2, separators=(',', ': ')))
|
||||
|
||||
# Validate actual vs. expected landmarks.
|
||||
expected = np.load(expected_path)['predictions']
|
||||
|
||||
Reference in New Issue
Block a user