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Renamed HandLandmarksDetectionResult to HandLandmarkerResult

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This commit is contained in:
kinaryml 2022-11-08 23:06:28 -08:00
parent 96e2eb38c7
commit 46f135e54d
2 changed files with 36 additions and 36 deletions
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40
mediapipe/tasks/python/test/vision/hand_landmarker_test.py
View File

@ -41,7 +41,7 @@ _LandmarksDetectionResult = landmark_detection_result_module.LandmarksDetectionR
_Image = image_module.Image
_HandLandmarker = hand_landmarker.HandLandmarker
_HandLandmarkerOptions = hand_landmarker.HandLandmarkerOptions
_HandLandmarksDetectionResult = hand_landmarker.HandLandmarksDetectionResult
_HandLandmarkerResult = hand_landmarker.HandLandmarkerResult
_RUNNING_MODE = running_mode_module.VisionTaskRunningMode
_ImageProcessingOptions = image_processing_options_module.ImageProcessingOptions
@ -58,8 +58,8 @@ _LANDMARKS_ERROR_TOLERANCE = 0.03
_HANDEDNESS_MARGIN = 0.05
def _get_expected_hand_landmarks_detection_result(
file_path: str) -> _HandLandmarksDetectionResult:
def _get_expected_hand_landmarker_result(
file_path: str) -> _HandLandmarkerResult:
landmarks_detection_result_file_path = test_utils.get_test_data_path(
file_path)
with open(landmarks_detection_result_file_path, "rb") as f:
@ -69,7 +69,7 @@ def _get_expected_hand_landmarks_detection_result(
text_format.Parse(f.read(), landmarks_detection_result_proto)
landmarks_detection_result = _LandmarksDetectionResult.create_from_pb2(
landmarks_detection_result_proto)
return _HandLandmarksDetectionResult(
return _HandLandmarkerResult(
handedness=[landmarks_detection_result.categories],
hand_landmarks=[landmarks_detection_result.landmarks],
hand_world_landmarks=[landmarks_detection_result.world_landmarks])
@ -91,8 +91,8 @@ class HandLandmarkerTest(parameterized.TestCase):
def _assert_actual_result_approximately_matches_expected_result(
self,
actual_result: _HandLandmarksDetectionResult,
expected_result: _HandLandmarksDetectionResult
actual_result: _HandLandmarkerResult,
expected_result: _HandLandmarkerResult
):
# Expects to have the same number of hands detected.
self.assertLen(actual_result.hand_landmarks,
@ -150,10 +150,10 @@ class HandLandmarkerTest(parameterized.TestCase):
self.assertIsInstance(landmarker, _HandLandmarker)
@parameterized.parameters(
(ModelFileType.FILE_NAME, _get_expected_hand_landmarks_detection_result(
(ModelFileType.FILE_NAME, _get_expected_hand_landmarker_result(
_THUMB_UP_LANDMARKS
)),
(ModelFileType.FILE_CONTENT, _get_expected_hand_landmarks_detection_result(
(ModelFileType.FILE_CONTENT, _get_expected_hand_landmarker_result(
_THUMB_UP_LANDMARKS
)))
def test_detect(self, model_file_type, expected_detection_result):
@ -181,10 +181,10 @@ class HandLandmarkerTest(parameterized.TestCase):
landmarker.close()
@parameterized.parameters(
(ModelFileType.FILE_NAME, _get_expected_hand_landmarks_detection_result(
(ModelFileType.FILE_NAME, _get_expected_hand_landmarker_result(
_THUMB_UP_LANDMARKS
)),
(ModelFileType.FILE_CONTENT, _get_expected_hand_landmarks_detection_result(
(ModelFileType.FILE_CONTENT, _get_expected_hand_landmarker_result(
_THUMB_UP_LANDMARKS
)))
def test_detect_in_context(self, model_file_type, expected_detection_result):
@ -233,7 +233,7 @@ class HandLandmarkerTest(parameterized.TestCase):
# Performs hand landmarks detection on the input.
detection_result = landmarker.detect(test_image,
image_processing_options)
expected_detection_result = _get_expected_hand_landmarks_detection_result(
expected_detection_result = _get_expected_hand_landmarker_result(
_POINTING_UP_ROTATED_LANDMARKS)
# Comparing results.
self._assert_actual_result_approximately_matches_expected_result(
@ -332,14 +332,14 @@ class HandLandmarkerTest(parameterized.TestCase):
landmarker.detect_for_video(self.test_image, 0)
@parameterized.parameters(
(_THUMB_UP_IMAGE, 0, _get_expected_hand_landmarks_detection_result(
(_THUMB_UP_IMAGE, 0, _get_expected_hand_landmarker_result(
_THUMB_UP_LANDMARKS)),
(_POINTING_UP_IMAGE, 0, _get_expected_hand_landmarks_detection_result(
(_POINTING_UP_IMAGE, 0, _get_expected_hand_landmarker_result(
_POINTING_UP_LANDMARKS)),
(_POINTING_UP_ROTATED_IMAGE, -90,
_get_expected_hand_landmarks_detection_result(
_get_expected_hand_landmarker_result(
_POINTING_UP_ROTATED_LANDMARKS)),
(_NO_HANDS_IMAGE, 0, _HandLandmarksDetectionResult([], [], [])))
(_NO_HANDS_IMAGE, 0, _HandLandmarkerResult([], [], [])))
def test_detect_for_video(self, image_path, rotation, expected_result):
test_image = _Image.create_from_file(
test_utils.get_test_data_path(image_path))
@ -392,14 +392,14 @@ class HandLandmarkerTest(parameterized.TestCase):
landmarker.detect_async(self.test_image, 0)
@parameterized.parameters(
(_THUMB_UP_IMAGE, 0, _get_expected_hand_landmarks_detection_result(
(_THUMB_UP_IMAGE, 0, _get_expected_hand_landmarker_result(
_THUMB_UP_LANDMARKS)),
(_POINTING_UP_IMAGE, 0, _get_expected_hand_landmarks_detection_result(
(_POINTING_UP_IMAGE, 0, _get_expected_hand_landmarker_result(
_POINTING_UP_LANDMARKS)),
(_POINTING_UP_ROTATED_IMAGE, -90,
_get_expected_hand_landmarks_detection_result(
_get_expected_hand_landmarker_result(
_POINTING_UP_ROTATED_LANDMARKS)),
(_NO_HANDS_IMAGE, 0, _HandLandmarksDetectionResult([], [], [])))
(_NO_HANDS_IMAGE, 0, _HandLandmarkerResult([], [], [])))
def test_detect_async_calls(self, image_path, rotation, expected_result):
test_image = _Image.create_from_file(
test_utils.get_test_data_path(image_path))
@ -407,7 +407,7 @@ class HandLandmarkerTest(parameterized.TestCase):
image_processing_options = _ImageProcessingOptions(rotation_degrees=rotation)
observed_timestamp_ms = -1
def check_result(result: _HandLandmarksDetectionResult,
def check_result(result: _HandLandmarkerResult,
output_image: _Image,
timestamp_ms: int):
if result.hand_landmarks and result.hand_world_landmarks and \

32
mediapipe/tasks/python/vision/hand_landmarker.py
View File

@ -54,8 +54,8 @@ _MICRO_SECONDS_PER_MILLISECOND = 1000
@dataclasses.dataclass
class HandLandmarksDetectionResult:
"""The hand landmarks detection result from HandLandmarker, where each vector
class HandLandmarkerResult:
"""The hand landmarks result from HandLandmarker, where each vector
element represents a single hand detected in the image.
Attributes:
@ -69,9 +69,9 @@ class HandLandmarksDetectionResult:
hand_world_landmarks: List[List[landmark_module.Landmark]]
def _build_detection_result(
def _build_landmarker_result(
output_packets: Mapping[str,packet_module.Packet]
) -> HandLandmarksDetectionResult:
) -> HandLandmarkerResult:
"""Constructs a `HandLandmarksDetectionResult` from output packets."""
handedness_proto_list = packet_getter.get_proto_list(
output_packets[_HANDEDNESS_STREAM_NAME])
@ -114,9 +114,9 @@ def _build_detection_result(
landmark_module.Landmark.create_from_pb2(hand_world_landmark))
hand_world_landmarks_results.append(hand_world_landmarks_list)
return HandLandmarksDetectionResult(handedness_results,
hand_landmarks_results,
hand_world_landmarks_results)
return HandLandmarkerResult(handedness_results,
hand_landmarks_results,
hand_world_landmarks_results)
@dataclasses.dataclass
@ -151,7 +151,7 @@ class HandLandmarkerOptions:
min_hand_presence_confidence: Optional[float] = 0.5
min_tracking_confidence: Optional[float] = 0.5
result_callback: Optional[Callable[
[HandLandmarksDetectionResult, image_module.Image, int], None]] = None
[HandLandmarkerResult, image_module.Image, int], None]] = None
@doc_controls.do_not_generate_docs
def to_pb2(self) -> _HandLandmarkerGraphOptionsProto:
@ -221,11 +221,11 @@ class HandLandmarker(base_vision_task_api.BaseVisionTaskApi):
if output_packets[_HAND_LANDMARKS_STREAM_NAME].is_empty():
empty_packet = output_packets[_HAND_LANDMARKS_STREAM_NAME]
options.result_callback(
HandLandmarksDetectionResult([], [], []), image,
HandLandmarkerResult([], [], []), image,
empty_packet.timestamp.value // _MICRO_SECONDS_PER_MILLISECOND)
return
hand_landmarks_detection_result = _build_detection_result(output_packets)
hand_landmarks_detection_result = _build_landmarker_result(output_packets)
timestamp = output_packets[_HAND_LANDMARKS_STREAM_NAME].timestamp
options.result_callback(hand_landmarks_detection_result, image,
timestamp.value // _MICRO_SECONDS_PER_MILLISECOND)
@ -255,7 +255,7 @@ class HandLandmarker(base_vision_task_api.BaseVisionTaskApi):
self,
image: image_module.Image,
image_processing_options: Optional[_ImageProcessingOptions] = None
) -> HandLandmarksDetectionResult:
) -> HandLandmarkerResult:
"""Performs hand landmarks detection on the given image.
Only use this method when the HandLandmarker is created with the image
@ -286,16 +286,16 @@ class HandLandmarker(base_vision_task_api.BaseVisionTaskApi):
})
if output_packets[_HAND_LANDMARKS_STREAM_NAME].is_empty():
return HandLandmarksDetectionResult([], [], [])
return HandLandmarkerResult([], [], [])
return _build_detection_result(output_packets)
return _build_landmarker_result(output_packets)
def detect_for_video(
self,
image: image_module.Image,
timestamp_ms: int,
image_processing_options: Optional[_ImageProcessingOptions] = None
) -> HandLandmarksDetectionResult:
) -> HandLandmarkerResult:
"""Performs hand landmarks detection on the provided video frame.
Only use this method when the HandLandmarker is created with the video
@ -330,9 +330,9 @@ class HandLandmarker(base_vision_task_api.BaseVisionTaskApi):
})
if output_packets[_HAND_LANDMARKS_STREAM_NAME].is_empty():
return HandLandmarksDetectionResult([], [], [])
return HandLandmarkerResult([], [], [])
return _build_detection_result(output_packets)
return _build_landmarker_result(output_packets)
def detect_async(
self,