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- # copyright (c) 2024 PaddlePaddle Authors. All Rights Reserve.
- #
- # 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.
- from __future__ import absolute_import
- from ... import c_lib_wrap as C
- class PPTinyPose(object):
- def __init__(self, det_model=None, pptinypose_model=None):
- """Set initialized detection model object and pptinypose model object
- :param det_model: (ultra_infer.vision.detection.PicoDet)Initialized detection model object
- :param pptinypose_model: (ultra_infer.vision.keypointdetection.PPTinyPose)Initialized pptinypose model object
- """
- assert (
- det_model is not None or pptinypose_model is not None
- ), "The det_model and pptinypose_model cannot be None."
- self._pipeline = C.pipeline.PPTinyPose(
- det_model._model, pptinypose_model._model
- )
- def predict(self, input_image):
- """Predict the keypoint detection result for an input image
- :param im: (numpy.ndarray)The input image data, 3-D array with layout HWC, BGR format
- :return: KeyPointDetectionResult
- """
- return self._pipeline.predict(input_image)
- @property
- def detection_model_score_threshold(self):
- """Atrribute of PPTinyPose pipeline model. Stating the score threshold for detectin model to filter bbox before inputting pptinypose model
- :return: value of detection_model_score_threshold(float)
- """
- return self._pipeline.detection_model_score_threshold
- @detection_model_score_threshold.setter
- def detection_model_score_threshold(self, value):
- """Set attribute detection_model_score_threshold of PPTinyPose pipeline model.
- :param value: (float)The value to set use_dark
- """
- assert isinstance(
- value, float
- ), "The value to set `detection_model_score_threshold` must be type of float."
- self._pipeline.detection_model_score_threshold = value
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