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[Model] Add tinypose single && pipeline model (#177)
* Add tinypose model * Add PPTinypose python API * Fix picodet preprocess bug && Add Tinypose examples * Update tinypose example code * Update ppseg preprocess if condition * Update ppseg backend support type * Update permute.h * Update README.md * Update code with comments * Move files dir * Delete premute.cc * Add single model pptinypose * Delete pptinypose old code in ppdet * Code format * Add ppdet + pptinypose pipeline model * Fix bug for posedetpipeline * Change Frontend to ModelFormat * Change Frontend to ModelFormat in __init__.py * Add python posedetpipeline/ * Update pptinypose example dir name * Update README.md * Update README.md * Update README.md * Update README.md * Create keypointdetection_result.md * Create README.md * Create README.md * Create README.md * Update README.md * Update README.md * Create README.md * Fix det_keypoint_unite_infer.py bug * Create README.md * Update PP-Tinypose by comment * Update by comment * Add pipeline directory * Add pptinypose dir * Update pptinypose to align accuracy * Addd warpAffine processor * Update GetCpuMat to GetOpenCVMat * Add comment for pptinypose && pipline * Update docs/main_page.md * Add README.md for pptinypose * Add README for det_keypoint_unite * Remove ENABLE_PIPELINE option * Remove ENABLE_PIPELINE option * Change pptinypose default backend * PP-TinyPose Pipeline support multi PP-Detection models * Update pp-tinypose comment * Update by comments * Add single test example Co-authored-by: Jason <jiangjiajun@baidu.com>
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python/fastdeploy/vision/keypointdetection/__init__.py
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python/fastdeploy/vision/keypointdetection/__init__.py
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# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from __future__ import absolute_import
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from .pptinypose import PPTinyPose
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# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from __future__ import absolute_import
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import logging
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from .... import FastDeployModel, ModelFormat
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from .... import c_lib_wrap as C
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class PPTinyPose(FastDeployModel):
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def __init__(self,
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model_file,
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params_file,
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config_file,
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runtime_option=None,
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model_format=ModelFormat.PADDLE):
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"""load a PPTinyPose model exported by PaddleDetection.
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:param model_file: (str)Path of model file, e.g pptinypose/model.pdmodel
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:param params_file: (str)Path of parameters file, e.g pptinypose/model.pdiparams, if the model_fomat is ModelFormat.ONNX, this param will be ignored, can be set as empty string
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:param config_file: (str)Path of configuration file for deployment, e.g pptinypose/infer_cfg.yml
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:param runtime_option: (fastdeploy.RuntimeOption)RuntimeOption for inference this model, if it's None, will use the default backend on CPU
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:param model_format: (fastdeploy.ModelForamt)Model format of the loaded model
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"""
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super(PPTinyPose, self).__init__(runtime_option)
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assert model_format == ModelFormat.PADDLE, "PPTinyPose model only support model format of ModelFormat.Paddle now."
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self._model = C.vision.keypointdetection.PPTinyPose(
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model_file, params_file, config_file, self._runtime_option,
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model_format)
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assert self.initialized, "PPTinyPose model initialize failed."
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def predict(self, input_image):
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"""Detect keypoints in an input image
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:param im: (numpy.ndarray)The input image data, 3-D array with layout HWC, BGR format
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:return: KeyPointDetectionResult
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"""
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assert input_image is not None, "The input image data is None."
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return self._model.predict(input_image)
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@property
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def use_dark(self):
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"""Atrribute of PPTinyPose model. Stating whether using Distribution-Aware Coordinate Representation for Human Pose Estimation(DARK for short) in postprocess, default is True
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:return: value of use_dark(bool)
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"""
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return self._model.use_dark
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@use_dark.setter
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def use_dark(self, value):
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"""Set attribute use_dark of PPTinyPose model.
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:param value: (bool)The value to set use_dark
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"""
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assert isinstance(
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value, bool), "The value to set `use_dark` must be type of bool."
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self._model.use_dark = value
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