[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>

python/fastdeploy/pipeline/__init__.py

@@ -0,0 +1,16 @@
+# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
+#
+# 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 .pptinypose import PPTinyPose

python/fastdeploy/pipeline/pptinypose/__init__.py

@@ -0,0 +1,55 @@
+# # Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
+# #
+# # 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: (fastdeploy.vision.detection.PicoDet)Initialized detection model object
+        :param pptinypose_model: (fastdeploy.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