[Model] Refactor insightface models (#919)

* 重构insightface代码

* 重写insightface example代码

* 重写insightface example代码

* 删除多余代码

* 修改预处理代码

* 修改文档

* 修改文档

* 恢复误删除的文件

* 修改cpp example

* 修改cpp example

* 测试python代码

* 测试python代码

* 测试python代码

* 测试python代码

* 测试python代码

* 测试python代码

* 测试python代码

* 跑通python代码

* 修复重复初始化的bug

* 更新adaface的python代码

* 修复c++重复初始化的问题

* 修复c++重复初始化的问题

* 修复Python重复初始化的问题

* 新增preprocess的几个参数的获取方式

* 修复注释的错误

* 按照要求修改

* 修改文档中的图片为图片压缩包

* 修改编译完成后程序的提示

* 更新错误include

* 删除无用文件

* 更新文档

python/fastdeploy/vision/faceid/contrib/adaface/__init__.py

@@ -0,0 +1,109 @@
+# 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 FastDeployModel, ModelFormat
+from ..... import c_lib_wrap as C
+
+
+class AdaFacePreprocessor:
+    def __init__(self):
+        """Create a preprocessor for AdaFace Model
+        """
+        self._preprocessor = C.vision.faceid.AdaFacePreprocessor()
+
+    def run(self, input_ims):
+        """Preprocess input images for AdaFace Model
+
+        :param: input_ims: (list of numpy.ndarray)The input image
+        :return: list of FDTensor, include image, scale_factor, im_shape
+        """
+        return self._preprocessor.run(input_ims)
+
+
+class AdaFacePostprocessor:
+    def __init__(self):
+        """Create a postprocessor for AdaFace Model
+
+        """
+        self._postprocessor = C.vision.faceid.AdaFacePostprocessor()
+
+    def run(self, runtime_results):
+        """Postprocess the runtime results for PaddleClas Model
+
+        :param: runtime_results: (list of FDTensor)The output FDTensor results from runtime
+        :return: list of FaceRecognitionResult(If the runtime_results is predict by batched samples, the length of this list equals to the batch size)
+        """
+        return self._postprocessor.run(runtime_results)
+
+    @property
+    def l2_normalize(self):
+        """
+        confidence threshold for postprocessing, default is 0.5
+        """
+        return self._postprocessor.l2_normalize
+
+
+class AdaFace(FastDeployModel):
+    def __init__(self,
+                 model_file,
+                 params_file="",
+                 runtime_option=None,
+                 model_format=ModelFormat.ONNX):
+        """Load a AdaFace model exported by PaddleClas.
+
+        :param model_file: (str)Path of model file, e.g adaface/model.pdmodel
+        :param params_file: (str)Path of parameters file, e.g adaface/model.pdiparams, if the model_fomat is ModelFormat.ONNX, this param will be ignored, can be set as empty string
+        :param runtime_option: (fastdeploy.RuntimeOption)RuntimeOption for inference this model, if it's None, will use the default backend on CPU
+        :param model_format: (fastdeploy.ModelForamt)Model format of the loaded model
+        """
+        super(AdaFace, self).__init__(runtime_option)
+        self._model = C.vision.faceid.AdaFace(
+            model_file, params_file, self._runtime_option, model_format)
+        assert self.initialized, "AdaFace model initialize failed."
+
+    def predict(self, im):
+        """Detect an input image
+
+        :param im: (numpy.ndarray)The input image data, 3-D array with layout HWC, BGR format
+        :return: DetectionResult
+        """
+
+        assert im is not None, "The input image data is None."
+        return self._model.predict(im)
+
+    def batch_predict(self, images):
+        """Detect a batch of input image list
+
+        :param im: (list of numpy.ndarray) The input image list, each element is a 3-D array with layout HWC, BGR format
+        :return list of DetectionResult
+        """
+
+        return self._model.batch_predict(images)
+
+    @property
+    def preprocessor(self):
+        """Get AdaFacePreprocessor object of the loaded model
+
+        :return AdaFacePreprocessor
+        """
+        return self._model.preprocessor
+
+    @property
+    def postprocessor(self):
+        """Get AdaFacePostprocessor object of the loaded model
+
+        :return AdaFacePostprocessor
+        """
+        return self._model.postprocessor