[Model] add style transfer model (#922)

* add style transfer model

* add examples for generation model

* add unit test

* add speed comparison

* add speed comparison

* add variable for constant

* add preprocessor and postprocessor

* add preprocessor and postprocessor

* fix

* fix according to review

Co-authored-by: DefTruth <31974251+DefTruth@users.noreply.github.com>

python/fastdeploy/vision/__init__.py

@@ -26,6 +26,7 @@ from . import ocr
 from . import headpose
 from . import sr
 from . import evaluation
+from . import generation
 from .utils import fd_result_to_json
 from .visualize import *
 from .. import C

python/fastdeploy/vision/generation/__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 .contrib.anemigan import AnimeGAN

python/fastdeploy/vision/generation/contrib/__init__.py

@@ -0,0 +1,15 @@
+# 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

python/fastdeploy/vision/generation/contrib/anemigan.py

@@ -0,0 +1,102 @@
+# 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
+import logging
+from .... import FastDeployModel, ModelFormat
+from .... import c_lib_wrap as C
+
+
+class AnimeGANPreprocessor:
+    def __init__(self, config_file):
+        """Create a preprocessor for AnimeGAN.
+        """
+        self._preprocessor = C.vision.generation.AnimeGANPreprocessor()
+
+    def run(self, input_ims):
+        """Preprocess input images for AnimeGAN.
+
+        :param: input_ims: (list of numpy.ndarray)The input image
+        :return: list of FDTensor
+        """
+        return self._preprocessor.run(input_ims)
+
+
+class AnimeGANPostprocessor:
+    def __init__(self):
+        """Create a postprocessor for AnimeGAN.
+        """
+        self._postprocessor = C.vision.generation.AnimeGANPostprocessor()
+
+    def run(self, runtime_results):
+        """Postprocess the runtime results for AnimeGAN
+
+        :param: runtime_results: (list of FDTensor)The output FDTensor results from runtime
+        :return: results: (list) Final results
+        """
+        return self._postprocessor.run(runtime_results)
+
+
+class AnimeGAN(FastDeployModel):
+    def __init__(self,
+                 model_file,
+                 params_file="",
+                 runtime_option=None,
+                 model_format=ModelFormat.PADDLE):
+        """Load a AnimeGAN model.
+
+        :param model_file: (str)Path of model file, e.g ./model.pdmodel
+        :param params_file: (str)Path of parameters file, e.g ./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
+        """
+        # call super constructor to initialize self._runtime_option
+        super(AnimeGAN, self).__init__(runtime_option)
+
+        self._model = C.vision.generation.AnimeGAN(
+            model_file, params_file, self._runtime_option, model_format)
+        # assert self.initialized to confirm initialization successfully.
+        assert self.initialized, "AnimeGAN initialize failed."
+
+    def predict(self, input_image):
+        """ Predict the style transfer result for an input image
+
+        :param input_image: (numpy.ndarray)The input image data, 3-D array with layout HWC, BGR format
+        :return: style transfer result
+        """
+        return self._model.predict(input_image)
+
+    def batch_predict(self, input_images):
+        """ Predict the style transfer result for multiple input images
+
+        :param input_images: (list of numpy.ndarray)The list of input image data, each image is a 3-D array with layout HWC, BGR format
+        :return: a list of style transfer results
+        """
+        return self._model.batch_predict(input_images)
+
+    @property
+    def preprocessor(self):
+        """Get AnimeGANPreprocessor object of the loaded model
+
+        :return AnimeGANPreprocessor
+        """
+        return self._model.preprocessor
+
+    @property
+    def postprocessor(self):
+        """Get AnimeGANPostprocessor object of the loaded model
+
+        :return AnimeGANPostprocessor
+        """
+        return self._model.postprocessor