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c7ec14de95
* [Model] add vsr serials models Signed-off-by: ChaoII <849453582@qq.com> * [Model] add vsr serials models Signed-off-by: ChaoII <849453582@qq.com> * fix build problem Signed-off-by: ChaoII <849453582@qq.com> * fix code style Signed-off-by: ChaoII <849453582@qq.com> * modify according to review suggestions Signed-off-by: ChaoII <849453582@qq.com> * modify vsr trt example Signed-off-by: ChaoII <849453582@qq.com> * update sr directory * fix BindPPSR * add doxygen comment * add sr unit test * update model file url Signed-off-by: ChaoII <849453582@qq.com> Co-authored-by: Jason <jiangjiajun@baidu.com>
108 lines
5.0 KiB
Python
108 lines
5.0 KiB
Python
# 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 .... import FastDeployModel, ModelFormat
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from .... import c_lib_wrap as C
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class PPMSVSR(FastDeployModel):
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def __init__(self,
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model_file,
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params_file,
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runtime_option=None,
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model_format=ModelFormat.PADDLE):
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"""Load a VSR model exported by PaddleGAN.
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:param model_file: (str)Path of model file, e.g PPMSVSR/inference.pdmodel
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:param params_file: (str)Path of parameters file, e.g PPMSVSR/inference.pdiparams
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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(PPMSVSR, self).__init__(runtime_option)
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assert model_format == ModelFormat.PADDLE, "PPMSVSR model only support model format of ModelFormat.Paddle now."
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self._model = C.vision.sr.PPMSVSR(model_file, params_file,
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self._runtime_option, model_format)
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assert self.initialized, "PPMSVSR model initialize failed."
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def predict(self, input_images):
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"""Predict the super resolution frame sequences for an input frame sequences
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:param input_images: list[numpy.ndarray] The input image data, 3-D array with layout HWC, BGR format
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:return: list[numpy.ndarray]
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"""
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assert input_images is not None, "The input image data is None."
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return self._model.predict(input_images)
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class EDVR(PPMSVSR):
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def __init__(self,
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model_file,
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params_file,
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runtime_option=None,
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model_format=ModelFormat.PADDLE):
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"""Load a EDVR model exported by PaddleGAN.
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:param model_file: (str)Path of model file, e.g EDVR/inference.pdmodel
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:param params_file: (str)Path of parameters file, e.g EDVR/inference.pdiparams
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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(PPMSVSR, self).__init__(runtime_option)
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assert model_format == ModelFormat.PADDLE, "EDVR model only support model format of ModelFormat.Paddle now."
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self._model = C.vision.sr.EDVR(model_file, params_file,
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self._runtime_option, model_format)
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assert self.initialized, "EDVR model initialize failed."
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def predict(self, input_images):
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"""Predict the super resolution frame sequences for an input frame sequences
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:param input_images: list[numpy.ndarray] The input image data, 3-D array with layout HWC, BGR format
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:return: list[numpy.ndarray]
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"""
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assert input_images is not None, "The input image data is None."
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return self._model.predict(input_images)
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class BasicVSR(PPMSVSR):
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def __init__(self,
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model_file,
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params_file,
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runtime_option=None,
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model_format=ModelFormat.PADDLE):
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"""Load a EDVR model exported by PaddleGAN.
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:param model_file: (str)Path of model file, e.g BasicVSR/inference.pdmodel
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:param params_file: (str)Path of parameters file, e.g BasicVSR/inference.pdiparams
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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(PPMSVSR, self).__init__(runtime_option)
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assert model_format == ModelFormat.PADDLE, "BasicVSR model only support model format of ModelFormat.Paddle now."
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self._model = C.vision.sr.BasicVSR(model_file, params_file,
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self._runtime_option, model_format)
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assert self.initialized, "BasicVSR model initialize failed."
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def predict(self, input_images):
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"""Predict the super resolution frame sequences for an input frame sequences
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:param input_images: list[numpy.ndarray] The input image data, 3-D array with layout HWC, BGR format
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:return: list[numpy.ndarray]
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"""
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assert input_images is not None, "The input image data is None."
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return self._model.predict(input_images)
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