mirror of
https://github.com/PaddlePaddle/FastDeploy.git
synced 2025-10-30 19:36:42 +08:00
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.
|
|
#
|
|
# 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 PPMSVSR(FastDeployModel):
|
|
def __init__(self,
|
|
model_file,
|
|
params_file,
|
|
runtime_option=None,
|
|
model_format=ModelFormat.PADDLE):
|
|
"""Load a VSR model exported by PaddleGAN.
|
|
|
|
:param model_file: (str)Path of model file, e.g PPMSVSR/inference.pdmodel
|
|
:param params_file: (str)Path of parameters file, e.g PPMSVSR/inference.pdiparams
|
|
: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(PPMSVSR, self).__init__(runtime_option)
|
|
|
|
assert model_format == ModelFormat.PADDLE, "PPMSVSR model only support model format of ModelFormat.Paddle now."
|
|
self._model = C.vision.sr.PPMSVSR(model_file, params_file,
|
|
self._runtime_option, model_format)
|
|
assert self.initialized, "PPMSVSR model initialize failed."
|
|
|
|
def predict(self, input_images):
|
|
"""Predict the super resolution frame sequences for an input frame sequences
|
|
|
|
:param input_images: list[numpy.ndarray] The input image data, 3-D array with layout HWC, BGR format
|
|
:return: list[numpy.ndarray]
|
|
"""
|
|
assert input_images is not None, "The input image data is None."
|
|
return self._model.predict(input_images)
|
|
|
|
|
|
class EDVR(PPMSVSR):
|
|
def __init__(self,
|
|
model_file,
|
|
params_file,
|
|
runtime_option=None,
|
|
model_format=ModelFormat.PADDLE):
|
|
"""Load a EDVR model exported by PaddleGAN.
|
|
|
|
:param model_file: (str)Path of model file, e.g EDVR/inference.pdmodel
|
|
:param params_file: (str)Path of parameters file, e.g EDVR/inference.pdiparams
|
|
: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(PPMSVSR, self).__init__(runtime_option)
|
|
|
|
assert model_format == ModelFormat.PADDLE, "EDVR model only support model format of ModelFormat.Paddle now."
|
|
self._model = C.vision.sr.EDVR(model_file, params_file,
|
|
self._runtime_option, model_format)
|
|
assert self.initialized, "EDVR model initialize failed."
|
|
|
|
def predict(self, input_images):
|
|
"""Predict the super resolution frame sequences for an input frame sequences
|
|
|
|
:param input_images: list[numpy.ndarray] The input image data, 3-D array with layout HWC, BGR format
|
|
:return: list[numpy.ndarray]
|
|
"""
|
|
assert input_images is not None, "The input image data is None."
|
|
return self._model.predict(input_images)
|
|
|
|
|
|
class BasicVSR(PPMSVSR):
|
|
def __init__(self,
|
|
model_file,
|
|
params_file,
|
|
runtime_option=None,
|
|
model_format=ModelFormat.PADDLE):
|
|
"""Load a EDVR model exported by PaddleGAN.
|
|
|
|
:param model_file: (str)Path of model file, e.g BasicVSR/inference.pdmodel
|
|
:param params_file: (str)Path of parameters file, e.g BasicVSR/inference.pdiparams
|
|
: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(PPMSVSR, self).__init__(runtime_option)
|
|
|
|
assert model_format == ModelFormat.PADDLE, "BasicVSR model only support model format of ModelFormat.Paddle now."
|
|
self._model = C.vision.sr.BasicVSR(model_file, params_file,
|
|
self._runtime_option, model_format)
|
|
assert self.initialized, "BasicVSR model initialize failed."
|
|
|
|
def predict(self, input_images):
|
|
"""Predict the super resolution frame sequences for an input frame sequences
|
|
|
|
:param input_images: list[numpy.ndarray] The input image data, 3-D array with layout HWC, BGR format
|
|
:return: list[numpy.ndarray]
|
|
"""
|
|
assert input_images is not None, "The input image data is None."
|
|
return self._model.predict(input_images)
|