mirror of
https://github.com/PaddlePaddle/FastDeploy.git
synced 2025-10-07 01:22:59 +08:00
c6480de736
* bind success * bind success fix * FDMat pybind, ResizeByShort pybind * FDMat pybind, ResizeByShort pybind, remove initialized_ * override BindProcessorManager::Run in python is available * PyProcessorManager done * vision_pybind fix * manager.py fix * add tutorials * remove Apply() bind * remove Apply() bind and fix * fix reviewed problem * fix reviewed problem * fix reviewed problem readme * fix reviewed problem readme etc * apply return outputs * nits * update readme * fix FDMatbatch * add op pybind: CenterCrop, Pad * add op overload for pass FDMatBatch --------- Co-authored-by: Wang Xinyu <shaywxy@gmail.com>
70 lines
2.1 KiB
Python
70 lines
2.1 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 abc import ABC, abstractmethod
|
|
from ... import c_lib_wrap as C
|
|
|
|
|
|
class ProcessorManager:
|
|
def __init__(self):
|
|
self._manager = None
|
|
|
|
def run(self, input_ims):
|
|
"""Process input image
|
|
|
|
:param: input_ims: (list of numpy.ndarray) The input images
|
|
:return: list of FDTensor
|
|
"""
|
|
return self._manager.run(input_ims)
|
|
|
|
def use_cuda(self, enable_cv_cuda=False, gpu_id=-1):
|
|
"""Use CUDA processors
|
|
|
|
:param: enable_cv_cuda: Ture: use CV-CUDA, False: use CUDA only
|
|
:param: gpu_id: GPU device id
|
|
"""
|
|
return self._manager.use_cuda(enable_cv_cuda, gpu_id)
|
|
|
|
|
|
class PyProcessorManager(ABC):
|
|
"""
|
|
PyProcessorManager is used to define a customized processor in python
|
|
"""
|
|
|
|
def __init__(self):
|
|
self._manager = C.vision.processors.ProcessorManager()
|
|
|
|
def use_cuda(self, enable_cv_cuda=False, gpu_id=-1):
|
|
"""Use CUDA processors
|
|
|
|
:param: enable_cv_cuda: Ture: use CV-CUDA, False: use CUDA only
|
|
:param: gpu_id: GPU device id
|
|
"""
|
|
return self._manager.use_cuda(enable_cv_cuda, gpu_id)
|
|
|
|
def __call__(self, images):
|
|
image_batch = C.vision.FDMatBatch()
|
|
image_batch.from_mats(images)
|
|
|
|
self._manager.pre_apply(image_batch)
|
|
outputs = self.apply(image_batch)
|
|
self._manager.post_apply()
|
|
return outputs
|
|
|
|
@abstractmethod
|
|
def apply(self, image_batch):
|
|
print("This function has to be implemented.")
|
|
return []
|