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[CVCUDA] Utilize CV-CUDA batch processing function (#1223)

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* norm and permute batch processing

* move cache to mat, batch processors

* get batched tensor logic, resize on cpu logic

* fix cpu compile error

* remove vector mat api

* nits

* add comments

* nits

* fix batch size

* move initial resize on cpu option to use_cuda api

* fix pybind

* processor manager pybind

* rename mat and matbatch

* move initial resize on cpu to ppcls preprocessor

---------

Co-authored-by: Jason <jiangjiajun@baidu.com>
This commit is contained in:
Wang Xinyu
2023-02-07 13:44:30 +08:00
committed by GitHub
parent 7c9bf11c44
commit d3d914856d
29 changed files with 710 additions and 241 deletions
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36
python/fastdeploy/vision/classification/ppcls/__init__.py
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@@ -16,44 +16,40 @@ from __future__ import absolute_import
import logging
from .... import FastDeployModel, ModelFormat
from .... import c_lib_wrap as C
from ...common import ProcessorManager
class PaddleClasPreprocessor:
class PaddleClasPreprocessor(ProcessorManager):
def __init__(self, config_file):
"""Create a preprocessor for PaddleClasModel from configuration file
:param config_file: (str)Path of configuration file, e.g resnet50/inference_cls.yaml
"""
self._preprocessor = C.vision.classification.PaddleClasPreprocessor(
super(PaddleClasPreprocessor, self).__init__()
self._manager = C.vision.classification.PaddleClasPreprocessor(
config_file)
def run(self, input_ims):
"""Preprocess input images for PaddleClasModel
:param: input_ims: (list of numpy.ndarray)The input image
:return: list of FDTensor
"""
return self._preprocessor.run(input_ims)
def use_cuda(self, enable_cv_cuda=False, gpu_id=-1):
"""Use CUDA preprocessors
:param: enable_cv_cuda: Whether to enable CV-CUDA
:param: gpu_id: GPU device id
"""
return self._preprocessor.use_cuda(enable_cv_cuda, gpu_id)
def disable_normalize(self):
"""
This function will disable normalize in preprocessing step.
"""
self._preprocessor.disable_normalize()
self._manager.disable_normalize()
def disable_permute(self):
"""
This function will disable hwc2chw in preprocessing step.
"""
self._preprocessor.disable_permute()
self._manager.disable_permute()
def initial_resize_on_cpu(self, v):
"""
When the initial operator is Resize, and input image size is large,
maybe it's better to run resize on CPU, because the HostToDevice memcpy
is time consuming. Set this True to run the initial resize on CPU.
:param: v: True or False
"""
self._manager.initial_resize_on_cpu(v)
class PaddleClasPostprocessor: