mirror of
https://github.com/PaddlePaddle/FastDeploy.git
synced 2025-10-05 08:37:06 +08:00
941057888a
* Add files via upload * Add files via upload * Add files via upload * Add files via upload * Add files via upload * Add files via upload * Add files via upload * Add files via upload * Add files via upload * Add files via upload * Add files via upload * Add files via upload * Add files via upload * Add files via upload Co-authored-by: DefTruth <31974251+DefTruth@users.noreply.github.com>
300 lines
13 KiB
Python
300 lines
13 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 typing import Union, List
|
|
import logging
|
|
from .... import FastDeployModel, ModelFormat
|
|
from .... import c_lib_wrap as C
|
|
|
|
|
|
class PaddleDetPreprocessor:
|
|
def __init__(self, config_file):
|
|
"""Create a preprocessor for PaddleDetection Model from configuration file
|
|
|
|
:param config_file: (str)Path of configuration file, e.g ppyoloe/infer_cfg.yml
|
|
"""
|
|
self._preprocessor = C.vision.detection.PaddleDetPreprocessor(
|
|
config_file)
|
|
|
|
def run(self, input_ims):
|
|
"""Preprocess input images for PaddleDetection Model
|
|
|
|
:param: input_ims: (list of numpy.ndarray)The input image
|
|
:return: list of FDTensor, include image, scale_factor, im_shape
|
|
"""
|
|
return self._preprocessor.run(input_ims)
|
|
|
|
|
|
class PaddleDetPostprocessor:
|
|
def __init__(self):
|
|
"""Create a postprocessor for PaddleDetection Model
|
|
|
|
"""
|
|
self._postprocessor = C.vision.detection.PaddleDetPostprocessor()
|
|
|
|
def run(self, runtime_results):
|
|
"""Postprocess the runtime results for PaddleDetection Model
|
|
|
|
:param: runtime_results: (list of FDTensor)The output FDTensor results from runtime
|
|
:return: list of ClassifyResult(If the runtime_results is predict by batched samples, the length of this list equals to the batch size)
|
|
"""
|
|
return self._postprocessor.run(runtime_results)
|
|
|
|
def apply_decode_and_nms(self):
|
|
"""This function will enable decode and nms in postprocess step.
|
|
"""
|
|
return self._postprocessor.apply_decode_and_nms()
|
|
|
|
|
|
class PPYOLOE(FastDeployModel):
|
|
def __init__(self,
|
|
model_file,
|
|
params_file,
|
|
config_file,
|
|
runtime_option=None,
|
|
model_format=ModelFormat.PADDLE):
|
|
"""Load a PPYOLOE model exported by PaddleDetection.
|
|
|
|
:param model_file: (str)Path of model file, e.g ppyoloe/model.pdmodel
|
|
:param params_file: (str)Path of parameters file, e.g ppyoloe/model.pdiparams, if the model_fomat is ModelFormat.ONNX, this param will be ignored, can be set as empty string
|
|
:param config_file: (str)Path of configuration file for deployment, e.g ppyoloe/infer_cfg.yml
|
|
: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(PPYOLOE, self).__init__(runtime_option)
|
|
|
|
self._model = C.vision.detection.PPYOLOE(
|
|
model_file, params_file, config_file, self._runtime_option,
|
|
model_format)
|
|
assert self.initialized, "PPYOLOE model initialize failed."
|
|
|
|
def predict(self, im):
|
|
"""Detect an input image
|
|
|
|
:param im: (numpy.ndarray)The input image data, 3-D array with layout HWC, BGR format
|
|
:return: DetectionResult
|
|
"""
|
|
|
|
assert im is not None, "The input image data is None."
|
|
return self._model.predict(im)
|
|
|
|
def batch_predict(self, images):
|
|
"""Detect a batch of input image list
|
|
|
|
:param im: (list of numpy.ndarray) The input image list, each element is a 3-D array with layout HWC, BGR format
|
|
:return list of DetectionResult
|
|
"""
|
|
|
|
return self._model.batch_predict(images)
|
|
|
|
@property
|
|
def preprocessor(self):
|
|
"""Get PaddleDetPreprocessor object of the loaded model
|
|
|
|
:return PaddleDetPreprocessor
|
|
"""
|
|
return self._model.preprocessor
|
|
|
|
@property
|
|
def postprocessor(self):
|
|
"""Get PaddleDetPostprocessor object of the loaded model
|
|
|
|
:return PaddleDetPostprocessor
|
|
"""
|
|
return self._model.postprocessor
|
|
|
|
|
|
class PPYOLO(PPYOLOE):
|
|
def __init__(self,
|
|
model_file,
|
|
params_file,
|
|
config_file,
|
|
runtime_option=None,
|
|
model_format=ModelFormat.PADDLE):
|
|
"""Load a PPYOLO model exported by PaddleDetection.
|
|
|
|
:param model_file: (str)Path of model file, e.g ppyolo/model.pdmodel
|
|
:param params_file: (str)Path of parameters file, e.g ppyolo/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
|
|
"""
|
|
|
|
super(PPYOLOE, self).__init__(runtime_option)
|
|
|
|
assert model_format == ModelFormat.PADDLE, "PPYOLO model only support model format of ModelFormat.Paddle now."
|
|
self._model = C.vision.detection.PPYOLO(
|
|
model_file, params_file, config_file, self._runtime_option,
|
|
model_format)
|
|
assert self.initialized, "PPYOLO model initialize failed."
|
|
|
|
|
|
class PaddleYOLOX(PPYOLOE):
|
|
def __init__(self,
|
|
model_file,
|
|
params_file,
|
|
config_file,
|
|
runtime_option=None,
|
|
model_format=ModelFormat.PADDLE):
|
|
"""Load a YOLOX model exported by PaddleDetection.
|
|
|
|
:param model_file: (str)Path of model file, e.g yolox/model.pdmodel
|
|
:param params_file: (str)Path of parameters file, e.g yolox/model.pdiparams, if the model_fomat is ModelFormat.ONNX, this param will be ignored, can be set as empty string
|
|
:param config_file: (str)Path of configuration file for deployment, e.g ppyoloe/infer_cfg.yml
|
|
: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(PPYOLOE, self).__init__(runtime_option)
|
|
|
|
assert model_format == ModelFormat.PADDLE, "PaddleYOLOX model only support model format of ModelFormat.Paddle now."
|
|
self._model = C.vision.detection.PaddleYOLOX(
|
|
model_file, params_file, config_file, self._runtime_option,
|
|
model_format)
|
|
assert self.initialized, "PaddleYOLOX model initialize failed."
|
|
|
|
|
|
class PicoDet(PPYOLOE):
|
|
def __init__(self,
|
|
model_file,
|
|
params_file,
|
|
config_file,
|
|
runtime_option=None,
|
|
model_format=ModelFormat.PADDLE):
|
|
"""Load a PicoDet model exported by PaddleDetection.
|
|
|
|
:param model_file: (str)Path of model file, e.g picodet/model.pdmodel
|
|
:param params_file: (str)Path of parameters file, e.g picodet/model.pdiparams, if the model_fomat is ModelFormat.ONNX, this param will be ignored, can be set as empty string
|
|
:param config_file: (str)Path of configuration file for deployment, e.g ppyoloe/infer_cfg.yml
|
|
: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(PPYOLOE, self).__init__(runtime_option)
|
|
|
|
self._model = C.vision.detection.PicoDet(
|
|
model_file, params_file, config_file, self._runtime_option,
|
|
model_format)
|
|
assert self.initialized, "PicoDet model initialize failed."
|
|
|
|
|
|
class FasterRCNN(PPYOLOE):
|
|
def __init__(self,
|
|
model_file,
|
|
params_file,
|
|
config_file,
|
|
runtime_option=None,
|
|
model_format=ModelFormat.PADDLE):
|
|
"""Load a FasterRCNN model exported by PaddleDetection.
|
|
|
|
:param model_file: (str)Path of model file, e.g fasterrcnn/model.pdmodel
|
|
:param params_file: (str)Path of parameters file, e.g fasterrcnn/model.pdiparams, if the model_fomat is ModelFormat.ONNX, this param will be ignored, can be set as empty string
|
|
:param config_file: (str)Path of configuration file for deployment, e.g ppyoloe/infer_cfg.yml
|
|
: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(PPYOLOE, self).__init__(runtime_option)
|
|
|
|
assert model_format == ModelFormat.PADDLE, "FasterRCNN model only support model format of ModelFormat.Paddle now."
|
|
self._model = C.vision.detection.FasterRCNN(
|
|
model_file, params_file, config_file, self._runtime_option,
|
|
model_format)
|
|
assert self.initialized, "FasterRCNN model initialize failed."
|
|
|
|
|
|
class YOLOv3(PPYOLOE):
|
|
def __init__(self,
|
|
model_file,
|
|
params_file,
|
|
config_file,
|
|
runtime_option=None,
|
|
model_format=ModelFormat.PADDLE):
|
|
"""Load a YOLOv3 model exported by PaddleDetection.
|
|
|
|
:param model_file: (str)Path of model file, e.g yolov3/model.pdmodel
|
|
:param params_file: (str)Path of parameters file, e.g yolov3/model.pdiparams, if the model_fomat is ModelFormat.ONNX, this param will be ignored, can be set as empty string
|
|
:param config_file: (str)Path of configuration file for deployment, e.g ppyoloe/infer_cfg.yml
|
|
: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(PPYOLOE, self).__init__(runtime_option)
|
|
|
|
assert model_format == ModelFormat.PADDLE, "YOLOv3 model only support model format of ModelFormat.Paddle now."
|
|
self._model = C.vision.detection.YOLOv3(
|
|
model_file, params_file, config_file, self._runtime_option,
|
|
model_format)
|
|
assert self.initialized, "YOLOv3 model initialize failed."
|
|
|
|
|
|
class MaskRCNN(PPYOLOE):
|
|
def __init__(self,
|
|
model_file,
|
|
params_file,
|
|
config_file,
|
|
runtime_option=None,
|
|
model_format=ModelFormat.PADDLE):
|
|
"""Load a MaskRCNN model exported by PaddleDetection.
|
|
|
|
:param model_file: (str)Path of model file, e.g fasterrcnn/model.pdmodel
|
|
:param params_file: (str)Path of parameters file, e.g fasterrcnn/model.pdiparams, if the model_fomat is ModelFormat.ONNX, this param will be ignored, can be set as empty string
|
|
:param config_file: (str)Path of configuration file for deployment, e.g ppyoloe/infer_cfg.yml
|
|
: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(PPYOLOE, self).__init__(runtime_option)
|
|
|
|
assert model_format == ModelFormat.PADDLE, "MaskRCNN model only support model format of ModelFormat.Paddle now."
|
|
self._model = C.vision.detection.MaskRCNN(
|
|
model_file, params_file, config_file, self._runtime_option,
|
|
model_format)
|
|
assert self.initialized, "MaskRCNN model initialize failed."
|
|
|
|
def batch_predict(self, images):
|
|
"""Detect a batch of input image list, batch_predict is not supported for maskrcnn now.
|
|
|
|
:param im: (list of numpy.ndarray) The input image list, each element is a 3-D array with layout HWC, BGR format
|
|
:return list of DetectionResult
|
|
"""
|
|
|
|
raise Exception(
|
|
"batch_predict is not supported for MaskRCNN model now.")
|
|
|
|
|
|
class SSD(PPYOLOE):
|
|
def __init__(self,
|
|
model_file,
|
|
params_file,
|
|
config_file,
|
|
runtime_option=None,
|
|
model_format=ModelFormat.PADDLE):
|
|
"""Load a SSD model exported by PaddleDetection.
|
|
|
|
:param model_file: (str)Path of model file, e.g ssd/model.pdmodel
|
|
:param params_file: (str)Path of parameters file, e.g ssd/model.pdiparams, if the model_fomat is ModelFormat.ONNX, this param will be ignored, can be set as empty string
|
|
:param config_file: (str)Path of configuration file for deployment, e.g ppyoloe/infer_cfg.yml
|
|
: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(PPYOLOE, self).__init__(runtime_option)
|
|
|
|
assert model_format == ModelFormat.PADDLE, "SSD model only support model format of ModelFormat.Paddle now."
|
|
self._model = C.vision.detection.SSD(
|
|
model_file, params_file, config_file, self._runtime_option,
|
|
model_format)
|
|
assert self.initialized, "SSD model initialize failed."
|