Files
FastDeploy/python/fastdeploy/vision/perception/paddle3d/centerpoint.py
zengshao0622 79a3587339 [Model] Add Paddle3D CenterPoint model (#2078)
* add centerpoint

* update for review comments
2023-07-03 13:39:16 +08:00

93 lines
3.4 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
import logging
from .... import FastDeployModel, ModelFormat
from .... import c_lib_wrap as C
class CenterpointPreprocessor:
def __init__(self, config_file):
"""Create a preprocessor for Centerpoint
"""
self._preprocessor = C.vision.perception.CenterpointPreprocessor(
config_file)
def run(self, point_dirs, num_point_dim, with_timelag):
"""Preprocess input images for Centerpoint
:param: input_ims: (list of numpy.ndarray)The input image
:return: list of FDTensor
"""
return self._preprocessor.run(point_dirs, num_point_dim, with_timelag)
class Centerpoint(FastDeployModel):
def __init__(self,
model_file,
params_file,
config_file,
runtime_option=None,
model_format=ModelFormat.PADDLE):
"""Load a Centerpoint model exported by Centerpoint.
:param model_file: (str)Path of model file, e.g ./Centerpoint.pdmodel
:param params_file: (str)Path of parameters file, e.g ./Centerpoint.pdiparams
:param config_file: (str)Path of config file, e.g ./infer_cfg.yaml
: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(Centerpoint, self).__init__(runtime_option)
self._model = C.vision.perception.Centerpoint(
model_file, params_file, config_file, self._runtime_option,
model_format)
assert self.initialized, "Centerpoint initialize failed."
def predict(self, point_dir):
"""Detect an input image
:param input_image: (numpy.ndarray)The input image data, 3-D array with layout HWC, BGR format
:param conf_threshold: confidence threshold for postprocessing, default is 0.25
:param nms_iou_threshold: iou threshold for NMS, default is 0.5
:return: PerceptionResult
"""
return self._model.predict(point_dir)
def batch_predict(self, points_dir):
"""Classify a batch of input image
: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 PerceptionResult
"""
return self._model.batch_predict(points_dir)
@property
def preprocessor(self):
"""Get CenterpointPreprocessor object of the loaded model
:return CenterpointPreprocessor
"""
return self._model.preprocessor
@property
def postprocessor(self):
"""Get CenterpointPostprocessor object of the loaded model
:return CenterpointPostprocessor
"""
return self._model.postprocessor