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106 lines
3.6 KiB
Python
106 lines
3.6 KiB
Python
# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from __future__ import absolute_import
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import logging
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from .... import FastDeployModel, Frontend
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from .... import c_lib_wrap as C
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class NanoDetPlus(FastDeployModel):
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def __init__(self,
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model_file,
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params_file="",
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runtime_option=None,
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model_format=Frontend.ONNX):
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# 调用基函数进行backend_option的初始化
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# 初始化后的option保存在self._runtime_option
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super(NanoDetPlus, self).__init__(runtime_option)
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self._model = C.vision.detection.NanoDetPlus(
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model_file, params_file, self._runtime_option, model_format)
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# 通过self.initialized判断整个模型的初始化是否成功
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assert self.initialized, "NanoDetPlus initialize failed."
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def predict(self, input_image, conf_threshold=0.25, nms_iou_threshold=0.5):
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return self._model.predict(input_image, conf_threshold,
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nms_iou_threshold)
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# 一些跟NanoDetPlus模型有关的属性封装
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# 多数是预处理相关，可通过修改如model.size = [416, 416]改变预处理时resize的大小（前提是模型支持）
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@property
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def size(self):
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return self._model.size
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@property
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def padding_value(self):
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return self._model.padding_value
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@property
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def keep_ratio(self):
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return self._model.keep_ratio
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@property
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def downsample_strides(self):
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return self._model.downsample_strides
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@property
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def max_wh(self):
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return self._model.max_wh
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@property
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def reg_max(self):
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return self._model.reg_max
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@size.setter
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def size(self, wh):
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assert isinstance(wh, (list, tuple)),\
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"The value to set `size` must be type of tuple or list."
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assert len(wh) == 2,\
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"The value to set `size` must contatins 2 elements means [width, height], but now it contains {} elements.".format(
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len(wh))
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self._model.size = wh
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@padding_value.setter
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def padding_value(self, value):
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assert isinstance(
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value,
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list), "The value to set `padding_value` must be type of list."
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self._model.padding_value = value
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@keep_ratio.setter
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def keep_ratio(self, value):
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assert isinstance(
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value, bool), "The value to set `keep_ratio` must be type of bool."
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self._model.keep_ratio = value
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@downsample_strides.setter
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def downsample_strides(self, value):
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assert isinstance(
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value,
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list), "The value to set `downsample_strides` must be type of list."
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self._model.downsample_strides = value
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@max_wh.setter
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def max_wh(self, value):
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assert isinstance(
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value, float), "The value to set `max_wh` must be type of float."
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self._model.max_wh = value
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@reg_max.setter
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def reg_max(self, value):
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assert isinstance(
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value, int), "The value to set `reg_max` must be type of int."
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self._model.reg_max = value
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