Modify file structure to separate python and cpp code (#223)

Modify code structure
This commit is contained in:
Jason
2022-09-14 15:44:13 +08:00
committed by GitHub
parent 26cb1dc838
commit 68523be411
290 changed files with 10 additions and 9 deletions

View File

@@ -0,0 +1,15 @@
# 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

View File

@@ -0,0 +1,98 @@
# 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, Frontend
from .... import c_lib_wrap as C
class RetinaFace(FastDeployModel):
def __init__(self,
model_file,
params_file="",
runtime_option=None,
model_format=Frontend.ONNX):
# 调用基函数进行backend_option的初始化
# 初始化后的option保存在self._runtime_option
super(RetinaFace, self).__init__(runtime_option)
self._model = C.vision.facedet.RetinaFace(
model_file, params_file, self._runtime_option, model_format)
# 通过self.initialized判断整个模型的初始化是否成功
assert self.initialized, "RetinaFace initialize failed."
def predict(self, input_image, conf_threshold=0.7, nms_iou_threshold=0.3):
return self._model.predict(input_image, conf_threshold,
nms_iou_threshold)
# 一些跟模型有关的属性封装
# 多数是预处理相关可通过修改如model.size = [640, 480]改变预处理时resize的大小前提是模型支持
@property
def size(self):
return self._model.size
@property
def variance(self):
return self._model.variance
@property
def downsample_strides(self):
return self._model.downsample_strides
@property
def min_sizes(self):
return self._model.min_sizes
@property
def landmarks_per_face(self):
return self._model.landmarks_per_face
@size.setter
def size(self, wh):
assert isinstance(wh, (list, tuple)),\
"The value to set `size` must be type of tuple or list."
assert len(wh) == 2,\
"The value to set `size` must contatins 2 elements means [width, height], but now it contains {} elements.".format(
len(wh))
self._model.size = wh
@variance.setter
def variance(self, value):
assert isinstance(v, (list, tuple)),\
"The value to set `variance` must be type of tuple or list."
assert len(value) == 2,\
"The value to set `variance` must contatins 2 elements".format(
len(value))
self._model.variance = value
@downsample_strides.setter
def downsample_strides(self, value):
assert isinstance(
value,
list), "The value to set `downsample_strides` must be type of list."
self._model.downsample_strides = value
@min_sizes.setter
def min_sizes(self, value):
assert isinstance(
value, list), "The value to set `min_sizes` must be type of list."
self._model.min_sizes = value
@landmarks_per_face.setter
def landmarks_per_face(self, value):
assert isinstance(
value,
int), "The value to set `landmarks_per_face` must be type of int."
self._model.landmarks_per_face = value

View File

@@ -0,0 +1,158 @@
# 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, Frontend
from .... import c_lib_wrap as C
class SCRFD(FastDeployModel):
def __init__(self,
model_file,
params_file="",
runtime_option=None,
model_format=Frontend.ONNX):
# 调用基函数进行backend_option的初始化
# 初始化后的option保存在self._runtime_option
super(SCRFD, self).__init__(runtime_option)
self._model = C.vision.facedet.SCRFD(
model_file, params_file, self._runtime_option, model_format)
# 通过self.initialized判断整个模型的初始化是否成功
assert self.initialized, "SCRFD initialize failed."
def predict(self, input_image, conf_threshold=0.7, nms_iou_threshold=0.3):
return self._model.predict(input_image, conf_threshold,
nms_iou_threshold)
# 一些跟SCRFD模型有关的属性封装
# 多数是预处理相关可通过修改如model.size = [640, 640]改变预处理时resize的大小前提是模型支持
@property
def size(self):
return self._model.size
@property
def padding_value(self):
return self._model.padding_value
@property
def is_no_pad(self):
return self._model.is_no_pad
@property
def is_mini_pad(self):
return self._model.is_mini_pad
@property
def is_scale_up(self):
return self._model.is_scale_up
@property
def stride(self):
return self._model.stride
@property
def downsample_strides(self):
return self._model.downsample_strides
@property
def landmarks_per_face(self):
return self._model.landmarks_per_face
@property
def use_kps(self):
return self._model.use_kps
@property
def max_nms(self):
return self._model.max_nms
@property
def num_anchors(self):
return self._model.num_anchors
@size.setter
def size(self, wh):
assert isinstance(wh, (list, tuple)),\
"The value to set `size` must be type of tuple or list."
assert len(wh) == 2,\
"The value to set `size` must contatins 2 elements means [width, height], but now it contains {} elements.".format(
len(wh))
self._model.size = wh
@padding_value.setter
def padding_value(self, value):
assert isinstance(
value,
list), "The value to set `padding_value` must be type of list."
self._model.padding_value = value
@is_no_pad.setter
def is_no_pad(self, value):
assert isinstance(
value, bool), "The value to set `is_no_pad` must be type of bool."
self._model.is_no_pad = value
@is_mini_pad.setter
def is_mini_pad(self, value):
assert isinstance(
value,
bool), "The value to set `is_mini_pad` must be type of bool."
self._model.is_mini_pad = value
@is_scale_up.setter
def is_scale_up(self, value):
assert isinstance(
value,
bool), "The value to set `is_scale_up` must be type of bool."
self._model.is_scale_up = value
@stride.setter
def stride(self, value):
assert isinstance(
value, int), "The value to set `stride` must be type of int."
self._model.stride = value
@downsample_strides.setter
def downsample_strides(self, value):
assert isinstance(
value,
list), "The value to set `downsample_strides` must be type of list."
self._model.downsample_strides = value
@landmarks_per_face.setter
def landmarks_per_face(self, value):
assert isinstance(
value,
int), "The value to set `landmarks_per_face` must be type of int."
self._model.landmarks_per_face = value
@use_kps.setter
def use_kps(self, value):
assert isinstance(
value, bool), "The value to set `use_kps` must be type of bool."
self._model.use_kps = value
@max_nms.setter
def max_nms(self, value):
assert isinstance(
value, int), "The value to set `max_nms` must be type of int."
self._model.max_nms = value
@num_anchors.setter
def num_anchors(self, value):
assert isinstance(
value, int), "The value to set `num_anchors` must be type of int."
self._model.num_anchors = value

View File

@@ -0,0 +1,53 @@
# 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, Frontend
from .... import c_lib_wrap as C
class UltraFace(FastDeployModel):
def __init__(self,
model_file,
params_file="",
runtime_option=None,
model_format=Frontend.ONNX):
# 调用基函数进行backend_option的初始化
# 初始化后的option保存在self._runtime_option
super(UltraFace, self).__init__(runtime_option)
self._model = C.vision.facedet.UltraFace(
model_file, params_file, self._runtime_option, model_format)
# 通过self.initialized判断整个模型的初始化是否成功
assert self.initialized, "UltraFace initialize failed."
def predict(self, input_image, conf_threshold=0.7, nms_iou_threshold=0.3):
return self._model.predict(input_image, conf_threshold,
nms_iou_threshold)
# 一些跟UltraFace模型有关的属性封装
# 多数是预处理相关可通过修改如model.size = [640, 480]改变预处理时resize的大小前提是模型支持
@property
def size(self):
return self._model.size
@size.setter
def size(self, wh):
assert isinstance(wh, (list, tuple)),\
"The value to set `size` must be type of tuple or list."
assert len(wh) == 2,\
"The value to set `size` must contatins 2 elements means [width, height], but now it contains {} elements.".format(
len(wh))
self._model.size = wh

View File

@@ -0,0 +1,117 @@
# 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, Frontend
from .... import c_lib_wrap as C
class YOLOv5Face(FastDeployModel):
def __init__(self,
model_file,
params_file="",
runtime_option=None,
model_format=Frontend.ONNX):
# 调用基函数进行backend_option的初始化
# 初始化后的option保存在self._runtime_option
super(YOLOv5Face, self).__init__(runtime_option)
self._model = C.vision.facedet.YOLOv5Face(
model_file, params_file, self._runtime_option, model_format)
# 通过self.initialized判断整个模型的初始化是否成功
assert self.initialized, "YOLOv5Face initialize failed."
def predict(self, input_image, conf_threshold=0.25, nms_iou_threshold=0.5):
return self._model.predict(input_image, conf_threshold,
nms_iou_threshold)
# 一些跟YOLOv5Face模型有关的属性封装
# 多数是预处理相关可通过修改如model.size = [1280, 1280]改变预处理时resize的大小前提是模型支持
@property
def size(self):
return self._model.size
@property
def padding_value(self):
return self._model.padding_value
@property
def is_no_pad(self):
return self._model.is_no_pad
@property
def is_mini_pad(self):
return self._model.is_mini_pad
@property
def is_scale_up(self):
return self._model.is_scale_up
@property
def stride(self):
return self._model.stride
@property
def landmarks_per_face(self):
return self._model.landmarks_per_face
@size.setter
def size(self, wh):
assert isinstance(wh, (list, tuple)),\
"The value to set `size` must be type of tuple or list."
assert len(wh) == 2,\
"The value to set `size` must contatins 2 elements means [width, height], but now it contains {} elements.".format(
len(wh))
self._model.size = wh
@padding_value.setter
def padding_value(self, value):
assert isinstance(
value,
list), "The value to set `padding_value` must be type of list."
self._model.padding_value = value
@is_no_pad.setter
def is_no_pad(self, value):
assert isinstance(
value, bool), "The value to set `is_no_pad` must be type of bool."
self._model.is_no_pad = value
@is_mini_pad.setter
def is_mini_pad(self, value):
assert isinstance(
value,
bool), "The value to set `is_mini_pad` must be type of bool."
self._model.is_mini_pad = value
@is_scale_up.setter
def is_scale_up(self, value):
assert isinstance(
value,
bool), "The value to set `is_scale_up` must be type of bool."
self._model.is_scale_up = value
@stride.setter
def stride(self, value):
assert isinstance(
value, int), "The value to set `stride` must be type of int."
self._model.stride = value
@landmarks_per_face.setter
def landmarks_per_face(self, value):
assert isinstance(
value,
int), "The value to set `landmarks_per_face` must be type of int."
self._model.landmarks_per_face = value