[Model] Add FSANet model (#448)

* add yolov5cls

* fixed bugs

* fixed bugs

* fixed preprocess bug

* add yolov5cls readme

* deal with comments

* Add YOLOv5Cls Note

* add yolov5cls test

* add rvm support

* support rvm model

* add rvm demo

* fixed bugs

* add rvm readme

* add TRT support

* add trt support

* add rvm test

* add EXPORT.md

* rename export.md

* rm poros doxyen

* deal with comments

* deal with comments

* add rvm video_mode note

* add fsanet

* fixed bug

* update readme

* fixed for ci

* deal with comments

* deal with comments

* deal with comments

Co-authored-by: Jason <jiangjiajun@baidu.com>
Co-authored-by: DefTruth <31974251+DefTruth@users.noreply.github.com>
This commit is contained in:
WJJ1995
2022-11-04 11:00:35 +08:00
committed by GitHub
parent ce828ecb38
commit 7150e6405c
31 changed files with 922 additions and 22 deletions

1
python/fastdeploy/vision/__init__.py Normal file → Executable file
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@@ -23,6 +23,7 @@ from . import facedet
from . import facealign
from . import faceid
from . import ocr
from . import headpose
from . import evaluation
from .utils import fd_result_to_json
from .visualize import *

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@@ -0,0 +1,16 @@
# 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 .contrib.fsanet import FSANet

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@@ -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

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@@ -0,0 +1,68 @@
# 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 FSANet(FastDeployModel):
def __init__(self,
model_file,
params_file="",
runtime_option=None,
model_format=ModelFormat.ONNX):
"""Load a headpose model exported by FSANet.
:param model_file: (str)Path of model file, e.g fsanet/fsanet-var.onnx
:param params_file: (str)Path of parameters file, 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, default is ONNX
"""
super(FSANet, self).__init__(runtime_option)
assert model_format == ModelFormat.ONNX, "FSANet only support model format of ModelFormat.ONNX now."
self._model = C.vision.headpose.FSANet(
model_file, params_file, self._runtime_option, model_format)
assert self.initialized, "FSANet initialize failed."
def predict(self, input_image):
"""Predict an input image headpose
:param im: (numpy.ndarray)The input image data, 3-D array with layout HWC, BGR format
:return: HeadPoseResult
"""
return self._model.predict(input_image)
@property
def size(self):
"""
Returns the preprocess image size, default (64, 64)
"""
return self._model.size
@size.setter
def size(self, wh):
"""
Set the preprocess image size, default (64, 64)
"""
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

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@@ -109,3 +109,7 @@ def vis_ppocr(im_data, det_result):
def vis_mot(im_data, mot_result, score_threshold=0.0, records=None):
return C.vision.vis_mot(im_data, mot_result, score_threshold, records)
def vis_headpose(im_data, headpose_result, size=50, line_size=1):
return C.vision.vis_headpose(im_data, headpose_result, size, line_size)