[Model] Optimizer RVM Postprocess (#679)

* add paddle_trt in benchmark

* update benchmark in device

* update benchmark

* update result doc

* fixed for CI

* update python api_docs

* update index.rst

* add runtime cpp examples

* deal with comments

* Update infer_paddle_tensorrt.py

* Add runtime quick start

* deal with comments

* fixed reused_input_tensors&&reused_output_tensors

* fixed docs

* fixed headpose typo

* fixed typo

* refactor yolov5

* update model infer

* refactor pybind for yolov5

* rm origin yolov5

* fixed bugs

* rm cuda preprocess

* fixed bugs

* fixed bugs

* fixed bug

* fixed bug

* fix pybind

* rm useless code

* add convert_and_permute

* fixed bugs

* fixed im_info for bs_predict

* fixed bug

* add bs_predict for yolov5

* Add runtime test and batch eval

* deal with comments

* fixed bug

* update testcase

* fixed batch eval bug

* fixed preprocess bug

* refactor yolov7

* add yolov7 testcase

* rm resize_after_load and add is_scale_up

* fixed bug

* set multi_label true

* optimize rvm preprocess

* optimizer rvm postprocess

* fixed bug

* deal with comments

Co-authored-by: Jason <928090362@qq.com>
Co-authored-by: Jason <jiangjiajun@baidu.com>
This commit is contained in:
WJJ1995
2022-11-25 13:17:09 +08:00
committed by GitHub
parent 124f9f8115
commit 1da8c523b0
6 changed files with 25 additions and 3 deletions

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@@ -47,6 +47,8 @@ bool RobustVideoMatting::Initialize() {
video_mode = true; video_mode = true;
swap_rb = true;
if (!InitRuntime()) { if (!InitRuntime()) {
FDERROR << "Failed to initialize fastdeploy backend." << std::endl; FDERROR << "Failed to initialize fastdeploy backend." << std::endl;
return false; return false;
@@ -66,7 +68,7 @@ bool RobustVideoMatting::Preprocess(
// Convert_and_permute(swap_rb=true) // Convert_and_permute(swap_rb=true)
std::vector<float> alpha = {1.0f / 255.0f, 1.0f / 255.0f, 1.0f / 255.0f}; std::vector<float> alpha = {1.0f / 255.0f, 1.0f / 255.0f, 1.0f / 255.0f};
std::vector<float> beta = {0.0f, 0.0f, 0.0f}; std::vector<float> beta = {0.0f, 0.0f, 0.0f};
ConvertAndPermute::Run(mat, alpha, beta, true); ConvertAndPermute::Run(mat, alpha, beta, swap_rb);
// Record output shape of preprocessed image // Record output shape of preprocessed image
(*im_info)["output_shape"] = {mat->Height(), mat->Width()}; (*im_info)["output_shape"] = {mat->Height(), mat->Width()};
@@ -130,7 +132,6 @@ bool RobustVideoMatting::Postprocess(
Resize::Run(&fgr_resized, in_w, in_h, -1, -1); Resize::Run(&fgr_resized, in_w, in_h, -1, -1);
} }
result->Clear();
result->contain_foreground = true; result->contain_foreground = true;
// if contain_foreground == true, shape must set to (h, w, c) // if contain_foreground == true, shape must set to (h, w, c)
result->shape = {static_cast<int64_t>(in_h), static_cast<int64_t>(in_w), 3}; result->shape = {static_cast<int64_t>(in_h), static_cast<int64_t>(in_w), 3};

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@@ -58,6 +58,9 @@ class FASTDEPLOY_DECL RobustVideoMatting : public FastDeployModel {
/// Whether to open the video mode, if there are some irrelevant pictures, set it to fasle, the default is true // NOLINT /// Whether to open the video mode, if there are some irrelevant pictures, set it to fasle, the default is true // NOLINT
bool video_mode; bool video_mode;
/// Whether convert to RGB, Set to false if you have converted YUV format images to RGB outside the model, dafault true // NOLINT
bool swap_rb;
private: private:
bool Initialize(); bool Initialize();
/// Preprocess an input image, and set the preprocessed results to `outputs` /// Preprocess an input image, and set the preprocessed results to `outputs`

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@@ -28,7 +28,8 @@ void BindRobustVideoMatting(pybind11::module& m) {
return res; return res;
}) })
.def_readwrite("size", &vision::matting::RobustVideoMatting::size) .def_readwrite("size", &vision::matting::RobustVideoMatting::size)
.def_readwrite("video_mode", &vision::matting::RobustVideoMatting::video_mode); .def_readwrite("video_mode", &vision::matting::RobustVideoMatting::video_mode)
.def_readwrite("swap_rb", &vision::matting::RobustVideoMatting::swap_rb);
} }
} // namespace fastdeploy } // namespace fastdeploy

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@@ -59,6 +59,13 @@ class RobustVideoMatting(FastDeployModel):
""" """
return self._model.video_mode return self._model.video_mode
@property
def swap_rb(self):
"""
Whether convert to RGB, Set to false if you have converted YUV format images to RGB outside the model, dafault true
"""
return self._model.swap_rb
@size.setter @size.setter
def size(self, wh): def size(self, wh):
""" """
@@ -79,3 +86,12 @@ class RobustVideoMatting(FastDeployModel):
assert isinstance( assert isinstance(
value, bool), "The value to set `video_mode` must be type of bool." value, bool), "The value to set `video_mode` must be type of bool."
self._model.video_mode = value self._model.video_mode = value
@swap_rb.setter
def swap_rb(self, value):
"""
Set swap_rb property, the default is true
"""
assert isinstance(
value, bool), "The value to set `swap_rb` must be type of bool."
self._model.swap_rb = value

1
tests/models/test_rvm.py Normal file → Executable file
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@@ -27,6 +27,7 @@ def test_matting_rvm_cpu():
fd.download(input_url, "resources") fd.download(input_url, "resources")
model_path = "resources/rvm/rvm_mobilenetv3_fp32.onnx" model_path = "resources/rvm/rvm_mobilenetv3_fp32.onnx"
# use ORT # use ORT
rc.test_option.use_ort_backend()
model = fd.vision.matting.RobustVideoMatting( model = fd.vision.matting.RobustVideoMatting(
model_path, runtime_option=rc.test_option) model_path, runtime_option=rc.test_option)