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[Model] Refactor YOLOv7 module (#611)

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* 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

Co-authored-by: Jason <928090362@qq.com>
This commit is contained in:
WJJ1995
2022-11-18 10:52:02 +08:00
committed by GitHub
parent c19dcce77c
commit 8dd3e64227
20 changed files with 976 additions and 606 deletions
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19
fastdeploy/vision/detection/contrib/yolov5/preprocessor.cc
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@@ -24,7 +24,7 @@ YOLOv5Preprocessor::YOLOv5Preprocessor() {
padding_value_ = {114.0, 114.0, 114.0};
is_mini_pad_ = false;
is_no_pad_ = false;
is_scale_up_ = false;
is_scale_up_ = true;
stride_ = 32;
max_wh_ = 7680.0;
}
@@ -50,7 +50,9 @@ void YOLOv5Preprocessor::LetterBox(FDMat* mat) {
resize_h = size_[1];
resize_w = size_[0];
}
Resize::Run(mat, resize_w, resize_h);
if (std::fabs(scale - 1.0f) > 1e-06) {
Resize::Run(mat, resize_w, resize_h);
}
if (pad_h > 0 || pad_w > 0) {
float half_h = pad_h * 1.0 / 2;
int top = int(round(half_h - 0.1));
@@ -67,19 +69,6 @@ bool YOLOv5Preprocessor::Preprocess(FDMat* mat, FDTensor* output,
// Record the shape of image and the shape of preprocessed image
(*im_info)["input_shape"] = {static_cast<float>(mat->Height()),
static_cast<float>(mat->Width())};
// process after image load
double ratio = (size_[0] * 1.0) / std::max(static_cast<float>(mat->Height()),
static_cast<float>(mat->Width()));
if (std::fabs(ratio - 1.0f) > 1e-06) {
int interp = cv::INTER_AREA;
if (ratio > 1.0) {
interp = cv::INTER_LINEAR;
}
int resize_h = int(mat->Height() * ratio);
int resize_w = int(mat->Width() * ratio);
Resize::Run(mat, resize_w, resize_h, -1, -1, interp);
}
// yolov5's preprocess steps
// 1. letterbox
// 2. convert_and_permute(swap_rb=true)