正能量网站免费入口不用下载,网站建设与管理课件,网站资源做外链,建站城前言
想做一个目标旋转角度检测的工程#xff0c;但是网上多少python的#xff0c;或者linux的。在win10 visual 2022移植部署#xff0c;记录一下。 参考 这篇文章没有C win10 环境下的部署教程#xff0c;我相对于是对此做了补充。
1、下载工程
https://github.com/sh…前言
想做一个目标旋转角度检测的工程但是网上多少python的或者linux的。在win10 visual 2022移植部署记录一下。 参考 这篇文章没有C win10 环境下的部署教程我相对于是对此做了补充。
1、下载工程
https://github.com/shouxieai/tensorRT_Pro
2 模型导出
在 ultralytics/engine/exporter.py 文件中改动一处
# output_names [output0, output1] if isinstance(self.model, SegmentationModel) else [output0]
# dynamic self.args.dynamic
# if dynamic:
# dynamic {images: {0: batch, 2: height, 3: width}} # shape(1,3,640,640)
# if isinstance(self.model, SegmentationModel):
# dynamic[output0] {0: batch, 2: anchors} # shape(1, 116, 8400)
# dynamic[output1] {0: batch, 2: mask_height, 3: mask_width} # shape(1,32,160,160)
# elif isinstance(self.model, DetectionModel):
# dynamic[output0] {0: batch, 2: anchors} # shape(1, 84, 8400)
# exporter.py
output_names [output0, output1] if isinstance(self.model, SegmentationModel) else [output]
dynamic self.args.dynamic
if dynamic:dynamic {images: {0: batch}} # shape(1,3,640,640)if isinstance(self.model, SegmentationModel):dynamic[output0] {0: batch, 2: anchors} # shape(1, 116, 8400)dynamic[output1] {0: batch, 2: mask_height, 3: mask_width} # shape(1,32,160,160)elif isinstance(self.model, DetectionModel):dynamic[output] {0: batch} # shape(1, 84, 8400)在 ultralytics/nn/modules/head.py 文件中改动一处
def forward(self, x):Concatenates and returns predicted bounding boxes and class probabilities.bs x[0].shape[0] # batch sizeangle torch.cat([self.cv4[i](x[i]).view(bs, self.ne, -1) for i in range(self.nl)], 2) # OBB theta logits# NOTE: set angle as an attribute so that decode_bboxes could use it.angle (angle.sigmoid() - 0.25) * math.pi # [-pi/4, 3pi/4]# angle angle.sigmoid() * math.pi / 2 # [0, pi/2]if not self.training:self.angle anglex Detect.forward(self, x)if self.training:return x, angle#return torch.cat([x, angle], 1) if self.export else (torch.cat([x[0], angle], 1), (x[1], angle))return torch.cat([x, angle], 1).permute(0, 2, 1) if self.export else (torch.cat([x[0], angle], 1), (x[1], angle))在终端执行如下指令即可完成 onnx 导出
from ultralytics import YOLOmodel YOLO(yolov8_obb_zwc_0918.pt)success model.export(formatonnx, dynamicTrue, simplifyTrue)3 C
修改一个简单的测试测序在原工程app_yolo_obb.cpp 的基础上修改如下
#include trt_builder.hpp
#include trt_infer.hpp
#include ilogger.hpp
#include yolo_obb.hpp
static const char* dotalabels[] {0topleft, 1topright, 2downleft, 3downright, 4top,5right, 6down, 7left, bridge, large vehicle,small vehicle, helicopter, roundabout, soccer ball field, swimming pool
};
using namespace std;
static vectorcv::Point xywhr2xyxyxyxy(const YoloOBB::Box box) {float cos_value std::cos(box.angle);float sin_value std::sin(box.angle);float w_2 box.width / 2, h_2 box.height / 2;float vec1_x w_2 * cos_value, vec1_y w_2 * sin_value;float vec2_x -h_2 * sin_value, vec2_y h_2 * cos_value;vectorcv::Point corners;corners.push_back(cv::Point(box.center_x vec1_x vec2_x, box.center_y vec1_y vec2_y));corners.push_back(cv::Point(box.center_x vec1_x - vec2_x, box.center_y vec1_y - vec2_y));corners.push_back(cv::Point(box.center_x - vec1_x - vec2_x, box.center_y - vec1_y - vec2_y));corners.push_back(cv::Point(box.center_x - vec1_x vec2_x, box.center_y - vec1_y vec2_y));return corners;
}
static void test_single_image() {// //----initialauto engine YoloOBB::create_infer(E:***.trt, // engine file0, // gpu id0.25f, // confidence threshold0.45f, // nms thresholdYoloOBB::NMSMethod::FastGPU, // NMS method, fast GPU / CPU1024, // max objectsfalse // preprocess use multi stream);if (engine nullptr) {INFOE(Engine is nullptr);return;}//auto files iLogger::find_files(IMG, *.jpg;*.jpeg;*.png;*.gif;*.tif);vectorcv::Mat images;for (int i 0; i files.size(); i) {auto image cv::imread(files[i]);images.emplace_back(image);}//for (auto img : images)//{// cv::imshow(src, img);// cv::waitKey(0);//}for(auto img:images){cv::Mat imageimg ;if (image.empty()) {INFOE(Image is empty);return;}auto boxes engine-commit(image).get();for (auto obj : boxes) {uint8_t b, g, r;tie(b, g, r) iLogger::random_color(obj.class_label);auto corners xywhr2xyxyxyxy(obj);cv::polylines(image, vectorvectorcv::Point{corners}, true, cv::Scalar(b, g, r), 2, 16);auto name dotalabels[obj.class_label];auto caption iLogger::format(%s %.2f, name, obj.confidence);int width cv::getTextSize(caption, 0, 1, 2, nullptr).width 10;cv::rectangle(image, cv::Point(corners[0].x - 3, corners[0].y - 33), cv::Point(corners[0].x - 3 width, corners[0].y), cv::Scalar(b, g, r), -1);cv::putText(image, caption, cv::Point(corners[0].x - 3, corners[0].y - 5), 0, 1, cv::Scalar::all(0), 2, 16);}INFO(Save to Result.jpg, %d objects, boxes.size());cv::imwrite(Result.jpg, image);cv::imshow(result, image);cv::waitKey(0);}engine.reset();
}
int main() {test_single_image();return 0;
}3.1 工程下IMG 文件夹结构(你要测试的图片集合) 3.2 所需要的CPP 3.3 编译 添加头文件 3.3 .cu的文件需要设置CUDA C/C 编译类型 4 结果 5 PS
Cuda 、cudnn 、OpenCV,的配置可以自行百度or参考我的往期文章https://blog.csdn.net/qq_36784503/article/details/138597169
