├── LICENSE ├── README.md ├── images ├── bus.jpg └── zidane.jpg ├── main.cpp ├── models └── put_model_here ├── yolo.cpp └── yolo.h /LICENSE: -------------------------------------------------------------------------------- 1 | Apache License 2 | Version 2.0, January 2004 3 | http://www.apache.org/licenses/ 4 | 5 | TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION 6 | 7 | 1. Definitions. 8 | 9 | "License" shall mean the terms and conditions for use, reproduction, 10 | and distribution as defined by Sections 1 through 9 of this document. 11 | 12 | "Licensor" shall mean the copyright owner or entity authorized by 13 | the copyright owner that is granting the License. 14 | 15 | "Legal Entity" shall mean the union of the acting entity and all 16 | other entities that control, are controlled by, or are under common 17 | control with that entity. For the purposes of this definition, 18 | "control" means (i) the power, direct or indirect, to cause the 19 | direction or management of such entity, whether by contract or 20 | otherwise, or (ii) ownership of fifty percent (50%) or more of the 21 | outstanding shares, or (iii) beneficial ownership of such entity. 22 | 23 | "You" (or "Your") shall mean an individual or Legal Entity 24 | exercising permissions granted by this License. 25 | 26 | "Source" form shall mean the preferred form for making modifications, 27 | including but not limited to software source code, documentation 28 | source, and configuration files. 29 | 30 | "Object" form shall mean any form resulting from mechanical 31 | transformation or translation of a Source form, including but 32 | not limited to compiled object code, generated documentation, 33 | and conversions to other media types. 34 | 35 | "Work" shall mean the work of authorship, whether in Source or 36 | Object form, made available under the License, as indicated by a 37 | copyright notice that is included in or attached to the work 38 | (an example is provided in the Appendix below). 39 | 40 | "Derivative Works" shall mean any work, whether in Source or Object 41 | form, that is based on (or derived from) the Work and for which the 42 | editorial revisions, annotations, elaborations, or other modifications 43 | represent, as a whole, an original work of authorship. For the purposes 44 | of this License, Derivative Works shall not include works that remain 45 | separable from, or merely link (or bind by name) to the interfaces of, 46 | the Work and Derivative Works thereof. 47 | 48 | "Contribution" shall mean any work of authorship, including 49 | the original version of the Work and any modifications or additions 50 | to that Work or Derivative Works thereof, that is intentionally 51 | submitted to Licensor for inclusion in the Work by the copyright owner 52 | or by an individual or Legal Entity authorized to submit on behalf of 53 | the copyright owner. For the purposes of this definition, "submitted" 54 | means any form of electronic, verbal, or written communication sent 55 | to the Licensor or its representatives, including but not limited to 56 | communication on electronic mailing lists, source code control systems, 57 | and issue tracking systems that are managed by, or on behalf of, the 58 | Licensor for the purpose of discussing and improving the Work, but 59 | excluding communication that is conspicuously marked or otherwise 60 | designated in writing by the copyright owner as "Not a Contribution." 61 | 62 | "Contributor" shall mean Licensor and any individual or Legal Entity 63 | on behalf of whom a Contribution has been received by Licensor and 64 | subsequently incorporated within the Work. 65 | 66 | 2. Grant of Copyright License. Subject to the terms and conditions of 67 | this License, each Contributor hereby grants to You a perpetual, 68 | worldwide, non-exclusive, no-charge, royalty-free, irrevocable 69 | copyright license to reproduce, prepare Derivative Works of, 70 | publicly display, publicly perform, sublicense, and distribute the 71 | Work and such Derivative Works in Source or Object form. 72 | 73 | 3. Grant of Patent License. Subject to the terms and conditions of 74 | this License, each Contributor hereby grants to You a perpetual, 75 | worldwide, non-exclusive, no-charge, royalty-free, irrevocable 76 | (except as stated in this section) patent license to make, have made, 77 | use, offer to sell, sell, import, and otherwise transfer the Work, 78 | where such license applies only to those patent claims licensable 79 | by such Contributor that are necessarily infringed by their 80 | Contribution(s) alone or by combination of their Contribution(s) 81 | with the Work to which such Contribution(s) was submitted. If You 82 | institute patent litigation against any entity (including a 83 | cross-claim or counterclaim in a lawsuit) alleging that the Work 84 | or a Contribution incorporated within the Work constitutes direct 85 | or contributory patent infringement, then any patent licenses 86 | granted to You under this License for that Work shall terminate 87 | as of the date such litigation is filed. 88 | 89 | 4. Redistribution. You may reproduce and distribute copies of the 90 | Work or Derivative Works thereof in any medium, with or without 91 | modifications, and in Source or Object form, provided that You 92 | meet the following conditions: 93 | 94 | (a) You must give any other recipients of the Work or 95 | Derivative Works a copy of this License; and 96 | 97 | (b) You must cause any modified files to carry prominent notices 98 | stating that You changed the files; and 99 | 100 | (c) You must retain, in the Source form of any Derivative Works 101 | that You distribute, all copyright, patent, trademark, and 102 | attribution notices from the Source form of the Work, 103 | excluding those notices that do not pertain to any part of 104 | the Derivative Works; and 105 | 106 | (d) If the Work includes a "NOTICE" text file as part of its 107 | distribution, then any Derivative Works that You distribute must 108 | include a readable copy of the attribution notices contained 109 | within such NOTICE file, excluding those notices that do not 110 | pertain to any part of the Derivative Works, in at least one 111 | of the following places: within a NOTICE text file distributed 112 | as part of the Derivative Works; within the Source form or 113 | documentation, if provided along with the Derivative Works; or, 114 | within a display generated by the Derivative Works, if and 115 | wherever such third-party notices normally appear. The contents 116 | of the NOTICE file are for informational purposes only and 117 | do not modify the License. You may add Your own attribution 118 | notices within Derivative Works that You distribute, alongside 119 | or as an addendum to the NOTICE text from the Work, provided 120 | that such additional attribution notices cannot be construed 121 | as modifying the License. 122 | 123 | You may add Your own copyright statement to Your modifications and 124 | may provide additional or different license terms and conditions 125 | for use, reproduction, or distribution of Your modifications, or 126 | for any such Derivative Works as a whole, provided Your use, 127 | reproduction, and distribution of the Work otherwise complies with 128 | the conditions stated in this License. 129 | 130 | 5. Submission of Contributions. Unless You explicitly state otherwise, 131 | any Contribution intentionally submitted for inclusion in the Work 132 | by You to the Licensor shall be under the terms and conditions of 133 | this License, without any additional terms or conditions. 134 | Notwithstanding the above, nothing herein shall supersede or modify 135 | the terms of any separate license agreement you may have executed 136 | with Licensor regarding such Contributions. 137 | 138 | 6. Trademarks. This License does not grant permission to use the trade 139 | names, trademarks, service marks, or product names of the Licensor, 140 | except as required for reasonable and customary use in describing the 141 | origin of the Work and reproducing the content of the NOTICE file. 142 | 143 | 7. Disclaimer of Warranty. Unless required by applicable law or 144 | agreed to in writing, Licensor provides the Work (and each 145 | Contributor provides its Contributions) on an "AS IS" BASIS, 146 | WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or 147 | implied, including, without limitation, any warranties or conditions 148 | of TITLE, NON-INFRINGEMENT, MERCHANTABILITY, or FITNESS FOR A 149 | PARTICULAR PURPOSE. You are solely responsible for determining the 150 | appropriateness of using or redistributing the Work and assume any 151 | risks associated with Your exercise of permissions under this License. 152 | 153 | 8. Limitation of Liability. In no event and under no legal theory, 154 | whether in tort (including negligence), contract, or otherwise, 155 | unless required by applicable law (such as deliberate and grossly 156 | negligent acts) or agreed to in writing, shall any Contributor be 157 | liable to You for damages, including any direct, indirect, special, 158 | incidental, or consequential damages of any character arising as a 159 | result of this License or out of the use or inability to use the 160 | Work (including but not limited to damages for loss of goodwill, 161 | work stoppage, computer failure or malfunction, or any and all 162 | other commercial damages or losses), even if such Contributor 163 | has been advised of the possibility of such damages. 164 | 165 | 9. Accepting Warranty or Additional Liability. While redistributing 166 | the Work or Derivative Works thereof, You may choose to offer, 167 | and charge a fee for, acceptance of support, warranty, indemnity, 168 | or other liability obligations and/or rights consistent with this 169 | License. However, in accepting such obligations, You may act only 170 | on Your own behalf and on Your sole responsibility, not on behalf 171 | of any other Contributor, and only if You agree to indemnify, 172 | defend, and hold each Contributor harmless for any liability 173 | incurred by, or claims asserted against, such Contributor by reason 174 | of your accepting any such warranty or additional liability. 175 | 176 | END OF TERMS AND CONDITIONS 177 | 178 | APPENDIX: How to apply the Apache License to your work. 179 | 180 | To apply the Apache License to your work, attach the following 181 | boilerplate notice, with the fields enclosed by brackets "[]" 182 | replaced with your own identifying information. (Don't include 183 | the brackets!) The text should be enclosed in the appropriate 184 | comment syntax for the file format. We also recommend that a 185 | file or class name and description of purpose be included on the 186 | same "printed page" as the copyright notice for easier 187 | identification within third-party archives. 188 | 189 | Copyright [yyyy] [name of copyright owner] 190 | 191 | Licensed under the Apache License, Version 2.0 (the "License"); 192 | you may not use this file except in compliance with the License. 193 | You may obtain a copy of the License at 194 | 195 | http://www.apache.org/licenses/LICENSE-2.0 196 | 197 | Unless required by applicable law or agreed to in writing, software 198 | distributed under the License is distributed on an "AS IS" BASIS, 199 | WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 200 | See the License for the specific language governing permissions and 201 | limitations under the License. 202 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # yolov5-opencv-dnn-cpp 2 | 使用opencv模块部署yolov5-6.0版本 3 | 基于6.0版本的yolov5:https://github.com/ultralytics/yolov5 4 | 5 | ## The Yolov5 code has been merged into https://github.com/UNeedCryDear/yolov5-seg-opencv-onnxruntime-cpp, and the repository will no longer be updated. 6 | 7 | **OpenCV>=4.5.0** 8 | 9 | + 导出onnx模型需要将opset设置成12（原来默认的是13，在opencv下面会报错，原因未知）
10 | + 如果是torch1.12.x的版本,需要在 11 | https://github.com/ultralytics/yolov5/blob/c98128fe71a8676037a0605ab389c7473c743d07/export.py#L155 12 | 这里的```do_constant_folding=False```,设置为false才行，否者读取网络会失败，原因未知。
13 | ``` 14 | $ python path/to/export.py --weights yolov5s.pt --img [640,640] --opset 12 --include onnx 15 | ``` 16 | #### 2023.02.19 更新： 17 | + 旧代码已经是两年之前的了，之前为了适应yolov5-5.0的版本，后处理部分留下太多繁琐的操作，包括像计算anchors，需要设置对应的stride等等。本次更新将会优化这部分内容，同时加上预处理部分的LetterBox(),与python下的源码保持一致性的预处理方式。 18 | 19 | #### 2022.12.13 更新： 20 | + 如果你的显卡支持FP16推理的话，可以将模型读取代码中的```DNN_TARGET_CUDA```改成```DNN_TARGET_CUDA_FP16```提升推理速度（虽然是蚊子腿，好歹也是肉（： 21 | #### 2022.03.29 更新： 22 | 23 | + 新增P6模型支持，可以通过yolo.h中定义的YOLO_P6切换 24 | 25 | + 另外关于换行符，windows下面需要设置为CRLF，上传到github会自动切换成LF，windows下面切换一下即可 26 | 27 | 以下图片为更新p6模型之后yolov5s6.onnx运行结果： 28 | ![zidane](https://user-images.githubusercontent.com/52729998/160559827-45572f7e-54e8-4653-b9be-6d287912b065.jpg) 29 | 30 | ![bus](https://user-images.githubusercontent.com/52729998/160559831-3ddf926d-b7c3-4687-bd57-26dd4d1cc055.jpg) 31 | -------------------------------------------------------------------------------- /images/bus.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/UNeedCryDear/yolov5-opencv-dnn-cpp/084f7b941fa6be2828b906a22b4ae526ed2113ee/images/bus.jpg -------------------------------------------------------------------------------- /images/zidane.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/UNeedCryDear/yolov5-opencv-dnn-cpp/084f7b941fa6be2828b906a22b4ae526ed2113ee/images/zidane.jpg -------------------------------------------------------------------------------- /main.cpp: -------------------------------------------------------------------------------- 1 | 2 | #include "yolo.h" 3 | #include 4 | #include 5 | #include 6 | 7 | using namespace std; 8 | using namespace cv; 9 | using namespace dnn; 10 | 11 | int main() 12 | { 13 | string img_path = "./images/bus.jpg"; 14 | string model_path = "./models/yolov5s.onnx"; 15 | //int num_devices = cv::cuda::getCudaEnabledDeviceCount(); 16 | //if (num_devices <= 0) { 17 | //cerr << "There is no cuda." << endl; 18 | //return -1; 19 | //} 20 | //else { 21 | //cout << num_devices << endl; 22 | //} 23 | 24 | Yolov5 test; 25 | Net net; 26 | if (test.readModel(net, model_path, false)) { 27 | cout << "read net ok!" << endl; 28 | } 29 | else { 30 | return -1; 31 | } 32 | 33 | //生成随机颜色 34 | vector color; 35 | srand(time(0)); 36 | for (int i = 0; i < 80; i++) { 37 | int b = rand() % 256; 38 | int g = rand() % 256; 39 | int r = rand() % 256; 40 | color.push_back(Scalar(b, g, r)); 41 | } 42 | vector result; 43 | Mat img = imread(img_path); 44 | 45 | if (test.Detect(img, net, result)) { 46 | test.drawPred(img, result, color); 47 | 48 | } 49 | else { 50 | cout << "Detect Failed!"<& output) { 95 | Mat blob; 96 | int col = SrcImg.cols; 97 | int row = SrcImg.rows; 98 | int maxLen = MAX(col, row); 99 | Mat netInputImg = SrcImg.clone(); 100 | Vec4d params; 101 | LetterBox(SrcImg, netInputImg, params, cv::Size(_netWidth, _netHeight)); 102 | 103 | blobFromImage(netInputImg, blob, 1 / 255.0, cv::Size(_netWidth, _netHeight), cv::Scalar(0, 0, 0), true, false); 104 | //如果在其他设置没有问题的情况下但是结果偏差很大，可以尝试下用下面两句语句 105 | //blobFromImage(netInputImg, blob, 1 / 255.0, cv::Size(_netWidth, _netHeight), cv::Scalar(104, 117, 123), true, false); 106 | //blobFromImage(netInputImg, blob, 1 / 255.0, cv::Size(_netWidth, _netHeight), cv::Scalar(114, 114,114), true, false); 107 | net.setInput(blob); 108 | std::vector netOutputImg; 109 | //vector outputLayerName{"345","403", "461","output" }; 110 | //net.forward(netOutputImg, outputLayerName[3]); //获取output的输出 111 | net.forward(netOutputImg, net.getUnconnectedOutLayersNames()); 112 | std::vector classIds;//结果id数组 113 | std::vector confidences;//结果每个id对应置信度数组 114 | std::vector boxes;//每个id矩形框 115 | int net_width = _className.size() + 5; //输出的网络宽度是类别数+5 116 | int net_out_width = netOutputImg[0].size[2]; 117 | assert(net_out_width == net_width, "Error Wrong number of _className"); //模型类别数目不对 118 | float* pdata = (float*)netOutputImg[0].data; 119 | int net_height = netOutputImg[0].size[1]; 120 | for (int r = 0; r < net_height; ++r) { 121 | float box_score = pdata[4]; ;//获取每一行的box框中含有某个物体的概率 122 | if (box_score >= _classThreshold) { 123 | cv::Mat scores(1, _className.size(), CV_32FC1, pdata + 5); 124 | Point classIdPoint; 125 | double max_class_socre; 126 | minMaxLoc(scores, 0, &max_class_socre, 0, &classIdPoint); 127 | max_class_socre = max_class_socre* box_score; 128 | if (max_class_socre >= _classThreshold) { 129 | //rect [x,y,w,h] 130 | float x = (pdata[0] - params[2]) / params[0]; 131 | float y = (pdata[1] - params[3]) / params[1]; 132 | float w = pdata[2] / params[0]; 133 | float h = pdata[3] / params[1]; 134 | int left = MAX(round(x - 0.5 * w +0.5), 0); 135 | int top = MAX(round(y - 0.5 * h+0.5 ), 0); 136 | classIds.push_back(classIdPoint.x); 137 | confidences.push_back(max_class_socre ); 138 | boxes.push_back(Rect(left, top, int(w + 0.5), int(h + 0.5))); 139 | } 140 | } 141 | pdata += net_width;//下一行 142 | 143 | } 144 | 145 | //执行非最大抑制以消除具有较低置信度的冗余重叠框（NMS） 146 | vector nms_result; 147 | NMSBoxes(boxes, confidences, _classThreshold, _nmsThreshold, nms_result); 148 | for (int i = 0; i < nms_result.size(); i++) { 149 | int idx = nms_result[i]; 150 | Output result; 151 | result.id = classIds[idx]; 152 | result.confidence = confidences[idx]; 153 | result.box = boxes[idx]; 154 | output.push_back(result); 155 | } 156 | if (output.size()) 157 | return true; 158 | else 159 | return false; 160 | } 161 | 162 | void Yolov5::drawPred(Mat& img, vector result, vector color) { 163 | for (int i = 0; i < result.size(); i++) { 164 | int left, top; 165 | left = result[i].box.x; 166 | top = result[i].box.y; 167 | int color_num = i; 168 | rectangle(img, result[i].box, color[result[i].id], 2, 8); 169 | 170 | string label = _className[result[i].id] + ":" + to_string(result[i].confidence); 171 | 172 | int baseLine; 173 | Size labelSize = getTextSize(label, FONT_HERSHEY_SIMPLEX, 0.5, 1, &baseLine); 174 | top = max(top, labelSize.height); 175 | //rectangle(frame, Point(left, top - int(1.5 * labelSize.height)), Point(left + int(1.5 * labelSize.width), top + baseLine), Scalar(0, 255, 0), FILLED); 176 | putText(img, label, Point(left, top), FONT_HERSHEY_SIMPLEX, 1, color[result[i].id], 2); 177 | } 178 | imshow("1", img); 179 | //imwrite("out.bmp", img); 180 | waitKey(); 181 | //destroyAllWindows(); 182 | 183 | } 184 | -------------------------------------------------------------------------------- /yolo.h: -------------------------------------------------------------------------------- 1 | #pragma once 2 | #include 3 | #include 4 | 5 | #define YOLO_P6 false //是否使用P6模型 6 | 7 | struct Output { 8 | int id; //结果类别id 9 | float confidence; //结果置信度 10 | cv::Rect box; //矩形框 11 | }; 12 | 13 | class Yolov5 { 14 | public: 15 | Yolov5() { 16 | } 17 | ~Yolov5() {} 18 | bool readModel(cv::dnn::Net& net, std::string& netPath, bool isCuda); 19 | bool Detect(cv::Mat& SrcImg, cv::dnn::Net& net, std::vector& output); 20 | void drawPred(cv::Mat& img, std::vector result, std::vector color); 21 | 22 | private: 23 | 24 | void LetterBox(const cv::Mat& image, cv::Mat& outImage, 25 | cv::Vec4d& params, //[ratio_x,ratio_y,dw,dh] 26 | const cv::Size& newShape = cv::Size(640, 640), 27 | bool autoShape = false, 28 | bool scaleFill = false, 29 | bool scaleUp = true, 30 | int stride = 32, 31 | const cv::Scalar& color = cv::Scalar(114, 114, 114)); 32 | 33 | #if(defined YOLO_P6 && YOLO_P6==true) 34 | const int _netWidth = 1280; //ONNX图片输入宽度 35 | const int _netHeight = 1280; //ONNX图片输入高度 36 | #else 37 | 38 | const int _netWidth = 640; //ONNX图片输入宽度 39 | const int _netHeight = 640; //ONNX图片输入高度 40 | #endif // YOLO_P6 41 | 42 | float _classThreshold = 0.25; 43 | float _nmsThreshold = 0.45; 44 | public: 45 | std::vector _className = { "person", "bicycle", "car", "motorcycle", "airplane", "bus", "train", "truck", "boat", "traffic light", 46 | "fire hydrant", "stop sign", "parking meter", "bench", "bird", "cat", "dog", "horse", "sheep", "cow", 47 | "elephant", "bear", "zebra", "giraffe", "backpack", "umbrella", "handbag", "tie", "suitcase", "frisbee", 48 | "skis", "snowboard", "sports ball", "kite", "baseball bat", "baseball glove", "skateboard", "surfboard", 49 | "tennis racket", "bottle", "wine glass", "cup", "fork", "knife", "spoon", "bowl", "banana", "apple", 50 | "sandwich", "orange", "broccoli", "carrot", "hot dog", "pizza", "donut", "cake", "chair", "couch", 51 | "potted plant", "bed", "dining table", "toilet", "tv", "laptop", "mouse", "remote", "keyboard", "cell phone", 52 | "microwave", "oven", "toaster", "sink", "refrigerator", "book", "clock", "vase", "scissors", "teddy bear", 53 | "hair drier", "toothbrush" }; 54 | }; 55 | --------------------------------------------------------------------------------