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| // Tencent is pleased to support the open source community by making ncnn available. | |
| // | |
| // Copyright (C) 2018 THL A29 Limited, a Tencent company. All rights reserved. | |
| // | |
| // Licensed under the BSD 3-Clause License (the "License"); you may not use this file except | |
| // in compliance with the License. You may obtain a copy of the License at | |
| // | |
| // https://opensource.org/licenses/BSD-3-Clause | |
| // | |
| // 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. | |
| struct Object | |
| { | |
| cv::Rect_<float> rect; | |
| int label; | |
| float prob; | |
| }; | |
| static int detect_yolov3(const cv::Mat& bgr, std::vector<Object>& objects) | |
| { | |
| ncnn::Net yolov3; | |
| yolov3.opt.use_vulkan_compute = true; | |
| // original pretrained model from https://github.com/eric612/MobileNet-YOLO | |
| // param : https://drive.google.com/open?id=1V9oKHP6G6XvXZqhZbzNKL6FI_clRWdC- | |
| // bin : https://drive.google.com/open?id=1DBcuFCr-856z3FRQznWL_S5h-Aj3RawA | |
| // the ncnn model https://github.com/nihui/ncnn-assets/tree/master/models | |
| if (yolov3.load_param("mobilenetv2_yolov3.param")) | |
| exit(-1); | |
| if (yolov3.load_model("mobilenetv2_yolov3.bin")) | |
| exit(-1); | |
| const int target_size = 352; | |
| int img_w = bgr.cols; | |
| int img_h = bgr.rows; | |
| ncnn::Mat in = ncnn::Mat::from_pixels_resize(bgr.data, ncnn::Mat::PIXEL_BGR, bgr.cols, bgr.rows, target_size, target_size); | |
| const float mean_vals[3] = {127.5f, 127.5f, 127.5f}; | |
| const float norm_vals[3] = {0.007843f, 0.007843f, 0.007843f}; | |
| in.substract_mean_normalize(mean_vals, norm_vals); | |
| ncnn::Extractor ex = yolov3.create_extractor(); | |
| ex.input("data", in); | |
| ncnn::Mat out; | |
| ex.extract("detection_out", out); | |
| // printf("%d %d %d\n", out.w, out.h, out.c); | |
| objects.clear(); | |
| for (int i = 0; i < out.h; i++) | |
| { | |
| const float* values = out.row(i); | |
| Object object; | |
| object.label = values[0]; | |
| object.prob = values[1]; | |
| object.rect.x = values[2] * img_w; | |
| object.rect.y = values[3] * img_h; | |
| object.rect.width = values[4] * img_w - object.rect.x; | |
| object.rect.height = values[5] * img_h - object.rect.y; | |
| objects.push_back(object); | |
| } | |
| return 0; | |
| } | |
| static void draw_objects(const cv::Mat& bgr, const std::vector<Object>& objects) | |
| { | |
| static const char* class_names[] = {"background", | |
| "aeroplane", "bicycle", "bird", "boat", | |
| "bottle", "bus", "car", "cat", "chair", | |
| "cow", "diningtable", "dog", "horse", | |
| "motorbike", "person", "pottedplant", | |
| "sheep", "sofa", "train", "tvmonitor" | |
| }; | |
| cv::Mat image = bgr.clone(); | |
| for (size_t i = 0; i < objects.size(); i++) | |
| { | |
| const Object& obj = objects[i]; | |
| fprintf(stderr, "%d = %.5f at %.2f %.2f %.2f x %.2f\n", obj.label, obj.prob, | |
| obj.rect.x, obj.rect.y, obj.rect.width, obj.rect.height); | |
| cv::rectangle(image, obj.rect, cv::Scalar(255, 0, 0)); | |
| char text[256]; | |
| sprintf(text, "%s %.1f%%", class_names[obj.label], obj.prob * 100); | |
| int baseLine = 0; | |
| cv::Size label_size = cv::getTextSize(text, cv::FONT_HERSHEY_SIMPLEX, 0.5, 1, &baseLine); | |
| int x = obj.rect.x; | |
| int y = obj.rect.y - label_size.height - baseLine; | |
| if (y < 0) | |
| y = 0; | |
| if (x + label_size.width > image.cols) | |
| x = image.cols - label_size.width; | |
| cv::rectangle(image, cv::Rect(cv::Point(x, y), cv::Size(label_size.width, label_size.height + baseLine)), | |
| cv::Scalar(255, 255, 255), -1); | |
| cv::putText(image, text, cv::Point(x, y + label_size.height), | |
| cv::FONT_HERSHEY_SIMPLEX, 0.5, cv::Scalar(0, 0, 0)); | |
| } | |
| cv::imshow("image", image); | |
| cv::waitKey(0); | |
| } | |
| int main(int argc, char** argv) | |
| { | |
| if (argc != 2) | |
| { | |
| fprintf(stderr, "Usage: %s [imagepath]\n", argv[0]); | |
| return -1; | |
| } | |
| const char* imagepath = argv[1]; | |
| cv::Mat m = cv::imread(imagepath, 1); | |
| if (m.empty()) | |
| { | |
| fprintf(stderr, "cv::imread %s failed\n", imagepath); | |
| return -1; | |
| } | |
| std::vector<Object> objects; | |
| detect_yolov3(m, objects); | |
| draw_objects(m, objects); | |
| return 0; | |
| } | |