From e68b36f570727cd3df5fc13eeb0552c5a7accc9e Mon Sep 17 00:00:00 2001 From: yiicy Date: Mon, 24 Feb 2020 23:26:48 +0800 Subject: [PATCH] [DEMO] update mask detection demo, test=develop (#2988) update mask detection demo --- lite/demo/cxx/README.md | 6 +- .../demo/cxx/mask_detection/mask_detection.cc | 101 ++++++++++++++---- 2 files changed, 83 insertions(+), 24 deletions(-) diff --git a/lite/demo/cxx/README.md b/lite/demo/cxx/README.md index 6fb0a11c2e..212f68b928 100644 --- a/lite/demo/cxx/README.md +++ b/lite/demo/cxx/README.md @@ -70,7 +70,11 @@ export LD_LIBRARY_PATH=/data/local/tmp/:$LD_LIBRARY_PATH adb pull /data/local/tmp/test_mask_detection_result.jpg ./ ``` -![test_mask_detection_result](https://user-images.githubusercontent.com/7383104/74279176-6200cd00-4d55-11ea-9fc0-83cfc2b3b37d.jpg) +![test_mask_detection_result](https://user-images.githubusercontent.com/7383104/75131866-bae64300-570f-11ea-9cad-17acfaea1cfc.jpg) + +注：mask_detetion.cc 中的缩放因子shrink, 检测阈值detect_threshold, 可供自由配置: + - 缩放因子越大，模型运行速度越慢，检测准确率越高。 + - 检测阈值越高，人脸筛选越严格，检测出的人脸框可能越少。 3. 编译并运行全量api的demo(注：当编译模式为tiny_pubish时将不存在该demo) ```shell diff --git a/lite/demo/cxx/mask_detection/mask_detection.cc b/lite/demo/cxx/mask_detection/mask_detection.cc index 748b84365f..869f08094d 100644 --- a/lite/demo/cxx/mask_detection/mask_detection.cc +++ b/lite/demo/cxx/mask_detection/mask_detection.cc @@ -81,6 +81,29 @@ void neon_mean_scale(const float* din, } } +cv::Mat crop_img(const cv::Mat& img, + cv::Rect rec, + int res_width, + int res_height) { + float xmin = rec.x; + float ymin = rec.y; + float w = rec.width; + float h = rec.height; + float center_x = xmin + w / 2; + float center_y = ymin + h / 2; + cv::Point2f center(center_x, center_y); + float max_wh = std::max(w / 2, h / 2); + float scale = res_width / (2 * max_wh * 1.5); + cv::Mat rot_mat = cv::getRotationMatrix2D(center, 0.f, scale); + rot_mat.at(0, 2) = + rot_mat.at(0, 2) - (center_x - res_width / 2.0); + rot_mat.at(1, 2) = + rot_mat.at(1, 2) - (center_y - res_width / 2.0); + cv::Mat affine_img; + cv::warpAffine(img, affine_img, rot_mat, cv::Size(res_width, res_height)); + return affine_img; +} + void pre_process(const cv::Mat& img, int width, int height, @@ -89,8 +112,12 @@ void pre_process(const cv::Mat& img, float* data, bool is_scale = false) { cv::Mat resized_img; - cv::resize( - img, resized_img, cv::Size(width, height), 0.f, 0.f, cv::INTER_CUBIC); + if (img.cols != width || img.rows != height) { + cv::resize( + img, resized_img, cv::Size(width, height), 0.f, 0.f, cv::INTER_CUBIC); + } else { + resized_img = img; + } cv::Mat imgf; float scale_factor = is_scale ? 1.f / 256 : 1.f; resized_img.convertTo(imgf, CV_32FC3, scale_factor); @@ -103,7 +130,7 @@ void RunModel(std::string det_model_dir, std::string img_path) { // Prepare cv::Mat img = imread(img_path, cv::IMREAD_COLOR); - float shrink = 0.2; + float shrink = 0.4; int width = img.cols; int height = img.rows; int s_width = static_cast(width * shrink); @@ -138,7 +165,7 @@ void RunModel(std::string det_model_dir, int64_t out_len = ShapeProduction(shape_out); // Filter Out Detection Box - float detect_threshold = 0.3; + float detect_threshold = 0.7; std::vector detect_result; for (int i = 0; i < out_len / 6; ++i) { if (outptr[1] >= detect_threshold) { @@ -172,10 +199,13 @@ void RunModel(std::string det_model_dir, int detect_num = detect_result.size(); std::vector classify_mean = {0.5f, 0.5f, 0.5f}; std::vector classify_scale = {1.f, 1.f, 1.f}; - float classify_threshold = 0.5; for (int i = 0; i < detect_num; ++i) { cv::Rect rec_clip = detect_result[i].rec; - cv::Mat roi = img(rec_clip); + cv::Mat roi = crop_img(img, rec_clip, classify_w, classify_h); + + // uncomment two lines below, save roi img to disk + // std::string roi_name = "roi_" + std::to_string(i) + ".jpg"; + // imwrite(roi_name, roi); // Do PreProcess pre_process(roi, @@ -193,35 +223,58 @@ void RunModel(std::string det_model_dir, std::unique_ptr output_tensor1( std::move(predictor->GetOutput(1))); auto* outptr = output_tensor1->data(); + float prob = outptr[1]; // Draw Detection and Classification Results - cv::rectangle(img, rec_clip, cv::Scalar(0, 0, 255), 2, cv::LINE_AA); - std::string text = outptr[1] > classify_threshold ? "wear mask" : "no mask"; - int font_face = cv::FONT_HERSHEY_COMPLEX_SMALL; - double font_scale = 1.f; - int thickness = 1; + bool flag_mask = prob > 0.5f; + cv::Scalar roi_color; + std::string text; + if (flag_mask) { + text = "MASK: "; + roi_color = cv::Scalar(0, 255, 0); + } else { + text = "NO MASK: "; + roi_color = cv::Scalar(0, 0, 255); + prob = 1 - prob; + } + std::string prob_str = std::to_string(prob * 100); + int point_idx = prob_str.find_last_of("."); + + text += prob_str.substr(0, point_idx + 3) + "%"; + int font_face = cv::FONT_HERSHEY_SIMPLEX; + double font_scale = 0.25; + float thickness = 1; cv::Size text_size = cv::getTextSize(text, font_face, font_scale, thickness, nullptr); - float new_font_scale = rec_clip.width * 0.7 * font_scale / text_size.width; - text_size = - cv::getTextSize(text, font_face, new_font_scale, thickness, nullptr); + + int top_space = std::max(0.35 * text_size.height, 2.0); + int bottom_space = top_space + 2; + int right_space = 0.05 * text_size.width; + int back_width = text_size.width + right_space; + int back_height = text_size.height + top_space + bottom_space; + + // Configure text background + cv::Rect text_back = + cv::Rect(rec_clip.x, rec_clip.y - back_height, back_width, back_height); + + // Draw roi object, text, and background + cv::rectangle(img, rec_clip, roi_color, 1); + cv::rectangle(img, text_back, cv::Scalar(225, 225, 225), -1); cv::Point origin; - origin.x = rec_clip.x + 5; - origin.y = rec_clip.y + text_size.height + 5; + origin.x = rec_clip.x; + origin.y = rec_clip.y - bottom_space; cv::putText(img, text, origin, font_face, - new_font_scale, - cv::Scalar(0, 255, 255), - thickness, - cv::LINE_AA); + font_scale, + cv::Scalar(0, 0, 0), + thickness); std::cout << "detect face, location: x=" << rec_clip.x << ", y=" << rec_clip.y << ", width=" << rec_clip.width - << ", height=" << rec_clip.height - << ", wear mask: " << (outptr[1] > classify_threshold) - << std::endl; + << ", height=" << rec_clip.height << ", wear mask: " << flag_mask + << ", prob: " << prob << std::endl; } // Write Result to Image File @@ -230,6 +283,8 @@ void RunModel(std::string det_model_dir, std::string img_name = img_path.substr(start + 1, end - start - 1); std::string result_name = img_name + "_mask_detection_result.jpg"; cv::imwrite(result_name, img); + std::cout << "write result to file: " << result_name << ", success." + << std::endl; } int main(int argc, char** argv) { -- GitLab