Removed IplImage completely

README.md

@@ -44,7 +44,7 @@ More details: http://pjreddie.com/darknet/yolo/
 * Windows or Linux
 * **CMake >= 3.8** for modern CUDA support: https://cmake.org/download/
 * **CUDA 10.0**: https://developer.nvidia.com/cuda-toolkit-archive (on Linux do [Post-installation Actions](https://docs.nvidia.com/cuda/cuda-installation-guide-linux/index.html#post-installation-actions))
-* **OpenCV > 2.4**: use your preferred package manager (brew, apt), build from source using [vcpkg](https://github.com/Microsoft/vcpkg) or download from [OpenCV official site](https://opencv.org/releases.html) (on Windows set system variable `OpenCV_DIR` = `C:\opencv\build` - where are the `include` and `x64` folders [image](https://user-images.githubusercontent.com/4096485/53249516-5130f480-36c9-11e9-8238-a6e82e48c6f2.png))
+* **OpenCV >= 2.4**: use your preferred package manager (brew, apt), build from source using [vcpkg](https://github.com/Microsoft/vcpkg) or download from [OpenCV official site](https://opencv.org/releases.html) (on Windows set system variable `OpenCV_DIR` = `C:\opencv\build` - where are the `include` and `x64` folders [image](https://user-images.githubusercontent.com/4096485/53249516-5130f480-36c9-11e9-8238-a6e82e48c6f2.png))
 * **cuDNN >= 7.0 for CUDA 10.0** https://developer.nvidia.com/rdp/cudnn-archive (on **Linux** copy `cudnn.h`,`libcudnn.so`... as desribed here https://docs.nvidia.com/deeplearning/sdk/cudnn-install/index.html#installlinux-tar , on **Windows** copy `cudnn.h`,`cudnn64_7.dll`, `cudnn64_7.lib` as desribed here https://docs.nvidia.com/deeplearning/sdk/cudnn-install/index.html#installwindows )
 * **GPU with CC >= 3.0**: https://en.wikipedia.org/wiki/CUDA#GPUs_supported
 * on Linux **GCC or Clang**, on Windows **MSVC 2015/2017/2019** https://visualstudio.microsoft.com/thank-you-downloading-visual-studio/?sku=Community

include/yolo_v2_class.hpp

@@ -132,33 +132,28 @@ public:
         else if (img_src.channels() == 1) cv::cvtColor(img_src, img, cv::COLOR_GRAY2BGR);
         else std::cerr << " Warning: img_src.channels() is not 1, 3 or 4. It is = " << img_src.channels() << std::endl;
         std::shared_ptr<image_t> image_ptr(new image_t, [](image_t *img) { free_image(*img); delete img; });
-        std::shared_ptr<IplImage> ipl_small = std::make_shared<IplImage>(img);
+        *image_ptr = mat_to_image_custom(img);
-        *image_ptr = ipl_to_image(ipl_small.get());
         return image_ptr;
     }
 
 private:
 
-    static image_t ipl_to_image(IplImage* src)
+    static image_t mat_to_image_custom(cv::Mat mat)
     {
-        unsigned char *data = (unsigned char *)src->imageData;
+        int w = mat.cols;
-        int h = src->height;
+        int h = mat.rows;
-        int w = src->width;
+        int c = mat.channels();
-        int c = src->nChannels;
+        image_t im = make_image_custom(w, h, c);
-        int step = src->widthStep;
+        unsigned char *data = (unsigned char *)mat.data;
-        image_t out = make_image_custom(w, h, c);
+        int step = mat.step;
-        int count = 0;
+        for (int y = 0; y < h; ++y) {
-
             for (int k = 0; k < c; ++k) {
-            for (int i = 0; i < h; ++i) {
+                for (int x = 0; x < w; ++x) {
-                int i_step = i*step;
+                    im.data[k*w*h + y*w + x] = data[y*step + x*c + k] / 255.0f;
-                for (int j = 0; j < w; ++j) {
-                    out.data[count++] = data[i_step + j*c + k] / 255.;
                 }
             }
         }
-
+        return im;
-        return out;
     }
 
     static image_t make_empty_image(int w, int h, int c)

src/image_opencv.cpp

@@ -86,8 +86,8 @@ extern "C" {
 // ====================================================================
     image mat_to_image(cv::Mat mat);
     cv::Mat image_to_mat(image img);
-    image ipl_to_image(mat_cv* src);
+//    image ipl_to_image(mat_cv* src);
-    mat_cv *image_to_ipl(image img);
+//    mat_cv *image_to_ipl(image img);
 //    cv::Mat ipl_to_mat(IplImage *ipl);
 //    IplImage *mat_to_ipl(cv::Mat mat);
 
@@ -850,6 +850,7 @@ void save_cv_jpg(mat_cv *img_src, const char *name)
 // ====================================================================
 void draw_detections_cv_v3(mat_cv* mat, detection *dets, int num, float thresh, char **names, image **alphabet, int classes, int ext_output)
 {
+    try {
         cv::Mat *show_img = mat;
         int i, j;
         if (!show_img) return;
@@ -866,7 +867,7 @@ void draw_detections_cv_v3(mat_cv* mat, detection *dets, int num, float thresh,
                         strcat(labelstr, names[j]);
                         class_id = j;
                         char buff[10];
-                    sprintf(buff, " (%2.0f%%)", dets[i].prob[j]*100);
+                        sprintf(buff, " (%2.0f%%)", dets[i].prob[j] * 100);
                         strcat(labelstr, buff);
                     }
                     else {
@@ -933,7 +934,7 @@ void draw_detections_cv_v3(mat_cv* mat, detection *dets, int num, float thresh,
                 pt_text.x = left;
                 pt_text.y = top - 4;// 12;
                 pt_text_bg1.x = left;
-            pt_text_bg1.y = top - (1 + 18 * font_size);
+                pt_text_bg1.y = top - (3 + 18 * font_size);
                 pt_text_bg2.x = right;
                 if ((right - left) < text_size.width) pt_text_bg2.x = left + text_size.width;
                 pt_text_bg2.y = top;
@@ -968,14 +969,18 @@ void draw_detections_cv_v3(mat_cv* mat, detection *dets, int num, float thresh,
 
                 cv::rectangle(*show_img, pt_text_bg1, pt_text_bg2, color, width, 8, 0);
                 cv::rectangle(*show_img, pt_text_bg1, pt_text_bg2, color, CV_FILLED, 8, 0);    // filled
-            cv::Scalar black_color = CV_RGB(0,0,0);
+                cv::Scalar black_color = CV_RGB(0, 0, 0);
-            cv::putText(*show_img, labelstr, pt_text, cv::FONT_HERSHEY_COMPLEX_SMALL, font_size, black_color, 2*font_size, CV_AA);
+                cv::putText(*show_img, labelstr, pt_text, cv::FONT_HERSHEY_COMPLEX_SMALL, font_size, black_color, 2 * font_size, CV_AA);
                 // cv::FONT_HERSHEY_COMPLEX_SMALL, cv::FONT_HERSHEY_SIMPLEX
             }
         }
         if (ext_output) {
             fflush(stdout);
         }
+    }
+    catch (...) {
+        cerr << "OpenCV exception: draw_detections_cv_v3() \n";
+    }
 }
 // ----------------------------------------
 
@@ -984,22 +989,23 @@ void draw_detections_cv_v3(mat_cv* mat, detection *dets, int num, float thresh,
 // ====================================================================
 mat_cv* draw_train_chart(float max_img_loss, int max_batches, int number_of_lines, int img_size, int dont_show)
 {
-    int img_offset = 50;
+    int img_offset = 60;
     int draw_size = img_size - img_offset;
     cv::Mat *img_ptr = new cv::Mat(img_size, img_size, CV_8UC3, CV_RGB(255, 255, 255));
     cv::Mat &img = *img_ptr;
     cv::Point pt1, pt2, pt_text;
 
+    try {
         char char_buff[100];
         int i;
         // vertical lines
-    pt1.x = img_offset; pt2.x = img_size, pt_text.x = 10;
+        pt1.x = img_offset; pt2.x = img_size, pt_text.x = 30;
         for (i = 1; i <= number_of_lines; ++i) {
             pt1.y = pt2.y = (float)i * draw_size / number_of_lines;
             cv::line(img, pt1, pt2, CV_RGB(224, 224, 224), 1, 8, 0);
             if (i % 10 == 0) {
                 sprintf(char_buff, "%2.1f", max_img_loss*(number_of_lines - i) / number_of_lines);
-            pt_text.y = pt1.y + 5;
+                pt_text.y = pt1.y + 3;
 
                 cv::putText(img, char_buff, pt_text, cv::FONT_HERSHEY_COMPLEX_SMALL, 0.7, CV_RGB(0, 0, 0), 1, CV_AA);
                 cv::line(img, pt1, pt2, CV_RGB(128, 128, 128), 1, 8, 0);
@@ -1018,7 +1024,7 @@ mat_cv* draw_train_chart(float max_img_loss, int max_batches, int number_of_line
             }
         }
 
-    cv::putText(img, "Loss", cv::Point(0, 35), cv::FONT_HERSHEY_COMPLEX_SMALL, 0.7, CV_RGB(0, 0, 0), 1, CV_AA);
+        cv::putText(img, "Loss", cv::Point(10, 55), cv::FONT_HERSHEY_COMPLEX_SMALL, 0.7, CV_RGB(0, 0, 255), 1, CV_AA);
         cv::putText(img, "Iteration number", cv::Point(draw_size / 2, img_size - 10), cv::FONT_HERSHEY_COMPLEX_SMALL, 0.7, CV_RGB(0, 0, 0), 1, CV_AA);
         char max_batches_buff[100];
         sprintf(max_batches_buff, "in cfg max_batches=%d", max_batches);
@@ -1032,6 +1038,10 @@ mat_cv* draw_train_chart(float max_img_loss, int max_batches, int number_of_line
             cv::imshow("average loss", img);
             cv::waitKey(20);
         }
+    }
+    catch (...) {
+        cerr << "OpenCV exception: draw_train_chart() \n";
+    }
     return (mat_cv*)img_ptr;
 }
 // ----------------------------------------
@@ -1039,8 +1049,9 @@ mat_cv* draw_train_chart(float max_img_loss, int max_batches, int number_of_line
 void draw_train_loss(mat_cv* img_src, int img_size, float avg_loss, float max_img_loss, int current_batch, int max_batches,
     float precision, int draw_precision, char *accuracy_name, int dont_show, int mjpeg_port)
 {
+    try {
         cv::Mat &img = *(cv::Mat*)img_src;
-    int img_offset = 50;
+        int img_offset = 60;
         int draw_size = img_size - img_offset;
         char char_buff[100];
         cv::Point pt1, pt2;
@@ -1055,18 +1066,20 @@ void draw_train_loss(mat_cv* img_src, int img_size, float avg_loss, float max_im
             static int iteration_old = 0;
             static int text_iteration_old = 0;
             if (iteration_old == 0)
-            cv::putText(img, accuracy_name, cv::Point(0, 12), cv::FONT_HERSHEY_COMPLEX_SMALL, 0.7, CV_RGB(255, 0, 0), 1, CV_AA);
+                cv::putText(img, accuracy_name, cv::Point(10, 12), cv::FONT_HERSHEY_COMPLEX_SMALL, 0.7, CV_RGB(255, 0, 0), 1, CV_AA);
 
             cv::line(img,
                 cv::Point(img_offset + draw_size * (float)iteration_old / max_batches, draw_size * (1 - old_precision)),
                 cv::Point(img_offset + draw_size * (float)current_batch / max_batches, draw_size * (1 - precision)),
                 CV_RGB(255, 0, 0), 1, 8, 0);
 
+            sprintf(char_buff, "%2.0f%% ", precision * 100);
+            cv::putText(img, char_buff, cv::Point(10, 28), cv::FONT_HERSHEY_COMPLEX_SMALL, 0.7, CV_RGB(255, 255, 255), 5, CV_AA);
+            cv::putText(img, char_buff, cv::Point(10, 28), cv::FONT_HERSHEY_COMPLEX_SMALL, 0.7, CV_RGB(200, 0, 0), 1, CV_AA);
+
             if (((int)(old_precision * 10) != (int)(precision * 10)) || (current_batch - text_iteration_old) >= max_batches / 10) {
                 text_iteration_old = current_batch;
-            sprintf(char_buff, "%2.0f%% ", precision * 100);
                 cv::putText(img, char_buff, cv::Point(pt1.x - 30, draw_size * (1 - precision) + 15), cv::FONT_HERSHEY_COMPLEX_SMALL, 0.7, CV_RGB(255, 255, 255), 5, CV_AA);
-
                 cv::putText(img, char_buff, cv::Point(pt1.x - 30, draw_size * (1 - precision) + 15), cv::FONT_HERSHEY_COMPLEX_SMALL, 0.7, CV_RGB(200, 0, 0), 1, CV_AA);
             }
             old_precision = precision;
@@ -1074,11 +1087,11 @@ void draw_train_loss(mat_cv* img_src, int img_size, float avg_loss, float max_im
         }
 
         sprintf(char_buff, "current avg loss = %2.4f    iteration = %d", avg_loss, current_batch);
-    pt1.x = 55, pt1.y = 10;
+        pt1.x = 15, pt1.y = draw_size + 18;
         pt2.x = pt1.x + 460, pt2.y = pt1.y + 20;
         cv::rectangle(img, pt1, pt2, CV_RGB(255, 255, 255), CV_FILLED, 8, 0);
         pt1.y += 15;
-    cv::putText(img, char_buff, pt1, cv::FONT_HERSHEY_COMPLEX_SMALL, 0.7, CV_RGB(0, 0, 0), 1, CV_AA);
+        cv::putText(img, char_buff, pt1, cv::FONT_HERSHEY_COMPLEX_SMALL, 0.7, CV_RGB(0, 0, 100), 1, CV_AA);
 
         int k = 0;
         if (!dont_show) {
@@ -1093,6 +1106,10 @@ void draw_train_loss(mat_cv* img_src, int img_size, float avg_loss, float max_im
             cv::putText(img, "- Saved", cv::Point(260, img_size - 10), cv::FONT_HERSHEY_COMPLEX_SMALL, 0.7, CV_RGB(255, 255, 255), 1, CV_AA);
 
         if (mjpeg_port > 0) send_mjpeg((mat_cv *)&img, mjpeg_port, 500000, 100);
+    }
+    catch (...) {
+        cerr << "OpenCV exception: draw_train_loss() \n";
+    }
 }
 // ----------------------------------------