Update api && comments

fastdeploy/vision/visualize/matting.cc

@@ -19,8 +19,8 @@ namespace fastdeploy {
 namespace vision {
 
 cv::Mat VisMatting(const cv::Mat& im, const MattingResult& result,
-                   bool remove_small_connected_area, bool is_transparent, 
+                   bool transparent_background, float transparent_threshold,
-                   float transparent_threshold) {
+                   bool remove_small_connected_area) {
   FDASSERT((!im.empty()), "im can't be empty!");
 
   auto vis_img = im.clone();
@@ -45,7 +45,7 @@ cv::Mat VisMatting(const cv::Mat& im, const MattingResult& result,
     (vis_img).convertTo((vis_img), CV_8UC3);
   }
 
-  if(is_transparent) {
+  if (transparent_background) {
     if (vis_img.channels() != 4) {
       cv::cvtColor(vis_img, transparent_vis_mat, cv::COLOR_BGR2BGRA);
       vis_img = transparent_vis_mat;
@@ -60,17 +60,24 @@ cv::Mat VisMatting(const cv::Mat& im, const MattingResult& result,
   for (size_t i = 0; i < height; ++i) {
     for (size_t j = 0; j < width; ++j) {
       float alpha_val = alpha_data[i * width + j];
-      vis_data[i * width * channel + j * channel + 0] = cv::saturate_cast<uchar>(
+      vis_data[i * width * channel + j * channel + 0] =
-          static_cast<float>(im_data[i * width * 3 + j * 3 + 0]) * alpha_val +
+          cv::saturate_cast<uchar>(
+              static_cast<float>(im_data[i * width * 3 + j * 3 + 0]) *
+                  alpha_val +
               (1.f - alpha_val) * 153.f);
-      vis_data[i * width * channel + j * channel + 1] = cv::saturate_cast<uchar>(
+      vis_data[i * width * channel + j * channel + 1] =
-          static_cast<float>(im_data[i * width * 3 + j * 3 + 1]) * alpha_val +
+          cv::saturate_cast<uchar>(
+              static_cast<float>(im_data[i * width * 3 + j * 3 + 1]) *
+                  alpha_val +
               (1.f - alpha_val) * 255.f);
-      vis_data[i * width * channel + j * channel + 2] = cv::saturate_cast<uchar>(
+      vis_data[i * width * channel + j * channel + 2] =
-          static_cast<float>(im_data[i * width * 3 + j * 3 + 2]) * alpha_val +
+          cv::saturate_cast<uchar>(
+              static_cast<float>(im_data[i * width * 3 + j * 3 + 2]) *
+                  alpha_val +
               (1.f - alpha_val) * 120.f);
-      if (is_transparent && alpha_val < transparent_threshold) {
+      if (transparent_background && alpha_val < transparent_threshold) {
-        vis_data[i * width * channel + j * channel + 3] = cv::saturate_cast<uchar>(0.f);
+        vis_data[i * width * channel + j * channel + 3] =
+            cv::saturate_cast<uchar>(0.f);
       }
     }
   }

fastdeploy/vision/visualize/visualize.h

@@ -143,16 +143,16 @@ FASTDEPLOY_DECL cv::Mat VisSegmentation(const cv::Mat& im,
  *
  * \param[in] im the input image data, comes from cv::imread(), is a 3-D array with layout HWC, BGR format
  * \param[in] result the result produced by model
- * \param[in] remove_small_connected_area if remove_small_connected_area==true, the visualized result will not include the small connected areas
  * \param[in] is_transparent if is_transparent==true, the background will with transparent color
  * \param[in] transparent_threshold since the alpha value in MattringResult is a float between [0, 1], transparent_threshold is used to filter background pixel
+ * \param[in] remove_small_connected_area if remove_small_connected_area==true, the visualized result will not include the small connected areas
  * \return cv::Mat type stores the visualized results
  */
 FASTDEPLOY_DECL cv::Mat VisMatting(const cv::Mat& im,
                                    const MattingResult& result,
-                                   bool remove_small_connected_area = false,
                                    bool is_transparent = false,
-                                   float transparent_threshold = 0.999);
+                                   float transparent_threshold = 0.999
+                                   bool remove_small_connected_area = false);
 /** \brief Show the visualized results for Ocr models
  *
  * \param[in] im the input image data, comes from cv::imread(), is a 3-D array with layout HWC, BGR format

fastdeploy/vision/visualize/visualize_pybind.cc

@@ -102,10 +102,12 @@ void BindVisualize(pybind11::module& m) {
            })
       .def("vis_matting",
            [](pybind11::array& im_data, vision::MattingResult& result,
+              bool transparent_background, bool transparent_threshold,
               bool remove_small_connected_area) {
              cv::Mat im = PyArrayToCvMat(im_data);
-             auto vis_im =
+             auto vis_im = vision::VisMatting(
-                 vision::VisMatting(im, result, remove_small_connected_area);
+                 im, result, transparent_background, transparent_threshold,
+                 remove_small_connected_area);
              FDTensor out;
              vision::Mat(vis_im).ShareWithTensor(&out);
              return TensorToPyArray(out);

python/fastdeploy/vision/visualize/__init__.py

@@ -95,15 +95,22 @@ def vis_matting_alpha(im_data,
                                 remove_small_connected_area)
 
 
-def vis_matting(im_data, matting_result, remove_small_connected_area=False):
+def vis_matting(im_data,
+                matting_result,
+                transparent_background=False,
+                transparent_threshold=0.99,
+                remove_small_connected_area=False):
     """Show the visualized results for matting models
 
     :param im_data: (numpy.ndarray)The input image data, 3-D array with layout HWC, BGR format
     :param matting_result: the result produced by model
+    :param transparent_background: whether visulizing matting result with transparent background
+    :param transparent_threshold: since the alpha value in MattringResult is a float between [0, 1], transparent_threshold is used to filter background pixel
     :param remove_small_connected_area: (bool) if remove_small_connected_area==True, the visualized result will not include the small connected areas
     :return: (numpy.ndarray) image with visualized results
     """
     return C.vision.vis_matting(im_data, matting_result,
+                                transparent_background, transparent_threshold,
                                 remove_small_connected_area)