[Doc] API docs for Visualize module

docs/api_docs/cpp/Doxyfile

@@ -2100,7 +2100,7 @@ INCLUDE_FILE_PATTERNS  =
 # recursively expanded use the := operator instead of the = operator.
 # This tag requires that the tag ENABLE_PREPROCESSING is set to YES.
 
-PREDEFINED = protected=private
+PREDEFINED = protected=private ENABLE_VISION_VISUALIZE=1
 
 # If the MACRO_EXPANSION and EXPAND_ONLY_PREDEF tags are set to YES then this
 # tag can be used to specify a list of macro names that should be expanded. The

docs/api_docs/python/visualize.md

@@ -0,0 +1,57 @@
+# Visaulize(可视化)
+
+## fastdeploy.vision.vis_detection
+
+```{eval-rst}
+.. autoclass:: fastdeploy.vision.vis_detection
+    :members:
+    :inherited-members:
+```
+
+## fastdeploy.vision.vis_segmentation
+
+```{eval-rst}
+.. autoclass:: fastdeploy.vision.vis_segmentation
+    :members:
+    :inherited-members:
+```
+
+## fastdeploy.vision.vis_keypoint_detection
+
+```{eval-rst}
+.. autoclass:: fastdeploy.vision.vis_keypoint_detection
+    :members:
+    :inherited-members:
+```
+## fastdeploy.vision.vis_face_detection
+
+```{eval-rst}
+.. autoclass:: fastdeploy.vision.vis_face_detection
+    :members:
+    :inherited-members:
+```
+
+
+## fastdeploy.vision.vis_face_alignment
+
+```{eval-rst}
+.. autoclass:: fastdeploy.vision.vis_face_alignment
+    :members:
+    :inherited-members:
+```
+
+## fastdeploy.vision.vis_matting
+
+```{eval-rst}
+.. autoclass:: fastdeploy.vision.vis_matting
+    :members:
+    :inherited-members:
+```
+
+## fastdeploy.vision.vis_ppocr
+
+```{eval-rst}
+.. autoclass:: fastdeploy.vision.vis_ppocr
+    :members:
+    :inherited-members:
+```

fastdeploy/vision/visualize/visualize.h

@@ -20,9 +20,11 @@
 #include "fastdeploy/vision/tracking/pptracking/model.h"
 
 namespace fastdeploy {
+/** \brief All C++ FastDeploy Vision Models APIs are defined inside this namespace
+*
+*/
 namespace vision {
 
-// This class will deprecated, please not use it
 class FASTDEPLOY_DECL Visualize {
  public:
   static int num_classes_;
@@ -52,35 +54,108 @@ class FASTDEPLOY_DECL Visualize {
 
 std::vector<int> GenerateColorMap(int num_classes = 1000);
 cv::Mat RemoveSmallConnectedArea(const cv::Mat& alpha_pred, float threshold);
+/** \brief Show the visualized results for detection models
+ *
+ * \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] score_threshold threshold for result scores, the bounding box will not be shown if the score is less than score_threshold
+ * \param[in] line_size line size for bounding boxes
+ * \param[in] font_size font size for text
+ * \return cv::Mat type stores the visualized results
+ */
 FASTDEPLOY_DECL cv::Mat VisDetection(const cv::Mat& im,
                                      const DetectionResult& result,
                                      float score_threshold = 0.0,
                                      int line_size = 1, float font_size = 0.5f);
+/** \brief Show the visualized results with custom labels for detection models
+ *
+ * \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] labels the visualized result will show the bounding box contain class label
+ * \param[in] score_threshold threshold for result scores, the bounding box will not be shown if the score is less than score_threshold
+ * \param[in] line_size line size for bounding boxes
+ * \param[in] font_size font size for text
+ * \return cv::Mat type stores the visualized results
+ */
 FASTDEPLOY_DECL cv::Mat VisDetection(const cv::Mat& im,
                                      const DetectionResult& result,
                                      const std::vector<std::string>& labels,
                                      float score_threshold = 0.0,
                                      int line_size = 1, float font_size = 0.5f);
+/** \brief Show the visualized results for classification models
+ *
+ * \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] top_k the length of return values, e.g., if topk==2, the result will include the 2 most possible class label for input image.
+ * \param[in] score_threshold threshold for top_k scores, the class will not be shown if the score is less than score_threshold
+ * \param[in] font_size font size
+ * \return cv::Mat type stores the visualized results
+ */
 FASTDEPLOY_DECL cv::Mat VisClassification(
   const cv::Mat& im, const ClassifyResult& result, int top_k = 5,
   float score_threshold = 0.0f, float font_size = 0.5f);
+/** \brief Show the visualized results with custom labels for classification models
+ *
+ * \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] labels custom labels for user, the visualized result will show the corresponding custom labels
+ * \param[in] top_k the length of return values, e.g., if topk==2, the result will include the 2 most possible class label for input image.
+ * \param[in] score_threshold threshold for top_k scores, the class will not be shown if the score is less than score_threshold
+ * \param[in] font_size font size
+ * \return cv::Mat type stores the visualized results
+ */
 FASTDEPLOY_DECL cv::Mat VisClassification(
   const cv::Mat& im, const ClassifyResult& result,
   const std::vector<std::string>& labels, int top_k = 5,
   float score_threshold = 0.0f, float font_size = 0.5f);
+/** \brief Show the visualized results for face detection models
+ *
+ * \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] line_size line size for bounding boxes
+ * \param[in] font_size font size for text
+ * \return cv::Mat type stores the visualized results
+ */
 FASTDEPLOY_DECL cv::Mat VisFaceDetection(const cv::Mat& im,
                                          const FaceDetectionResult& result,
                                          int line_size = 1,
                                          float font_size = 0.5f);
+/** \brief Show the visualized results for face alignment models
+ *
+ * \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] line_size line size for circle point
+ * \return cv::Mat type stores the visualized results
+ */
 FASTDEPLOY_DECL cv::Mat VisFaceAlignment(const cv::Mat& im,
                                          const FaceAlignmentResult& result,
                                          int line_size = 1);
+/** \brief Show the visualized results for segmentation models
+ *
+ * \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] weight transparent weight of visualized result image
+ * \return cv::Mat type stores the visualized results
+ */
 FASTDEPLOY_DECL cv::Mat VisSegmentation(const cv::Mat& im,
                                         const SegmentationResult& result,
                                         float weight = 0.5);
+/** \brief Show the visualized results for matting models
+ *
+ * \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
+ * \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);
+/** \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
+ * \param[in] result the result produced by model
+ * \return cv::Mat type stores the visualized results
+ */
 FASTDEPLOY_DECL cv::Mat VisOcr(const cv::Mat& im, const OCRResult& ocr_result);
 
 FASTDEPLOY_DECL cv::Mat VisMOT(const cv::Mat& img, const MOTResult& results,
@@ -93,6 +168,13 @@ FASTDEPLOY_DECL cv::Mat SwapBackground(const cv::Mat& im,
                                        const cv::Mat& background,
                                        const SegmentationResult& result,
                                        int background_label);
+/** \brief Show the visualized results for key point detection models
+ *
+ * \param[in] im the input image data, comes from cv::imread(), is a 3-D array with layout HWC, BGR format
+ * \param[in] results the result produced by model
+ * \param[in] conf_threshold threshold for result scores, the result will not be shown if the score is less than conf_threshold
+ * \return cv::Mat type stores the visualized results
+ */
 FASTDEPLOY_DECL cv::Mat VisKeypointDetection(const cv::Mat& im,
                         const KeyPointDetectionResult& results,
                         float conf_threshold = 0.5f);

python/fastdeploy/vision/visualize/__init__.py

@@ -24,25 +24,64 @@ def vis_detection(im_data,
                   score_threshold=0.0,
                   line_size=1,
                   font_size=0.5):
+    """Show the visualized results for detection models
+
+    :param im_data: (numpy.ndarray)The input image data, 3-D array with layout HWC, BGR format
+    :param det_result: the result produced by model
+    :param labels: (list of str) the visualized result will show the bounding box contain class label
+    :param score_threshold: (float) score_threshold threshold for result scores, the bounding box will not be shown if the score is less than score_threshold
+    :param line_size: (float) line_size line size for bounding boxes
+    :param font_size: (float) font_size font size for text
+    :return: (numpy.ndarray) image with visualized results
+    """
     return C.vision.vis_detection(im_data, det_result, labels, score_threshold,
                                   line_size, font_size)
 
 
 def vis_keypoint_detection(im_data, keypoint_det_result, conf_threshold=0.5):
+    """Show the visualized results for keypoint detection models
+
+    :param im_data: (numpy.ndarray)The input image data, 3-D array with layout HWC, BGR format
+    :param keypoint_det_result: the result produced by model
+    :param conf_threshold: (float) conf_threshold threshold for result scores, the bounding box will not be shown if the score is less than conf_threshold
+    :return: (numpy.ndarray) image with visualized results
+    """
     return C.vision.Visualize.vis_keypoint_detection(
         im_data, keypoint_det_result, conf_threshold)
 
 
 def vis_face_detection(im_data, face_det_result, line_size=1, font_size=0.5):
+    """Show the visualized results for face detection models
+
+    :param im_data: (numpy.ndarray)The input image data, 3-D array with layout HWC, BGR format
+    :param face_det_result: the result produced by model
+    :param line_size: (float) line_size line size for bounding boxes
+    :param font_size: (float) font_size font size for text
+    :return: (numpy.ndarray) image with visualized results
+    """
     return C.vision.vis_face_detection(im_data, face_det_result, line_size,
                                        font_size)
 
 
 def vis_face_alignment(im_data, face_align_result, line_size=1):
+    """Show the visualized results for face alignment models
+
+    :param im_data: (numpy.ndarray)The input image data, 3-D array with layout HWC, BGR format
+    :param face_align_result: the result produced by model
+    :param line_size: (float)line_size line size for circle point
+    :return: (numpy.ndarray) image with visualized results
+    """
     return C.vision.vis_face_alignment(im_data, face_align_result, line_size)
 
 
 def vis_segmentation(im_data, seg_result, weight=0.5):
+    """Show the visualized results for segmentation models
+
+    :param im_data: (numpy.ndarray)The input image data, 3-D array with layout HWC, BGR format
+    :param seg_result: the result produced by model
+    :param weight: (float)transparent weight of visualized result image
+    :return: (numpy.ndarray) image with visualized results
+    """
     return C.vision.vis_segmentation(im_data, seg_result, weight)
 
 
@@ -57,6 +96,13 @@ def vis_matting_alpha(im_data,
 
 
 def vis_matting(im_data, matting_result, 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 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,
                                 remove_small_connected_area)
 
@@ -105,6 +151,12 @@ def swap_background(im_data,
 
 
 def vis_ppocr(im_data, det_result):
+    """Show the visualized results for ocr models
+
+    :param im_data: (numpy.ndarray)The input image data, 3-D array with layout HWC, BGR format
+    :param det_result: the result produced by model
+    :return: (numpy.ndarray) image with visualized results
+    """
     return C.vision.vis_ppocr(im_data, det_result)