21 #include <opencv2/core/core.hpp>
34 namespace postprocessor
42 "your model uses a background class but your class file does not (use -1), or if your "
43 "model does not use a background class but your class file has one (use 1). If unsure, "
44 "use 0 and check whether reported class names are off.",
67 "InceptionV3 and possibly other networks",
72 (RAWYOLOv3) (RAWYOLOv4) (RAWYOLOv3tiny) )
84 "list of anchors. Should be formatted as: w1, h1, w2, h2, ... ; ww1, hh1, ww2, hh2, "
85 "... ; ... where individual entries for a given YOLO layer are separated by commas, "
86 "and successive YOLO layers (in the order in which they appear in the Darknet .cfg "
87 "
file) are separated by semicolons. Leave empty for other models. If your anchors are "
88 "the same for all YOLO layers, you may just specify them once.",
97 "semantic segmentation overlays",
105 "where N is the
number of classes and we
get one score per class, and we will show "
106 "the top scoring class for each pixel (e.g., UNet-MobileNet on TPU). If Classes2, "
107 "output is NxHxW and the rest is as for Classes (e.g., DeepLabV3 OpenCV). If ArgMax, "
108 "output is HxW and contains the class ID for each pixel (e.g., DeepLabV3 on TPU).",
109 SegType::Classes, SegType_Values, ParamCateg);
125 virtual void freeze(
bool doit) = 0;
128 virtual void process(std::vector<cv::Mat>
const & outs,
PreProcessor * preproc) = 0;