Determining a Hard Example Image
This section describes how to determine whether an input image is a hard example.
API Calling
virtual bool Filter(const float inferResult[], const int size);
virtual bool Filter(const std::vector<Bbox> &bboxList, DetectionFilterType type);
Parameter |
Description |
---|---|
inferResult[] |
Float array, which contains the confidence score of each class obtained by the classification algorithm |
size |
Input size |
Parameter |
Description |
---|---|
bboxList |
std::vector<Bbox>. The Bbox structure is defined as follows: structBbox { float xmin; float ymin; float xmax; float ymax; float score; int label; Bbox(floatbboxXmin, floatbboxYmin, floatbboxXmax, floatbboxYmax, floatbboxScore, intbboxLabel): xmin(bboxXmin), ymin(bboxYmin), xmax(bboxXmax), ymax(bboxYmax), score(bboxScore), label(bboxLabel){} }; Table 3 describes related parameters. |
type |
Type of the hard example filter. The value can be CrossEntropyFilter, IBT, or CSF. For details, see Introduction to Hard Example Upload. |
Value |
Description |
---|---|
xmin |
Coordinates of a bounding box |
ymin |
Coordinates of a bounding box |
xmax |
Coordinates of a bounding box |
ymax |
Coordinates of a bounding box |
score |
Score of a bounding box |
label |
Class of a bounding box |
Return Value
A bool value is returned, indicating whether the image is a hard example.
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