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Default Version APIs.

More details of basic types for Default Version APIs can be found at types . Note that Lite.AI.ToolKit uses onnxruntime as default backend, for the reason that onnxruntime supports the most of onnx's operators. (TODO: Add detailed API documentation)

lite::cv::detection::YoloV5

void detect(const cv::Mat &mat, std::vector<types::Boxf> &detected_boxes, 
            float score_threshold = 0.25f, float iou_threshold = 0.45f,
            unsigned int topk = 100, unsigned int nms_type = NMS::OFFSET);

lite::cv::detection::YoloV4

void detect(const cv::Mat &mat, std::vector<types::Boxf> &detected_boxes, 
            float score_threshold = 0.25f, float iou_threshold = 0.45f,
            unsigned int topk = 100, unsigned int nms_type = NMS::OFFSET);

lite::cv::detection::YoloV3

void detect(const cv::Mat &mat, std::vector<types::Boxf> &detected_boxes);

lite::cv::detection::TinyYoloV3

void detect(const cv::Mat &mat, std::vector<types::Boxf> &detected_boxes);

lite::cv::detection::SSD

void detect(const cv::Mat &mat, std::vector<types::Boxf> &detected_boxes, 
            float score_threshold = 0.25f, float iou_threshold = 0.45f,
            unsigned int topk = 100, unsigned int nms_type = NMS::OFFSET);

lite::cv::detection::SSDMobileNetV1

void detect(const cv::Mat &mat, std::vector<types::Boxf> &detected_boxes, 
            float score_threshold = 0.25f, float iou_threshold = 0.45f,
            unsigned int topk = 100, unsigned int nms_type = NMS::OFFSET);

lite::cv::face::FSANet

void detect(const cv::Mat &mat, types::EulerAngles &euler_angles);

lite::cv::face::UltraFace

void detect(const cv::Mat &mat, std::vector<types::Boxf> &detected_boxes,
            float score_threshold = 0.7f, float iou_threshold = 0.3f,
            unsigned int topk = 300, unsigned int nms_type = 0);

lite::cv::face::PFLD

void detect(const cv::Mat &mat, types::Landmarks &landmarks);

lite::cv::face::AgeGoogleNet

void detect(const cv::Mat &mat, types::Age &age);

lite::cv::face::GenderGoogleNet

void detect(const cv::Mat &mat, types::Gender &gender);

lite::cv::face::VGG16Age

void detect(const cv::Mat &mat, types::Age &age);

lite::cv::face::VGG16Gender

void detect(const cv::Mat &mat, types::Gender &gender);

lite::cv::face::EmotionFerPlus

void detect(const cv::Mat &mat, types::Emotions &emotions);

lite::cv::face::SSRNet

void detect(const cv::Mat &mat, types::Age &age);

lite::cv::faceid::ArcFaceResNet

void detect(const cv::Mat &mat, types::FaceContent &face_content);

lite::cv::segmentation::DeepLabV3ResNet101

void detect(const cv::Mat &mat, types::SegmentContent &content);

lite::cv::segmentation::FCNResNet101

void detect(const cv::Mat &mat, types::SegmentContent &content);

lite::cv::style::FastStyleTransfer

void detect(const cv::Mat &mat, types::StyleContent &style_content);

lite::cv::colorization::Colorizer

void detect(const cv::Mat &mat, types::ColorizeContent &colorize_content);

lite::cv::resolution::SubPixelCNN

void detect(const cv::Mat &mat, types::SuperResolutionContent &super_resolution_content);

lite::cv::classification::EfficientNetLite4

void detect(const cv::Mat &mat, types::ImageNetContent &content, unsigned int top_k = 5);

lite::cv::classification::ShuffleNetV2

void detect(const cv::Mat &mat, types::ImageNetContent &content, unsigned int top_k = 5);

lite::cv::classification::DenseNet

void detect(const cv::Mat &mat, types::ImageNetContent &content, unsigned int top_k = 5);

lite::cv::classification::GhostNet

void detect(const cv::Mat &mat, types::ImageNetContent &content, unsigned int top_k = 5);

lite::cv::classification::HdrDNet

void detect(const cv::Mat &mat, types::ImageNetContent &content, unsigned int top_k = 5);

lite::cv::classification::MobileNetV2

void detect(const cv::Mat &mat, types::ImageNetContent &content, unsigned int top_k = 5);

lite::cv::classification::ResNet

void detect(const cv::Mat &mat, types::ImageNetContent &content, unsigned int top_k = 5);

lite::cv::classification::ResNeXt

void detect(const cv::Mat &mat, types::ImageNetContent &content, unsigned int top_k = 5);

lite::cv::utils::hard_nms

LITEHUB_EXPORTS void
hard_nms(std::vector<types::Boxf> &input, std::vector<types::Boxf> &output, float iou_threshold, unsigned int topk);

lite::cv::utils::blending_nms

LITEHUB_EXPORTS void
blending_nms(std::vector<types::Boxf> &input, std::vector<types::Boxf> &output, float iou_threshold, unsigned int topk);

lite::cv::utils::offset_nms

LITEHUB_EXPORTS void
offset_nms(std::vector<types::Boxf> &input, std::vector<types::Boxf> &output, float iou_threshold, unsigned int topk);