compute_normalised_rect()

template<ComputeData InputType = std::shared_ptr<Kakshya::SignalSourceContainer>, ComputeData OutputType = std::vector<Kakshya::DataVariant>>

std::array< float, 4 > MayaFlux::Yantra::VisionExtractor< InputType, OutputType >::compute_normalised_rect ( const VisionAnalysis &  analysis ) const

inline

Compute the normalised crop rectangle for a given VisionAnalysis.

Returns { nx, ny, nw, nh } in image space [0,1]. Used by callers to configure a TextureExecutionContext before GPU dispatch:

auto rect = extractor->compute_normalised_rect(analysis);
ctx->set_output_dimensions(crop_w, crop_h);
ctx->set_push_constants(CropPC { rect[0], rect[1], rect[2], rect[3], crop_w, crop_h });
extractor->apply_operation(datum);

Exceptions

std::out_of_range

if index exceeds the relevant detection collection.

Definition at line 101 of file VisionExtractor.hpp.

    {
        switch (m_mode) {
        case VisionExtractionMode::BBOX: {
            if (m_index >= analysis.frame.boxes.size()) {
                error<std::out_of_range>(
                    Journal::Component::Yantra,
                    Journal::Context::ComputeMatrix,
                    std::source_location::current(),
                    "VisionExtractor: bbox index {} out of range ({})",
                    m_index, analysis.frame.boxes.size());
            }
            const auto& b = analysis.frame.boxes[m_index];
            return { b.x, b.y, b.w, b.h };
        }
        case VisionExtractionMode::CONTOUR_TIGHT:
        case VisionExtractionMode::CONTOUR_MASKED: {
            if (m_index >= analysis.frame.contours.size()) {
                error<std::out_of_range>(
                    Journal::Component::Yantra,
                    Journal::Context::ComputeMatrix,
                    std::source_location::current(),
                    "VisionExtractor: contour index {} out of range ({})",
                    m_index, analysis.frame.contours.size());
            }
            const auto& pts = analysis.frame.contours[m_index].points;
            float min_x = pts[0].x, max_x = pts[0].x;
            float min_y = pts[0].y, max_y = pts[0].y;
            for (const auto& p : pts) {
                if (p.x < min_x)
                    min_x = p.x;
                if (p.x > max_x)
                    max_x = p.x;
                if (p.y < min_y)
                    min_y = p.y;
                if (p.y > max_y)
                    max_y = p.y;
            }
            return { min_x, min_y, max_x - min_x, max_y - min_y };
        }
        }
        return { 0.F, 0.F, 1.F, 1.F };
    }

References b, MayaFlux::Yantra::BBOX, MayaFlux::Yantra::DetectionSummary::boxes, MayaFlux::Journal::ComputeMatrix, MayaFlux::Yantra::CONTOUR_MASKED, MayaFlux::Yantra::CONTOUR_TIGHT, MayaFlux::Yantra::DetectionSummary::contours, MayaFlux::Yantra::VisionAnalysis::frame, MayaFlux::Yantra::VisionExtractor< InputType, OutputType >::m_index, MayaFlux::Yantra::VisionExtractor< InputType, OutputType >::m_mode, and MayaFlux::Journal::Yantra.

Referenced by MayaFlux::Yantra::VisionExtractor< InputType, OutputType >::apply_operation_internal(), and MayaFlux::Yantra::VisionExtractor< InputType, OutputType >::extract_implementation().

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