#include "serialization.hpp"
namespace cms {
namespace {
template<class T> Json optional(std::optional<T> const& x){return x?Json(*x):Json(nullptr);}
Json riskJson(RiskResult const& r) {
    Json out={{"status",r.status},{"risk_score",optional(r.risk_score)},{"risk_level",r.risk_level},{"decision",r.decision},{"source",optional(r.source)},{"track_id",optional(r.track_id)},{"side",optional(r.side)},{"regions",Json::array()}};
    if(!r.door_mask.status.empty()) {
        auto const& d=r.door_mask;out["door_mask"]={{"status",d.status},{"annotation_index",d.annotation_index},{"path",optional(d.path)},{"format",d.format},{"area_px",d.area_px}};
        out["warning_distance_relative"]=r.warning_distance_relative;out["release_distance_relative"]=r.release_distance_relative;
    }
    for(auto const& v:r.regions) {
        Json j={{"status",v.status},{"risk_score",optional(v.risk_score)},{"risk_level",v.risk_level},{"decision",v.decision},{"source",v.source},{"track_id",v.track_id},{"side",v.side}};
        if(v.state)j["state"]=*v.state;
        if(v.region_area_px) {
            j["region_area_px"]=optional(v.region_area_px);j["door_overlap_px"]=optional(v.door_overlap_px);j["region_overlap_ratio"]=optional(v.region_overlap_ratio);
            j["min_distance_px"]=optional(v.min_distance_px);j["region_scale_px"]=optional(v.region_scale_px);j["distance_relative"]=optional(v.distance_relative);
        }
        out["regions"].push_back(std::move(j));
    }
    return out;
}
}
Json serializeResult(FrameResult const& r) {
    Json out={{"frame_index",r.frame_index},{"track_ids",r.track_ids},{"boxes",r.boxes},{"skeletons",Json::array()},{"risk",riskJson(r.risk)}};
    for(std::size_t i=0;i<r.persons.size();++i) {
        auto const& p=r.persons[i];Json points=Json::array(),metadata=Json::object();for(auto const& k:p.selected)points.push_back({rounded(k.x,3),rounded(k.y,3)});
        for(int s=0;s<2;++s){auto const& h=p.hands[s];metadata[s==0?"left":"right"]={{"limb_state",h.limb_consensus?"consensus":"inferred"},{"hand_source",h.source},{"hand_state",h.state},{"distance_eligible",h.distance_eligible},{"alarm_eligible",h.alarm_eligible}};}
        out["skeletons"].push_back({{"track_id",p.track_id},{"person_index",i},{"layout","coco_wholebody_133"},{"keypoints",points},{"metadata",metadata}});
    }
    for(std::size_t i=0;i<r.persons.size();++i) {
        auto const& p=r.persons[i];auto& skeleton=out["skeletons"][i];
        skeleton["confidence"]=p.confidence;skeleton["keypoint_scores"]=Json::array();
        skeleton["smoothed_keypoints"]=Json::array();skeleton["temporal_keypoints"]=Json::array();
        for(std::size_t k=0;k<p.selected.size();++k) {
            skeleton["keypoint_scores"].push_back(p.selected[k].score);
            auto const& a=p.smoothed[k];auto const& b=p.temporal[k];
            skeleton["smoothed_keypoints"].push_back({a.x,a.y,a.score});
            skeleton["temporal_keypoints"].push_back({b.x,b.y,b.score});
        }
    }
    out["timing"]={{"detector_ms",r.timing.detector_ms},{"pose_ms",r.timing.pose_ms},{"fusion_risk_ms",r.timing.fusion_risk_ms},{"capture_to_result_ms",r.timing.capture_to_result_ms}};
    out["capture"]={{"sequence",r.capture.driver_sequence},{"capture_monotonic_ms",r.capture.capture_monotonic_ns*1e-6},{"driver_timestamp_ms",r.capture.driver_timestamp_ns*1e-6}};
    out["capture_to_result_ms"]=rounded(r.timing.capture_to_result_ms,3);out["calibration_verified"]=r.door_mask_calibration_verified;return out;
}
}