dtourolleandClaude Opus 5
b35d49c772
Adds TRACES tags to code that already satisfies a Done requirement, so coverage reflects what exists rather than starting from zero: AR-001 face detection, AR-005 ArcFace alignment, AR-023 calibration fit, DP-001/DP-002 the single analysis core behind the CLI, IR-001 truth-file emission, IR-006 the Jellyfin round trip, GR-001/GR-002 gallery build and incremental merge, VR-001 the embedding dump, VR-002 replay through the real nodes, VR-003 per-second scoring. Only Done requirements are tagged. A tag on Planned work would inflate coverage with fiction that looks plausible — the same failure family as a gate that cannot fail, and harder to spot. GR-005 (gallery never leaves the instance) stays untagged deliberately: it is a prohibition satisfied by the absence of an egress path, so there is no unit that decides it. Same shape as PR-005 in the system spec, which has no software row for the same reason. A goal held only by prohibitions cannot be verified by pointing at code. Coverage 5/63 to 14/63. The three VR tags are reported as tagged-but-unexecuted and excluded from the numerator, since their tier cannot run on the CI host — tagging deliberately cannot raise the number on its own. Suite still 64 cases, 3199 assertions. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com> TRACES: AR-001, AR-005, AR-023, DP-001, DP-002, IR-001, IR-006, GR-001, GR-002, VR-001, VR-002, VR-003
60 lines
2.5 KiB
C++
60 lines
2.5 KiB
C++
#pragma once
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/// TRACES: AR-005 | SR-002
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#include "types.hpp"
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#include <opencv2/calib3d.hpp>
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#include <opencv2/imgproc.hpp>
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#include <cmath>
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// ── align_face ────────────────────────────────────────────────────────────────
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// Produces a 112×112 BGR crop using the ArcFace 5-point similarity transform.
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// Returns an empty Mat if the affine fit fails (degenerate detection).
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inline cv::Mat align_face(const cv::Mat& img,
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const std::array<cv::Point2f, 5>& landmarks) {
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std::vector<cv::Point2f> src(landmarks.begin(), landmarks.end());
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std::vector<cv::Point2f> dst(5);
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for (int i = 0; i < 5; ++i) dst[i] = {kArcFaceRef[i][0], kArcFaceRef[i][1]};
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cv::Mat M = cv::estimateAffinePartial2D(src, dst, cv::noArray(), cv::RANSAC, 3.0);
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if (M.empty()) return {};
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cv::Mat crop;
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cv::warpAffine(img, crop, M, {112, 112},
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cv::INTER_LINEAR, cv::BORDER_CONSTANT, {0, 0, 0});
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return crop;
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}
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// ── enhance_for_retry ────────────────────────────────────────────────────────
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// Used when initial face detection finds nothing. Pads the image by 50%
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// (border-replicated, so the detector doesn't see a hard edge) and applies
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// CLAHE to boost local contrast, giving the detector a second try.
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inline cv::Mat enhance_for_retry(const cv::Mat& img) {
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cv::Mat padded;
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const int pad_x = img.cols / 4;
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const int pad_y = img.rows / 4;
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cv::copyMakeBorder(img, padded, pad_y, pad_y, pad_x, pad_x, cv::BORDER_REPLICATE);
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cv::Mat lab;
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cv::cvtColor(padded, lab, cv::COLOR_BGR2Lab);
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std::vector<cv::Mat> channels;
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cv::split(lab, channels);
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cv::createCLAHE(2.0, cv::Size(8, 8))->apply(channels[0], channels[0]);
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cv::merge(channels, lab);
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cv::Mat out;
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cv::cvtColor(lab, out, cv::COLOR_Lab2BGR);
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return out;
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}
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// ── l2_normalise ──────────────────────────────────────────────────────────────
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inline Embedding l2_normalise(const float* row) {
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float norm = 0.f;
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for (int d = 0; d < 512; ++d) norm += row[d] * row[d];
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norm = std::sqrt(norm);
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if (norm < 1e-6f) norm = 1e-6f;
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Embedding emb;
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for (int d = 0; d < 512; ++d) emb[d] = row[d] / norm;
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return emb;
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}
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