CLAUDE: v2 Stage-2 Hough-vote wiring + curt_c5_en flag + ORT log fix

- CuasStage2Infer: ONNX runner for the learned Stage-2 vote-refine (full-field conv).
- CuasDetectRT: voteScatter (s^2-weighted bilinear splat at tail T=P-V*(N-1)) + reg-branch
  wiring -> saves -VOTE heatmap + -REFINED detection when curt_stage2_model is set;
  curt_c5_en gates the heavy C5P convolve (DNN-only fast path).
- IntersceneMatchParameters: curt_c5_en + curt_stage2_model params (all 6 sites each).
- CuasDnnInfer: setSessionLogLevel(ERROR) to suppress benign ORT VerifyOutputSizes warnings.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

src/main/java/com/elphel/imagej/cuas/rt/CuasDetectRT.java

@@ -276,6 +276,29 @@ public class CuasDetectRT {
 
 	/** Level selector for the heavy per-level paths (3d3/conv5d, C5P-direct, DNN): // By Claude on 06/13/2026
 	 *  empty/null curt_c5_levels = all built levels, otherwise only the listed ones. */
+	/** v2 Stage-2 vote scatter: each ROI pixel splats an s^2-weighted bilinear vote at the tail
+	 *  T = P - V*(N-1) (the invariant convergence point - all of a target's alias-ramp pixels land there).
+	 *  S,Vx,Vy: [rw*rh] row-major. Returns [accS, accVx, accVy] (row-major). By Claude on 06/18/2026 */
+	static double[][] voteScatter(double[] S, double[] Vx, double[] Vy, int rw, int rh, int Nm1) {
+		int npix = rw * rh;
+		double[] accS = new double[npix], accVx = new double[npix], accVy = new double[npix];
+		for (int p = 0; p < npix; p++) {
+			double s = S[p]; if (!(s > 0)) continue;
+			double w = s * s;                                  // s^2: suppress the many weak-s (noise) votes
+			double tx = (p % rw) - Vx[p] * Nm1, ty = (p / rw) - Vy[p] * Nm1;
+			int x0 = (int) Math.floor(tx), y0 = (int) Math.floor(ty);
+			double fx = tx - x0, fy = ty - y0;
+			for (int dx = 0; dx < 2; dx++) for (int dy = 0; dy < 2; dy++) {
+				int xi = x0 + dx, yi = y0 + dy;
+				if (xi < 0 || xi >= rw || yi < 0 || yi >= rh) continue;
+				double bw = w * (dx == 0 ? 1 - fx : fx) * (dy == 0 ? 1 - fy : fy);
+				int idx = yi * rw + xi;
+				accS[idx] += bw; accVx[idx] += bw * Vx[p]; accVy[idx] += bw * Vy[p];
+			}
+		}
+		return new double[][] { accS, accVx, accVy };
+	}
+
 	private static boolean c5LevelSelected(int [] c5_levels, int nlev) { // By Claude on 06/13/2026
 		if ((c5_levels == null) || (c5_levels.length == 0)) return true;
 		for (int l : c5_levels) if (l == nlev) return true;
@@ -1095,7 +1118,7 @@ public class CuasDetectRT {
    			double [] op_log_prior = cuasRTUtils.getVelLogPrior(                           // shared by gate + sweep // By Claude on 06/13/2026
    					clt_parameters.imp.curt_c5_prior_r0, clt_parameters.imp.curt_c5_prior_r1); // By Claude on 06/13/2026
    			for (int nlev = 0; nlev < pyramid_levels; nlev++) {                            // By Claude on 06/11/2026
-   				if (!c5LevelSelected(c5_levels, nlev)) continue;                           // skip non-selected levels (speed) // By Claude on 06/13/2026
+   				if (!clt_parameters.imp.curt_c5_en || !c5LevelSelected(c5_levels, nlev)) continue; // curt_c5_en=false skips the heavy C5P convolve+posterior entirely (DNN-only fast path) // By Claude on 06/17/2026
    				double [][] frames = dpixels_pyramid[nlev];                                // By Claude on 06/11/2026
    				if (frames == null) continue;                                              // By Claude on 06/11/2026
    				int num_5dp = Math.max(0, frames.length - num_hist_p + 1);                 // By Claude on 06/11/2026
@@ -1278,6 +1301,26 @@ public class CuasDetectRT {
    								svxys, curt_save_select.width, title_reg+"-VXYS", ts_reg, new String[]{"S","Vx","Vy","sigma"}, false), clt_parameters.imp), getModelDirectory());
    						QuadCLTCPU.saveImagePlusInDirectory(tagCuasImp(ShowDoubleFloatArrays.showArraysHyperstack(
    								soffr, curt_save_select.width, title_reg+"-OFFSET", ts_reg, new String[]{"dx","dy","s"}, false), clt_parameters.imp), getModelDirectory());
+   						if (!clt_parameters.imp.curt_stage2_model.isEmpty()) {  // v2 Stage-2: vote + learned refine views // By Claude on 06/18/2026
+							int rw2 = curt_save_select.width, rh2 = curt_save_select.height, Nm1v = N_dnn - 1;
+							double [][][] votem = new double [1][num][rnpr];   // vote heatmap (accS)
+							double [][][] refd  = new double [3][num][rnpr];   // refined {S,Vx,Vy}
+							try {
+								CuasStage2Infer s2 = new CuasStage2Infer(clt_parameters.imp.curt_stage2_model);
+								for (int j = 0; j < num; j++) {
+									double [][] acc = voteScatter(svxys[0][j], svxys[1][j], svxys[2][j], rw2, rh2, Nm1v);
+									votem[0][j] = acc[0];
+									double [][] r = s2.refine(acc, rw2, rh2);
+									refd[0][j] = r[0]; refd[1][j] = r[1]; refd[2][j] = r[2];
+								}
+								s2.close();
+								QuadCLTCPU.saveImagePlusInDirectory(tagCuasImp(ShowDoubleFloatArrays.showArraysHyperstack(
+										votem, rw2, title_reg+"-VOTE", ts_reg, new String[]{"vote"}, false), clt_parameters.imp), getModelDirectory());
+								QuadCLTCPU.saveImagePlusInDirectory(tagCuasImp(ShowDoubleFloatArrays.showArraysHyperstack(
+										refd, rw2, title_reg+"-REFINED", ts_reg, new String[]{"S","Vx","Vy"}, false), clt_parameters.imp), getModelDirectory());
+								System.out.println(now()+"   v2 Stage-2: saved -VOTE + -REFINED ("+num+" scenes)");
+							} catch (Exception e) { System.out.println("v2 Stage-2 failed: "+e); }
+						}
 						continue;  // reg level done - skip the grid path below
    					}
    					double [][][][] dnn_roi = new double [num][][][];                         // By Claude on 06/13/2026

src/main/java/com/elphel/imagej/cuas/rt/CuasDnnInfer.java

@@ -38,6 +38,9 @@ public class CuasDnnInfer implements AutoCloseable {
         String local = resolveModel(modelSpec);
         this.env = OrtEnvironment.getEnvironment();
         OrtSession.SessionOptions opts = new OrtSession.SessionOptions();
+        // Only log errors (not warnings): suppresses the benign dynamic-batch VerifyOutputSizes W-spam
+        // (reg head's cat pins the graph's declared batch to 1) that was yellow-on-white in Eclipse. By Claude on 06/17/2026
+        try { opts.setSessionLogLevel(ai.onnxruntime.OrtLoggingLevel.ORT_LOGGING_LEVEL_ERROR); } catch (Exception e) {}
         // CPU EP by default. GPU later: opts.addCUDA(deviceId) once cuDNN 9 is present.
         this.session = env.createSession(local, opts);
         this.inputName = session.getInputNames().iterator().next();  // "frames"

src/main/java/com/elphel/imagej/cuas/rt/CuasStage2Infer.java

+package com.elphel.imagej.cuas.rt;
+
+import java.nio.FloatBuffer;
+import java.util.Collections;
+
+import ai.onnxruntime.OnnxTensor;
+import ai.onnxruntime.OrtEnvironment;
+import ai.onnxruntime.OrtSession;
+
+/**
+ * C5P DNN v2 Stage-2 (Hough-vote refine) ONNX runner. By Claude on 06/18/2026
+ * Loads the learned refine net (3-channel vote accumulator [accS, accVx, accVy] -> det logit + Vx,Vy consensus)
+ * and runs it over a whole ROI-sized accumulator in one pass (full-field conv, NOT patch-based like CuasDnnInfer).
+ * The vote scatter itself is done in Java (CuasDetectRT.voteScatter); this only runs the conv refine.
+ */
+public class CuasStage2Infer {
+    private final OrtEnvironment env;
+    private final OrtSession session;
+    private final String inputName;
+
+    public CuasStage2Infer(String model) throws Exception {
+        env = OrtEnvironment.getEnvironment();
+        OrtSession.SessionOptions opts = new OrtSession.SessionOptions();
+        try { opts.setSessionLogLevel(ai.onnxruntime.OrtLoggingLevel.ORT_LOGGING_LEVEL_ERROR); } catch (Exception e) {}
+        session = env.createSession(model, opts);
+        inputName = session.getInputNames().iterator().next();
+        System.out.println("CuasStage2Infer: loaded " + model + "  input=" + inputName);
+    }
+
+    /** acc = [3][w*h] (accS, accVx, accVy), row-major. Returns [3][w*h]: {sigmoid(det), Vx, Vy} refined. */
+    public double[][] refine(double[][] acc, int w, int h) throws Exception {
+        final int npix = w * h;
+        FloatBuffer fb = FloatBuffer.allocate(3 * npix);
+        for (int c = 0; c < 3; c++) for (int i = 0; i < npix; i++) fb.put((float) acc[c][i]);
+        fb.rewind();
+        double[][] out = new double[3][npix];
+        try (OnnxTensor in = OnnxTensor.createTensor(env, fb, new long[] {1, 3, h, w});
+             OrtSession.Result res = session.run(Collections.singletonMap(inputName, in))) {
+            float[][][][] o = (float[][][][]) res.get(0).getValue();   // [1,3,h,w]
+            for (int y = 0; y < h; y++) for (int x = 0; x < w; x++) {
+                int i = y * w + x;
+                out[0][i] = 1.0 / (1.0 + Math.exp(-o[0][0][y][x]));     // det -> sigmoid
+                out[1][i] = o[0][1][y][x];                              // Vx consensus
+                out[2][i] = o[0][2][y][x];                              // Vy consensus
+            }
+        }
+        return out;
+    }
+
+    public void close() { try { if (session != null) session.close(); } catch (Exception e) {} }
+}