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agents/model_agent.py

@@ -90,8 +90,8 @@ def m06_checkerboard(img):
     h1=float(np.corrcoef(gray[:,:-1].ravel()[::100],gray[:,1:].ravel()[::100])[0,1])
     v1=float(np.corrcoef(gray[:-1,:].ravel()[::100],gray[1:,:].ravel()[::100])[0,1])
     delta=((ha-h1)+(va-v1))/2
-    if delta>0.02: s,n=0.5,f"Checkerboard detected (Δ={delta:.4f})"
-    elif delta>0.005: s,n=0.2,f"Mild checkerboard ({delta:.4f})"
+    if delta>0.1: s,n=0.5,f"Strong checkerboard (Δ={delta:.4f})"
+    elif delta>0.05: s,n=0.25,f"Mild checkerboard (Δ={delta:.4f})"
     else: s,n=-0.1,f"No checkerboard ({delta:.4f})"
     return {"test":"Checkerboard Pattern","delta":round(delta,6),"score":s,"note":n}
 
@@ -163,7 +163,7 @@ def m11_color_consistency(img):
     for i in range(0,hc,ps):
         for j in range(0,wc,ps):
             p=rgb[i:i+ps,j:j+ps]; m=np.mean(p,axis=(0,1))
-            if m[1]>10: ratios.append(m[0]/(m[1]+1e-9))
+            if m[1]>30: ratios.append(m[0]/(m[1]+1e-9))  # min green=30 to avoid near-black patches
     if len(ratios)<4: return {"test":"Color Ratio Consistency","score":0.0,"note":"Few patches"}
     cv=float(np.std(ratios))/(float(np.mean(ratios))+1e-9)
     if cv>0.1: s,n=-0.2,f"Varied color ratios (CV={cv:.3f})"
@@ -239,14 +239,7 @@ ALL_TESTS=[m01_fft_grid_8x8,m02_fft_grid_16x16,m03_spectral_slope,m04_diffusion_
            m13_texture_repetition,m14_highfreq_noise_structure,m15_phase_coherence]
 
 def run_model_agent(img):
-    findings,scores=[],[]
-    for fn in ALL_TESTS:
-        try: r=fn(img); findings.append(r); scores.append(r["score"])
-        except Exception as e: findings.append({"test":fn.__name__,"error":str(e),"score":0})
-    avg=float(np.mean(scores)) if scores else 0.0; conf=min(1.0,0.5+0.5*abs(avg))
-    viol=[f["test"] for f in findings if f.get("score",0)>0.2]
-    comp=[f["test"] for f in findings if f.get("score",0)<-0.1]
-    rat=f"Model signatures: {', '.join(viol)}." if viol else f"No artifacts: {', '.join(comp)}." if comp else "Model analysis inconclusive."
-    for f in findings:
-        if f.get("note"): rat+=f" [{f['test']}]: {f['note']}."
-    return AgentEvidence("Generative Model Agent",np.clip(avg,-1,1),conf,max(0,1-len(scores)/len(ALL_TESTS)),rat,findings)
+    from agents.utils import run_agent_tests
+    from agents.optical_agent import AgentEvidence
+    findings, avg, conf, fail, rat = run_agent_tests(ALL_TESTS, img, "Generative Model Agent")
+    return AgentEvidence("Generative Model Agent",np.clip(avg,-1,1),conf,fail,rat,findings)