feat: auto-select blender based on camera type

- NavCam -> enblend --pre-assemble (better vignette/horizon handling)
- Mastcam-Z -> verdandi (eliminates overexposure at seam transitions)
- Based on visual comparison: enblend default is best for NavCam,
  verdandi is best for MCZ (user confirmed)

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

pipeline/panorama_pipeline.py

@@ -278,8 +278,20 @@ def build_pto(pto_path, img_paths, azs, els, img_w, img_h, fov, ref_idx=None):
 # ============================================================
 
 def run_pipeline(work_dir, clahe_images, original_images, azs, els,
-                 img_w, img_h, fov, output_name):
+                 img_w, img_h, fov, output_name, blender="auto", camera=None):
-    """Full pipeline: cpfind(CLAHE) -> swap(originals) -> optimize(geo) -> nona -> verdandi."""
+    """Full pipeline: cpfind(CLAHE) -> swap(originals) -> optimize(geo) -> nona -> blend.
+
+    Blender selection:
+      - auto: enblend for NavCam (better vignette/horizon), verdandi for Mastcam-Z (no seam overexposure)
+      - enblend: force enblend --pre-assemble
+      - verdandi: force verdandi
+    """
+    # Select blender
+    if blender == "auto":
+        if camera and "MCZ" in camera:
+            blender = "verdandi"
+        else:
+            blender = "enblend"
 
     timings = {}
 
@@ -351,13 +363,16 @@ def run_pipeline(work_dir, clahe_images, original_images, azs, els,
         print("  ERROR: nona produced no output")
         return None, timings
 
-    # verdandi (better transitions than enblend, no overexposure at seams)
+    # Blend: verdandi for MCZ (no seam overexposure), enblend for NavCam (better vignette)
-    print("  verdandi...", flush=True)
+    print(f"  {blender}...", flush=True)
     out_tif = os.path.join(work_dir, f"{output_name}.tif")
     tif_list = " ".join([f'"{t}"' for t in tifs])
     t0 = time.time()
-    run_hugin("verdandi", f'-o "{out_tif}" {tif_list}', cwd=work_dir)
+    if blender == "verdandi":
-    timings["verdandi"] = time.time() - t0
+        run_hugin("verdandi", f'-o "{out_tif}" {tif_list}', cwd=work_dir)
+    else:
+        run_hugin("enblend", f'--pre-assemble -o "{out_tif}" {tif_list}', cwd=work_dir)
+    timings["blend"] = time.time() - t0
 
     # Convert to PNG
     out_png = os.path.join(work_dir, f"{output_name}.png")
@@ -456,7 +471,8 @@ def process_navcam(sol, camera, rover, data_dir, output_dir):
 
     output_name = f"panorama_sol{sol}"
     result, timings = run_pipeline(work_dir, clahe_imgs, originals,
-                                    azs, els, img_w, img_h, fov, output_name)
+                                    azs, els, img_w, img_h, fov, output_name,
+                                    camera=camera)
 
     print_timings(timings)
     return result
@@ -536,7 +552,8 @@ def process_mastcamz(sol, camera, rover, data_dir, output_dir):
 
     output_name = f"panorama_sol{sol}_mcz"
     result, timings = run_pipeline(work_dir, clahe_imgs, originals,
-                                    azs, els, img_w, img_h, fov, output_name)
+                                    azs, els, img_w, img_h, fov, output_name,
+                                    camera=camera)
 
     print_timings(timings)
     return result