diff --git a/assets/_fine.py b/assets/_fine.py
index 9234d7a..3908428 100644
--- a/assets/_fine.py
+++ b/assets/_fine.py
@@ -73,7 +73,26 @@ def block_size(a):
         if tot and ok / tot > 0.82: best = b
     return best
 
-def frames(a, cuts):
+# WHERE TO CUT WHEN THE FIGURES TOUCH. Segmentation by empty columns needs a clear gap, and the
+# generator routinely spaces a row so a belly, an elbow or a racket overlaps its neighbour — a whole
+# sheet of otherwise perfect art then reports "found 2 frames, expected 4" and is thrown away. That
+# happened five times in one afternoon, and the sheet it lost last was the best roll of the day.
+# A row is EVENLY SPACED by construction (we ask for one), so when the count is known the honest
+# recovery is: look near each even division and cut at the THINNEST column within that window —
+# between two figures the ink thins out even where it does not vanish. Never used to guess a count,
+# only to reach a count we already asked for.
+def valley_cuts(ink_cols, x0, x1, n):
+    span = x1 - x0
+    win = max(2, span // (3 * n))
+    out = []
+    for k in range(1, n):
+        c = x0 + span * k // n
+        lo, hi = max(x0 + 1, c - win), min(x1 - 1, c + win)
+        if hi <= lo: return []
+        out.append(lo + int(np.argmin(ink_cols[lo:hi])))
+    return out
+
+def frames(a, cuts, want=0):
     ink = (a[..., 3] > 0)
     cols = ink.any(0)
     out, start, gap = [], None, 0
@@ -88,13 +107,22 @@ def frames(a, cuts):
     for c in sorted(cuts, reverse=True):          # manual splits where two figures touch
         for i, (x0, x1) in enumerate(out):
             if x0 < c < x1: out[i:i+1] = [(x0, c), (c, x1)]; break
+    # ...and the automatic version of the same rescue, when no manual cut was given
+    if want and len(out) < want and not cuts:
+        xs = np.where(cols)[0]
+        if len(xs):
+            auto = valley_cuts(ink.sum(0), int(xs.min()), int(xs.max()) + 1, want)
+            if auto:
+                print(f'note: only {len(out)} blob(s) — figures touch; cutting at {auto}')
+                edges = [int(xs.min())] + auto + [int(xs.max()) + 1]
+                out = list(zip(edges, edges[1:]))
     return out
 
 def main(sheet, outs, target_h, cuts, anchor, defringe=2):
     a = key(Image.open(sheet), defringe)
     b = block_size(a)
     crops = []
-    for x0, x1 in frames(a, cuts):
+    for x0, x1 in frames(a, cuts, len(outs)):
         sub = a[:, x0:x1]
         ys = np.where((sub[..., 3] > 0).any(1))[0]; xs = np.where((sub[..., 3] > 0).any(0))[0]
         crops.append(sub[ys.min():ys.max()+1, xs.min():xs.max()+1])