Handle scipy.cluster.vq.kmeans too few points

Resolves #6664

utils/autoanchor.py

@@ -126,9 +126,10 @@ def print_results(k, verbose=True):
     # Kmeans calculation
     LOGGER.info(f'{PREFIX}Running kmeans for {n} anchors on {len(wh)} points...')
     s = wh.std(0)  # sigmas for whitening
-    k, dist = kmeans(wh / s, n, iter=30)  # points, mean distance
-    assert len(k) == n, f'{PREFIX}ERROR: scipy.cluster.vq.kmeans requested {n} points but returned only {len(k)}'
-    k *= s
+    k = kmeans(wh / s, n, iter=30)[0] * s  # points
+    if len(k) != n:  # kmeans may return fewer points than requested if wh is insufficient or too similar
+        LOGGER.warning(f'{PREFIX}WARNING: scipy.cluster.vq.kmeans returned only {len(k)} of {n} requested points')
+        k = np.sort(np.random.rand(n * 2)).reshape(n, 2) * img_size  # random init
     wh = torch.tensor(wh, dtype=torch.float32)  # filtered
     wh0 = torch.tensor(wh0, dtype=torch.float32)  # unfiltered
     k = print_results(k, verbose=False)