fixing divergent behavior in Cellpose and CellposeModel (#865)

cellpose/models.py

@@ -155,6 +155,7 @@ def eval(self, x, batch_size=8, channels=None, channel_axis=None, invert=False,
 
         tic0 = time.time()
         channels = [0, 0] if channels is None else channels
+        models_logger.warning("channels not specified, using [0,0] (grayscale + no nuclei)")
 
         diam0 = diameter[0] if isinstance(diameter, (np.ndarray, list)) else diameter
         estimate_size = True if (diameter is None or diam0 == 0) else False
@@ -539,6 +540,9 @@ def _run_cp(self, x, compute_masks=True, normalize=True, invert=False, niter=Non
                     masks = utils.stitch3D(masks, stitch_threshold=stitch_threshold)
                     masks = utils.fill_holes_and_remove_small_masks(
                         masks, min_size=min_size)
+                elif nimg > 1:
+                    models_logger.warning("3D stack used, but stitch_threshold=0 and do_3D=False, so masks are made per plane only")
+
 
             flow_time = time.time() - tic
             if nimg > 1:

cellpose/transforms.py

@@ -520,9 +520,9 @@ def convert_image(x, channels, channel_axis=None, z_axis=None, do_3D=False, ncha
                 % (nchan, nchan))
             x = x[..., :nchan]
 
-        if not do_3D and x.ndim > 3:
-            transforms_logger.critical("ERROR: cannot process 4D images in 2D mode")
-            raise ValueError("ERROR: cannot process 4D images in 2D mode")
+        #if not do_3D and x.ndim > 3:
+        #    transforms_logger.critical("ERROR: cannot process 4D images in 2D mode")
+        #    raise ValueError("ERROR: cannot process 4D images in 2D mode")
 
         if nchan is not None and x.shape[-1] < nchan:
             x = np.concatenate((x, np.tile(np.zeros_like(x), (1, 1, nchan - 1))),