From cf5e1e0df2edf1b8eddf5357e5f9a5fca4e43d2f Mon Sep 17 00:00:00 2001
From: vladmandic <mandic00@live.com>
Date: Wed, 11 Feb 2026 18:09:57 +0100
Subject: [PATCH] cleanup convert

Signed-off-by: vladmandic <mandic00@live.com>
---
 modules/image/convert.py  | 9 +++++----
 modules/image/sharpfin.py | 8 ++------
 2 files changed, 7 insertions(+), 10 deletions(-)

diff --git a/modules/image/convert.py b/modules/image/convert.py
index 042436fd2..87e06a5bb 100644
--- a/modules/image/convert.py
+++ b/modules/image/convert.py
@@ -7,13 +7,13 @@ from installer import log
 
 def to_tensor(image: Image.Image | np.ndarray):
     """PIL Image -> float32 CHW tensor [0,1]. Pure torch, no torchvision."""
-    # fn = f'{sys._getframe(2).f_code.co_name}:{sys._getframe(1).f_code.co_name}' # pylint: disable=protected-access
-    if not isinstance(image, Image.Image):
+    if isinstance(image, Image.Image):
         pic = np.array(image, copy=True)
     elif isinstance(image, np.ndarray):
         pic = image.copy()
     else:
-        raise TypeError(f"Expected PIL Image or np.ndarray, got {type(image)}")
+        fn = f'{sys._getframe(2).f_code.co_name}:{sys._getframe(1).f_code.co_name}' # pylint: disable=protected-access
+        raise TypeError(f"convert: target=tensor type={type(image)} fn={fn} unsupported")
     if pic.ndim == 2:
         pic = pic[:, :, np.newaxis]
     tensor = torch.from_numpy(pic.transpose((2, 0, 1))).contiguous()
@@ -30,7 +30,8 @@ def to_pil(tensor: torch.Tensor | np.ndarray):
     elif isinstance(tensor, np.ndarray):
         tensor = torch.from_numpy(tensor)
     else:
-        raise TypeError(f"Expected torch.Tensor, got {type(tensor)}")
+        fn = f'{sys._getframe(2).f_code.co_name}:{sys._getframe(1).f_code.co_name}' # pylint: disable=protected-access
+        raise TypeError(f"convert: target=image type={type(tensor)} fn={fn} unsupported")
     try:
         if tensor.dim() == 4:
             if tensor.shape[-1] in (1, 3, 4) and tensor.shape[-1] < tensor.shape[-2]:  # BHWC
diff --git a/modules/image/sharpfin.py b/modules/image/sharpfin.py
index 9acffbba0..0fc52d34c 100644
--- a/modules/image/sharpfin.py
+++ b/modules/image/sharpfin.py
@@ -211,12 +211,8 @@ def resize_tensor(tensor: torch.Tensor, target_size: tuple[int, int], *, kernel=
         result = scale(tensor, target_size, resize_kernel=rk, device=dev, dtype=dt, do_srgb_conversion=linearize, use_sparse=use_sparse)
     else:
         log.debug(f'Resize tensor: method=sharpfin shape={tensor.shape} target={target_size} direction={both_up}:{both_down} kernel={rk} sparse=False fn={fn}')
-        if th > src_h:
-            intermediate = scale(tensor, (th, src_w), resize_kernel=rk, device=dev, dtype=dt, do_srgb_conversion=linearize, use_sparse=False)
-            result = scale(intermediate, (th, tw), resize_kernel=rk, device=dev, dtype=dt, do_srgb_conversion=linearize, use_sparse=False)
-        else:
-            intermediate = scale(tensor, (th, src_w), resize_kernel=rk, device=dev, dtype=dt, do_srgb_conversion=linearize, use_sparse=False)
-            result = scale(intermediate, (th, tw), resize_kernel=rk, device=dev, dtype=dt, do_srgb_conversion=linearize, use_sparse=False)
+        intermediate = scale(tensor, (th, src_w), resize_kernel=rk, device=dev, dtype=dt, do_srgb_conversion=linearize, use_sparse=False)
+        result = scale(intermediate, (th, tw), resize_kernel=rk, device=dev, dtype=dt, do_srgb_conversion=linearize, use_sparse=False)
     if squeezed:
         result = result.squeeze(0)
     return result