fix: depth preprocessor name + basicsr/torchvision import shim

Two bugs caught after the HF Space redesign push:

1. ControlNet Depth preview always showed the raw image. controlnet_aux's
Processor registers depth under 'depth_midas', not 'midas'. The plain
'midas' name raised KeyError, which _preview_cn silently swallowed
(returning the raw input). Fix: use 'depth_midas' in preprocessors._run_depth.

2. Upscale crashed with ModuleNotFoundError on torchvision.transforms.
functional_tensor — basicsr (a realesrgan dep) imports that module, but
torchvision >=0.17 removed it. Fix: alias torchvision.transforms.functional
into sys.modules['torchvision.transforms.functional_tensor'] inside
upscale._realesrgan_4x before basicsr loads.

3. Hardened _preview_cn to log the underlying exception to stderr instead of
swallowing silently. The next preprocessor bug surfaces in HF logs.

app.py

@@ -105,12 +105,20 @@ def _preview_cn(image, mode):
 
     Wrapped in ``try/except`` so that a missing optional dep (controlnet_aux for
     Depth / Pose) never breaks the form — it just falls back to the raw input.
+    We DO log the exception to stderr so the next failure surfaces in the logs
+    rather than silently showing the user the original image (the previous
+    behavior hid a typo'd processor name for weeks).
     """
     if image is None:
         return None
     try:
         return preprocessors.run(mode, image)
-    except Exception:
+    except Exception as e:
+        import sys
+        import traceback
+
+        print(f"[preview_cn] {mode!r} failed: {e}", file=sys.stderr, flush=True)
+        traceback.print_exc(file=sys.stderr)
         return image
 
 

preprocessors.py

@@ -35,7 +35,9 @@ def _run_canny(image: Image.Image) -> Image.Image:
 
 
 def _run_depth(image: Image.Image) -> Image.Image:
-    proc = _get_processor("midas")
+    # controlnet_aux's Processor takes "depth_midas", NOT "midas".
+    # Plain "midas" is not in its MODELS dict and raises KeyError.
+    proc = _get_processor("depth_midas")
     out: Any = proc(image)
     if isinstance(out, Image.Image):
         return out.convert("RGB")

upscale.py

@@ -26,7 +26,16 @@ _MODEL_CACHE: dict[str, Any] = {}
 
 def _realesrgan_4x(model_path: Path | str, image: Image.Image) -> Image.Image:
     """Run RealESRGAN x4plus on ``image``. Caches the model in-process."""
+    import sys
+
     import numpy as np
+    import torchvision.transforms.functional as _tvf
+
+    # basicsr (a realesrgan dep) imports torchvision.transforms.functional_tensor,
+    # which was removed in torchvision >=0.17. Alias the old path to the current
+    # module so basicsr's degradations import keeps working.
+    sys.modules.setdefault("torchvision.transforms.functional_tensor", _tvf)
+
     from basicsr.archs.rrdbnet_arch import RRDBNet
     from realesrgan import RealESRGANer