refactor: integrate sharpfin for high-quality image resize

Vendor sharpfin library (Apache 2.0) and add centralized wrapper
module (images_sharpfin.py) replacing torchvision tensor/PIL
conversion and resize operations throughout the codebase.

- Add modules/sharpfin/ vendored library with MKS2021, Lanczos3,
  Mitchell, Catmull-Rom kernels and optional Triton sparse acceleration
- Add modules/images_sharpfin.py wrapper with to_tensor(), to_pil(),
  pil_to_tensor(), normalize(), resize(), resize_tensor()
- Add resize_quality and resize_linearize_srgb settings
- Add MKS2021 and Lanczos3 upscaler entries
- Replace torchvision.transforms.functional imports across 18 files
- to_pil() auto-detects HWC/BHWC layout, adds .round() before uint8
- Sparse Triton path falls back to dense GPU on compilation failure
- Mixed-axis resize splits into two single-axis scale() calls
- Masks and non-sRGB data always use linearize=False

modules/shared.py

@@ -671,6 +671,10 @@ options_templates.update(options_section(('postprocessing', "Postprocessing"), {
     "upscaler_latent_steps": OptionInfo(20, "Upscaler latent steps", gr.Slider, {"minimum": 4, "maximum": 100, "step": 1}),
     "upscaler_tile_size": OptionInfo(192, "Upscaler tile size", gr.Slider, {"minimum": 0, "maximum": 512, "step": 16}),
     "upscaler_tile_overlap": OptionInfo(8, "Upscaler tile overlap", gr.Slider, {"minimum": 0, "maximum": 64, "step": 1}),
+
+    "postprocessing_sep_resize": OptionInfo("<h2>Resize</h2>", "", gr.HTML),
+    "resize_quality": OptionInfo("Sharpfin MKS2021", "Image resize algorithm", gr.Dropdown, {"choices": ["PIL Lanczos", "Sharpfin MKS2021", "Sharpfin Lanczos3", "Sharpfin Mitchell", "Sharpfin Catmull-Rom"]}),
+    "resize_linearize_srgb": OptionInfo(True, "Apply sRGB linearization during image resize"),
 }))