Smart upscale: auto-detect hardware and pick best Real-ESRGAN path

Detection priority (probed once, cached):
  1. Real-ESRGAN PyTorch + CUDA GPU   → fastest, best quality
  2. Real-ESRGAN PyTorch + Apple MPS  → fast on Apple Silicon
  3. Real-ESRGAN NCNN Vulkan binary   → fast on any GPU via Vulkan (no CUDA needed)
  4. Real-ESRGAN PyTorch CPU          → works, slow (warned in UI)
  5. Lanczos                          → always available, instant fallback

Backend:
- services/upscale.py: full capability probe (probe_upscale_capabilities),
  implementations for PyTorch (CUDA/MPS/CPU auto-device) and NCNN binary,
  upscale_sync() resolves method with fallback chain,
  async upscale_image() runs in thread pool
- print_tools.py: /api/print/upscale uses new service; method="auto" by default;
  GET /api/print/upscale/available returns full capability map with device info
  and recommended_label; POST /api/print/upscale/refresh-caps busts cache
  without restart (useful after installing NCNN binary into container)

Frontend:
- upscale.js: fetches capability map on first open; builds method selector showing
  only available options; labels recommended method with ★; shows device info
  (CUDA/MPS/CPU/NCNN) in dialog; maps display label back to method key on submit;
  shows actual method used in success toast and undo history entry

Scripts:
- scripts/download_realesrgan.py: downloads NCNN Vulkan binary for current platform
  (Linux/macOS/Windows) to /app/data/models/realesrgan/; makes executable;
  run inside container or locally

https://claude.ai/code/session_01B58MaJCU1R6KwBDJCp8AfN

scripts/download_realesrgan.py

@@ -0,0 +1,98 @@
+#!/usr/bin/env python3
+"""
+Download Real-ESRGAN NCNN Vulkan binary.
+
+This gives you fast AI upscaling on ANY GPU (Intel/AMD/NVIDIA integrated or discrete,
+Apple Metal) without needing CUDA or Python AI packages.
+
+Usage:
+    docker exec -it ai-photo-edit python /scripts/download_realesrgan.py
+    # or locally:
+    python scripts/download_realesrgan.py
+"""
+
+import os
+import sys
+import platform
+import zipfile
+import urllib.request
+import stat
+from pathlib import Path
+
+DEST_DIR = Path("/app/data/models/realesrgan")
+VERSION = "v0.2.5.0"
+
+PLATFORM_MAP = {
+    "linux":  f"realesrgan-ncnn-vulkan-{VERSION}-ubuntu.zip",
+    "darwin": f"realesrgan-ncnn-vulkan-{VERSION}-macos.zip",
+    "win32":  f"realesrgan-ncnn-vulkan-{VERSION}-windows.zip",
+    "windows": f"realesrgan-ncnn-vulkan-{VERSION}-windows.zip",
+}
+
+BASE_URL = f"https://github.com/xinntao/Real-ESRGAN/releases/download/{VERSION}"
+
+
+def main():
+    plat = sys.platform.lower()
+    if plat not in PLATFORM_MAP:
+        print(f"Unknown platform: {plat}")
+        sys.exit(1)
+
+    filename = PLATFORM_MAP[plat]
+    url = f"{BASE_URL}/{filename}"
+    zip_path = DEST_DIR / filename
+
+    DEST_DIR.mkdir(parents=True, exist_ok=True)
+
+    binary_name = "realesrgan-ncnn-vulkan.exe" if "win" in plat else "realesrgan-ncnn-vulkan"
+    binary_path = DEST_DIR / binary_name
+
+    if binary_path.exists():
+        print(f"Already installed: {binary_path}")
+        print("Delete it and re-run to reinstall.")
+        return
+
+    print(f"Downloading Real-ESRGAN NCNN Vulkan {VERSION} for {plat}...")
+    print(f"URL: {url}")
+
+    def progress(count, block_size, total_size):
+        if total_size > 0 and count % 100 == 0:
+            pct = min(100, count * block_size * 100 // total_size)
+            mb = count * block_size / 1024 / 1024
+            total_mb = total_size / 1024 / 1024
+            print(f"  {pct}% ({mb:.1f}/{total_mb:.1f} MB)", end="\r")
+
+    urllib.request.urlretrieve(url, zip_path, progress)
+    print(f"\nDownloaded to {zip_path}")
+
+    print("Extracting...")
+    with zipfile.ZipFile(zip_path, "r") as zf:
+        zf.extractall(DEST_DIR)
+
+    # The zip extracts into a subdirectory — find the binary
+    found = list(DEST_DIR.rglob(binary_name))
+    if not found:
+        print(f"ERROR: Could not find {binary_name} in extracted files.")
+        sys.exit(1)
+
+    extracted = found[0]
+    if extracted != binary_path:
+        extracted.rename(binary_path)
+
+    # Make executable on unix
+    if "win" not in plat:
+        binary_path.chmod(binary_path.stat().st_mode | stat.S_IEXEC | stat.S_IXGRP | stat.S_IXOTH)
+
+    # Clean up zip
+    zip_path.unlink(missing_ok=True)
+
+    print(f"\nInstalled: {binary_path}")
+    print("\nTest it:")
+    print(f"  {binary_path} --help")
+    print("\nThe upscaler will auto-detect this binary next time you use Upscale in PaintPlus.")
+    print("Restart the backend container to clear the capability cache:")
+    print("  docker-compose restart backend")
+
+
+if __name__ == "__main__":
+    main()