Claude
cea9ee9d6c
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
99 lines
2.9 KiB
Python
99 lines
2.9 KiB
Python
#!/usr/bin/env python3
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"""
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Download Real-ESRGAN NCNN Vulkan binary.
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This gives you fast AI upscaling on ANY GPU (Intel/AMD/NVIDIA integrated or discrete,
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Apple Metal) without needing CUDA or Python AI packages.
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Usage:
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docker exec -it ai-photo-edit python /scripts/download_realesrgan.py
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# or locally:
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python scripts/download_realesrgan.py
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"""
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import os
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import sys
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import platform
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import zipfile
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import urllib.request
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import stat
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from pathlib import Path
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DEST_DIR = Path("/app/data/models/realesrgan")
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VERSION = "v0.2.5.0"
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PLATFORM_MAP = {
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"linux": f"realesrgan-ncnn-vulkan-{VERSION}-ubuntu.zip",
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"darwin": f"realesrgan-ncnn-vulkan-{VERSION}-macos.zip",
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"win32": f"realesrgan-ncnn-vulkan-{VERSION}-windows.zip",
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"windows": f"realesrgan-ncnn-vulkan-{VERSION}-windows.zip",
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}
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BASE_URL = f"https://github.com/xinntao/Real-ESRGAN/releases/download/{VERSION}"
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def main():
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plat = sys.platform.lower()
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if plat not in PLATFORM_MAP:
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print(f"Unknown platform: {plat}")
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sys.exit(1)
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filename = PLATFORM_MAP[plat]
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url = f"{BASE_URL}/{filename}"
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zip_path = DEST_DIR / filename
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DEST_DIR.mkdir(parents=True, exist_ok=True)
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binary_name = "realesrgan-ncnn-vulkan.exe" if "win" in plat else "realesrgan-ncnn-vulkan"
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binary_path = DEST_DIR / binary_name
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if binary_path.exists():
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print(f"Already installed: {binary_path}")
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print("Delete it and re-run to reinstall.")
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return
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print(f"Downloading Real-ESRGAN NCNN Vulkan {VERSION} for {plat}...")
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print(f"URL: {url}")
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def progress(count, block_size, total_size):
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if total_size > 0 and count % 100 == 0:
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pct = min(100, count * block_size * 100 // total_size)
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mb = count * block_size / 1024 / 1024
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total_mb = total_size / 1024 / 1024
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print(f" {pct}% ({mb:.1f}/{total_mb:.1f} MB)", end="\r")
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urllib.request.urlretrieve(url, zip_path, progress)
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print(f"\nDownloaded to {zip_path}")
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print("Extracting...")
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with zipfile.ZipFile(zip_path, "r") as zf:
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zf.extractall(DEST_DIR)
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# The zip extracts into a subdirectory — find the binary
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found = list(DEST_DIR.rglob(binary_name))
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if not found:
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print(f"ERROR: Could not find {binary_name} in extracted files.")
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sys.exit(1)
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extracted = found[0]
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if extracted != binary_path:
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extracted.rename(binary_path)
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# Make executable on unix
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if "win" not in plat:
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binary_path.chmod(binary_path.stat().st_mode | stat.S_IEXEC | stat.S_IXGRP | stat.S_IXOTH)
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# Clean up zip
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zip_path.unlink(missing_ok=True)
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print(f"\nInstalled: {binary_path}")
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print("\nTest it:")
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print(f" {binary_path} --help")
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print("\nThe upscaler will auto-detect this binary next time you use Upscale in PaintPlus.")
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print("Restart the backend container to clear the capability cache:")
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print(" docker-compose restart backend")
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if __name__ == "__main__":
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main()
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