paintplus: vendor the app source and rename from EditmaskwithAI

Bring the full EditmaskwithAI application into the repo under paintplus/
(429 files) so the service is self-contained — the installer copies the
vendored source to ~/docker/paintplus/src instead of cloning at runtime.

Rename to PaintPlus (service + branding; app logic untouched):
- services/editmaskwithai.sh -> services/paintplus.sh (register_service
  paintplus, install_paintplus, ~/docker/paintplus, Caddy paintplus:8000,
  Authelia option preserved)
- container names -> paintplus across docker-compose*.yml; dev network
  -> paintplus-network
- browser <title> -> "PaintPlus - AI Image Editor"; README heading ->
  PaintPlus with upstream provenance note
- README utilities table: editmaskwithai -> paintplus

Backend/frontend code (help strings referencing the old container name,
the ai_photo_edit.db filename) is intentionally left as-is to avoid
touching application logic.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Nb2vJ8W7bHKx1JXVvpCraH

paintplus/backend/app/services/local_inpaint.py

@@ -0,0 +1,82 @@
+"""
+Local inpainting operations — LaMa, OpenCV, and background removal.
+All operations use GPU automatically if PyTorch detects one, CPU otherwise.
+"""
+
+from io import BytesIO
+from PIL import Image
+import numpy as np
+import cv2
+
+# Lazy-loaded LaMa model (downloaded on first use, ~100MB)
+_lama = None
+
+
+def get_lama():
+    global _lama
+    if _lama is None:
+        from simple_lama_inpainting import SimpleLama
+        _lama = SimpleLama()
+    return _lama
+
+
+def lama_available() -> bool:
+    try:
+        import simple_lama_inpainting  # noqa: F401
+        return True
+    except ImportError:
+        return False
+
+
+def lama_inpaint(image_bytes: bytes, mask_bytes: bytes) -> bytes:
+    """LaMa structural inpainting — best for object removal and large fills."""
+    lama = get_lama()
+    image = Image.open(BytesIO(image_bytes)).convert("RGB")
+    mask = Image.open(BytesIO(mask_bytes)).convert("L")
+    if mask.size != image.size:
+        mask = mask.resize(image.size, Image.Resampling.LANCZOS)
+    result = lama(image, mask)
+    buf = BytesIO()
+    result.save(buf, format="PNG")
+    return buf.getvalue()
+
+
+def opencv_inpaint(image_bytes: bytes, mask_bytes: bytes, method: str = "telea") -> bytes:
+    """OpenCV fast structural inpainting — CPU only, milliseconds."""
+    image = Image.open(BytesIO(image_bytes)).convert("RGB")
+    mask = Image.open(BytesIO(mask_bytes)).convert("L")
+    if mask.size != image.size:
+        mask = mask.resize(image.size, Image.Resampling.LANCZOS)
+
+    img_np = np.array(image)
+    mask_np = np.array(mask)
+    _, mask_bin = cv2.threshold(mask_np, 127, 255, cv2.THRESH_BINARY)
+
+    flags = cv2.INPAINT_TELEA if method == "telea" else cv2.INPAINT_NS
+    result = cv2.inpaint(img_np, mask_bin, inpaintRadius=3, flags=flags)
+
+    buf = BytesIO()
+    Image.fromarray(result).save(buf, format="PNG")
+    return buf.getvalue()
+
+
+def remove_background_rembg(image_bytes: bytes) -> bytes:
+    """Background removal using rembg."""
+    from rembg import remove
+    return remove(image_bytes)
+
+
+def rembg_available() -> bool:
+    try:
+        import rembg  # noqa: F401
+        return True
+    except ImportError:
+        return False
+
+
+def gpu_available() -> bool:
+    try:
+        import torch
+        return torch.cuda.is_available()
+    except ImportError:
+        return False