fix: persistenza immagini su disco (sopravvive restart server)

Bug: _IMAGES era dict in-memory, restart server → browser con id cached
riceveva 404 'Immagini non trovate'.

Fix: scrittura PNG in /tmp/pm2d_cache/{id}.png al upload, _load_image()
prova cache memory prima di leggere disco.

Rimossa funzione _store_image duplicata.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

pm2d/web/server.py

@@ -9,17 +9,15 @@ Endpoint:
 """
 from __future__ import annotations
 
-import base64
+import tempfile
-import io
 import time
 import uuid
 from pathlib import Path
-from typing import Any
 
 import cv2
 import numpy as np
 from fastapi import FastAPI, File, HTTPException, UploadFile
-from fastapi.responses import FileResponse, HTMLResponse, Response, StreamingResponse
+from fastapi.responses import HTMLResponse, Response
 from fastapi.staticfiles import StaticFiles
 from pydantic import BaseModel
 
@@ -31,20 +29,36 @@ WEB_DIR = Path(__file__).parent
 STATIC_DIR = WEB_DIR / "static"
 STATIC_DIR.mkdir(exist_ok=True)
 
-# In-memory image store: id → np.ndarray BGR
+# Persistenza immagini su disco (sopravvive a restart server)
-_IMAGES: dict[str, np.ndarray] = {}
+CACHE_DIR = Path(tempfile.gettempdir()) / "pm2d_cache"
-# Cache del last annotated: (image_id, matches_hash) → png bytes
+CACHE_DIR.mkdir(exist_ok=True)
-_ANNOT_CACHE: dict[tuple[str, int], bytes] = {}
 
-app = FastAPI(title="PM2D Webapp", version="1.0.0")
+# Cache in-memory (soft, ricaricata da disco se mancante)
+_IMG_CACHE: dict[str, np.ndarray] = {}
 
 
 def _store_image(img: np.ndarray) -> str:
     iid = uuid.uuid4().hex[:12]
-    _IMAGES[iid] = img
+    cv2.imwrite(str(CACHE_DIR / f"{iid}.png"), img)
+    _IMG_CACHE[iid] = img
     return iid
 
 
+def _load_image(iid: str) -> np.ndarray | None:
+    cached = _IMG_CACHE.get(iid)
+    if cached is not None:
+        return cached
+    p = CACHE_DIR / f"{iid}.png"
+    if not p.exists():
+        return None
+    img = cv2.imread(str(p))
+    if img is not None:
+        _IMG_CACHE[iid] = img
+    return img
+
+app = FastAPI(title="PM2D Webapp", version="1.0.0")
+
+
 def _encode_png(img: np.ndarray) -> bytes:
     ok, buf = cv2.imencode(".png", img)
     if not ok:
@@ -257,7 +271,7 @@ async def upload(file: UploadFile = File(...)):
 
 @app.get("/image/{iid}/raw")
 def image_raw(iid: str):
-    img = _IMAGES.get(iid)
+    img = _load_image(iid)
     if img is None:
         raise HTTPException(404, "Image not found")
     return Response(_encode_png(img), media_type="image/png")
@@ -265,8 +279,8 @@ def image_raw(iid: str):
 
 @app.post("/match", response_model=MatchResp)
 def match(p: MatchParams):
-    model = _IMAGES.get(p.model_id)
+    model = _load_image(p.model_id)
-    scene = _IMAGES.get(p.scene_id)
+    scene = _load_image(p.scene_id)
     if model is None or scene is None:
         raise HTTPException(404, "Immagini non trovate")
     x, y, w, h = p.roi
@@ -317,8 +331,8 @@ def match_simple(p: SimpleMatchParams):
     Il server deriva i parametri tecnici (num_features, soglie gradiente,
     piramide, ecc.) dall'analisi automatica della ROI.
     """
-    model = _IMAGES.get(p.model_id)
+    model = _load_image(p.model_id)
-    scene = _IMAGES.get(p.scene_id)
+    scene = _load_image(p.scene_id)
     if model is None or scene is None:
         raise HTTPException(404, "Immagini non trovate")
     x, y, w, h = p.roi
@@ -364,7 +378,7 @@ def match_simple(p: SimpleMatchParams):
 
 @app.post("/auto_tune")
 def tune(p: TuneParams):
-    model = _IMAGES.get(p.model_id)
+    model = _load_image(p.model_id)
     if model is None:
         raise HTTPException(404, "Immagine non trovata")
     x, y, w, h = p.roi