"""EXIF + OCR test backend — validate that GPS survives upload pipeline.""" import io, json, os, re, uuid, sqlite3, urllib.request from pathlib import Path from fastapi import FastAPI, File, Form, HTTPException, Query, UploadFile from fastapi.staticfiles import StaticFiles from PIL import Image as PILImage # Optional HEIC/HEIF support for iPhone photos try: from pillow_heif import register_heif_opener register_heif_opener() HAS_HEIF = True except ImportError: HAS_HEIF = False try: import pytesseract HAS_TESSERACT = True except ImportError: HAS_TESSERACT = False # === LLM OCR via OpenCode Go === OPENCODE_GO_KEY = os.environ.get("OPENCODE_GO_API_KEY", "") OPENCODE_GO_BASE = os.environ.get("OPENCODE_GO_BASE_URL", "https://opencode.ai/zen/go/v1") LLM_OCR_MODEL = os.environ.get("LLM_OCR_MODEL", "mimo-v2-omni") UPLOADS = Path(__file__).parent / "uploads" UPLOADS.mkdir(exist_ok=True) CANTEEN_DB = Path(__file__).parent.parent / "canteen-asset-tracker" / "assets.db" app = FastAPI(title="EXIF Test") def _get_canteen_db(): """Get a read/write connection to the canteen assets database.""" if not CANTEEN_DB.exists(): return None conn = sqlite3.connect(str(CANTEEN_DB)) conn.row_factory = sqlite3.Row return conn def _dms_to_decimal(dms, ref): """Convert EXIF DMS tuple to decimal degrees.""" try: deg, minutes, sec = float(dms[0]), float(dms[1]), float(dms[2]) decimal = deg + minutes / 60.0 + sec / 3600.0 if ref in ("S", "W"): decimal = -decimal return round(decimal, 7) except Exception: return None def extract_exif(image_bytes: bytes) -> dict: """Pull all useful EXIF fields + GPS from raw image bytes.""" result = {"has_exif": False, "tags": {}, "gps": None} try: img = PILImage.open(io.BytesIO(image_bytes)) exif = img.getexif() if not exif: return result for tag_id, value in exif.items(): tag_name = PILImage.ExifTags.TAGS.get(tag_id, f"0x{tag_id:04x}") if tag_name in ("MakerNote", "UserComment", "PrintImageMatching"): continue result["tags"][tag_name] = str(value)[:300] if result["tags"]: result["has_exif"] = True gps_ifd = exif.get_ifd(0x8825) if gps_ifd: lat_ref = gps_ifd.get(1, "N") lat_dms = gps_ifd.get(2) lng_ref = gps_ifd.get(3, "E") lng_dms = gps_ifd.get(4) if lat_dms and lng_dms: lat = _dms_to_decimal(lat_dms, lat_ref) lng = _dms_to_decimal(lng_dms, lng_ref) if lat is not None and lng is not None: result["gps"] = { "lat": lat, "lng": lng, "lat_ref": str(lat_ref), "lng_ref": str(lng_ref), "raw_lat_dms": [float(v) for v in lat_dms], "raw_lng_dms": [float(v) for v in lng_dms], } except Exception as e: result["error"] = str(e) return result def run_ocr(image_bytes: bytes) -> dict: """Run Tesseract OCR on the image.""" if not HAS_TESSERACT: return {"available": False, "text": "", "error": "pytesseract not installed"} tmp_path = UPLOADS / f"ocr_{uuid.uuid4().hex}.jpg" tmp_path.write_bytes(image_bytes) try: img = PILImage.open(tmp_path) img_gray = img.convert("L") text = pytesseract.image_to_string(img_gray, config="--psm 6") match_5dash = re.search(r"(\d{5})[-\s]*(\d{6,})", text) match_5plus = re.search(r"(\d{5,})", text) return { "available": True, "raw_text": text.strip()[:500], "match_5dash6": match_5dash.group(0) if match_5dash else None, "match_5plus": match_5plus.group(0) if match_5plus else None, } finally: tmp_path.unlink(missing_ok=True) def run_ocr_llm(image_bytes: bytes, model: str | None = None) -> dict: """Run OCR via an LLM vision model on OpenCode Go. Falls back to Tesseract if the API key is missing or the call fails. Returns the same shape as run_ocr() with an additional ''engine'' field. """ if not OPENCODE_GO_KEY: result = run_ocr(image_bytes) result["engine"] = "tesseract" result["llm_fallback_reason"] = "no_api_key" return result import base64 model = model or LLM_OCR_MODEL b64 = base64.b64encode(image_bytes).decode() body = json.dumps({ "model": model, "messages": [{ "role": "user", "content": [ {"type": "text", "text": "Read ALL text and numbers visible in this photo. " "Return the exact text shown, nothing else."}, {"type": "image_url", "image_url": {"url": f"data:image/jpeg;base64,{b64}"}} ] }], "max_tokens": 200, }).encode() req = urllib.request.Request( f"{OPENCODE_GO_BASE}/chat/completions", data=body, headers={ "Authorization": f"Bearer {OPENCODE_GO_KEY}", "Content-Type": "application/json", "User-Agent": "Hermes-Agent/1.0", }, ) try: resp = urllib.request.urlopen(req, timeout=60) result = json.loads(resp.read()) text = result["choices"][0]["message"]["content"].strip() except Exception as exc: # Fallback to Tesseract result = run_ocr(image_bytes) result["engine"] = "tesseract" result["llm_fallback_reason"] = str(exc)[:200] return result match_5dash = re.search(r"(\d{5})[-\s]*(\d{6,})", text) match_5plus = re.search(r"(\d{5,})", text) return { "available": True, "engine": "llm", "llm_model": model, "raw_text": text[:500], "match_5dash6": match_5dash.group(0) if match_5dash else None, "match_5plus": match_5plus.group(0) if match_5plus else None, } def lookup_machine_id(machine_id: str) -> dict | None: """Look up an asset by machine_id. Returns asset dict or None.""" conn = _get_canteen_db() if not conn: return None try: row = conn.execute( "SELECT id, machine_id, name, category, status, address, building_name, " "floor, room, latitude, longitude, make, model, description, photo_path " "FROM assets WHERE machine_id = ?", (machine_id.strip(),), ).fetchone() if row: return { "id": row["id"], "machine_id": row["machine_id"], "name": row["name"], "category": row["category"], "status": row["status"], "address": row["address"], "building_name": row["building_name"], "floor": row["floor"], "room": row["room"], "latitude": row["latitude"], "longitude": row["longitude"], "make": row["make"], "model": row["model"], "description": row["description"], "photo_path": row["photo_path"], } finally: conn.close() return None @app.post("/api/analyze") async def analyze_photo( file: UploadFile = File(...), ocr_engine: str = Query(default="tesseract"), ocr_model: str = Query(default=""), ): """Upload a photo, get back EXIF + OCR results. Query params: - ocr_engine: ''tesseract'' (default) or ''llm'' - ocr_model: model name override (e.g. ''mimo-v2-omni'', ''glm-5.1'') """ contents = await file.read() file_size = len(contents) ext = Path(file.filename or "photo.jpg").suffix.lower() if ext not in {".jpg", ".jpeg", ".png", ".webp", ".bmp", ".tiff", ".tif", ".dng", ".heic", ".heif"}: ext = ".jpg" fname = f"{uuid.uuid4().hex}{ext}" (UPLOADS / fname).write_bytes(contents) exif_result = extract_exif(contents) if ocr_engine == "llm": ocr_result = run_ocr_llm(contents, ocr_model or None) elif HAS_TESSERACT: ocr_result = run_ocr(contents) ocr_result["engine"] = "tesseract" else: ocr_result = {"available": False, "text": "", "engine": "none"} machine_id = None asset = None if ocr_result.get("match_5dash6"): machine_id = re.sub(r"\D", "", ocr_result["match_5dash6"])[-5:] asset = lookup_machine_id(machine_id) return { "filename": file.filename, "saved_as": fname, "file_size": file_size, "file_size_kb": round(file_size / 1024, 1), "exif": exif_result, "ocr": ocr_result, "machine_id": machine_id, "asset": asset, } @app.post("/api/bulk-process") async def bulk_process( files: list[UploadFile] = File(...), ocr_engine: str = Query(default="tesseract"), ocr_model: str = Query(default=""), ): """Process multiple photos: OCR each, extract EXIF GPS, look up matching assets. Query params: - ocr_engine: ''tesseract'' (default) or ''llm'' - ocr_model: model name override Returns a list of results, each with: - filename, exif (gps), ocr match, matched asset (if found) - needs_gps: true if asset exists AND has no coordinates AND photo has GPS """ if not files: return {"results": [], "summary": {"total": 0, "has_gps": 0, "matched": 0, "needs_gps": 0}} results = [] summary = {"total": len(files), "has_gps": 0, "matched": 0, "needs_gps": 0} for file in files: contents = await file.read() file_size = len(contents) # Save ext = Path(file.filename or "photo.jpg").suffix.lower() if ext not in {".jpg", ".jpeg", ".png", ".webp", ".bmp", ".tiff", ".tif", ".dng", ".heic", ".heif"}: ext = ".jpg" fname = f"{uuid.uuid4().hex}{ext}" (UPLOADS / fname).write_bytes(contents) exif_result = extract_exif(contents) if ocr_engine == "llm": ocr_result = run_ocr_llm(contents, ocr_model or None) elif HAS_TESSERACT: ocr_result = run_ocr(contents) ocr_result["engine"] = "tesseract" else: ocr_result = {"available": False, "text": "", "engine": "none"} has_gps = exif_result.get("gps") is not None if has_gps: summary["has_gps"] += 1 machine_id = None asset = None needs_gps = False if ocr_result.get("match_5dash6"): machine_id = re.sub(r"\D", "", ocr_result["match_5dash6"])[-5:] asset = lookup_machine_id(machine_id) if asset: summary["matched"] += 1 # Check if asset needs GPS if (asset["latitude"] is None or asset["longitude"] is None) and has_gps: needs_gps = True summary["needs_gps"] += 1 results.append({ "filename": file.filename, "saved_as": fname, "file_size_kb": round(file_size / 1024, 1), "exif": exif_result, "ocr": ocr_result, "machine_id": machine_id, "asset": asset, "needs_gps": needs_gps, }) return {"results": results, "summary": summary} @app.get("/api/lookup") async def lookup_asset(machine_id: str = ""): """Look up an asset by machine_id in the canteen assets database.""" if not machine_id or not machine_id.strip(): return {"found": False, "reason": "No machine_id provided"} asset = lookup_machine_id(machine_id.strip()) if asset: return {"found": True, "asset": asset} return {"found": False, "reason": f"No asset with machine_id '{machine_id}'"} @app.post("/api/push-gps") async def push_gps(request: dict): """Update an asset's GPS coordinates from photo EXIF data. Body: {"asset_id": 123, "latitude": 40.7417, "longitude": -73.9292} Only updates assets that currently have NULL lat/lng. """ asset_id = request.get("asset_id") latitude = request.get("latitude") longitude = request.get("longitude") if not asset_id or latitude is None or longitude is None: raise HTTPException(400, "asset_id, latitude, and longitude are required") conn = _get_canteen_db() if not conn: raise HTTPException(500, "Database not available") try: # Only update if currently NULL row = conn.execute( "SELECT latitude, longitude FROM assets WHERE id = ?", (int(asset_id),) ).fetchone() if not row: conn.close() raise HTTPException(404, f"Asset {asset_id} not found") if row["latitude"] is not None and row["longitude"] is not None: conn.close() return {"updated": False, "reason": "Asset already has GPS coordinates", "asset_id": asset_id} conn.execute( "UPDATE assets SET latitude = ?, longitude = ?, updated_at = datetime('now') WHERE id = ?", (float(latitude), float(longitude), int(asset_id)), ) conn.commit() conn.close() return {"updated": True, "asset_id": asset_id, "latitude": float(latitude), "longitude": float(longitude)} except Exception as e: try: conn.close() except Exception: pass raise HTTPException(500, str(e)) @app.get("/api/uploads") async def list_uploads(): """List previously uploaded files.""" files = sorted(UPLOADS.glob("*"), key=lambda p: p.stat().st_mtime, reverse=True) return [ {"name": f.name, "size_kb": round(f.stat().st_size / 1024, 1)} for f in files[:20] ] # Mount static LAST app.mount("/", StaticFiles(directory="static", html=True), name="static") if __name__ == "__main__": import uvicorn uvicorn.run(app, host="0.0.0.0", port=8903)