""" EXIF Scanner — Admin server integration module. Ports the exif-test server functionality into the admin server as an APIRouter. Shares the same assets.db (via CANTEEN_DB_PATH) and uses the exif-test photos.db (via EXIF_PHOTOS_DB) so both servers can access the same photo data. Mounted at /api/admin/exif and automatically protected by the admin server's auth middleware. """ import base64 import csv import datetime import hashlib import io import json import logging import math import os import re import sqlite3 import urllib.request import uuid from pathlib import Path from typing import Optional from fastapi import APIRouter, File, Form, HTTPException, Query, UploadFile from fastapi.responses import FileResponse, StreamingResponse 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 logger = logging.getLogger("exif_module") # ─── Config ───────────────────────────────────────────────────────────────── # Path to the exif-test photos database (shared between exif-test and admin) EXIF_PHOTOS_DB = Path(os.environ.get( "EXIF_PHOTOS_DB", str(Path(__file__).parent.parent / "exif-test" / "photos.db") )) # Path to the exif-test uploads directory EXIF_UPLOADS_DIR = Path(os.environ.get( "EXIF_UPLOADS_DIR", str(Path(__file__).parent.parent / "exif-test" / "uploads") )) # Canteen asset DB (shared — same as admin_server) CANTEEN_DB_PATH = os.environ.get( "CANTEEN_DB_PATH", str(Path(__file__).parent.parent / "canteen-asset-tracker" / "assets.db") ) # LLM OCR config OPENCODE_GO_KEY = (os.environ.get("OPENCODE_GO_API_KEY") or "").strip() OPENCODE_GO_BASE = (os.environ.get("OPENCODE_GO_BASE_URL") or "https://opencode.ai/zen/go/v1").strip() LLM_OCR_MODEL = (os.environ.get("LLM_OCR_MODEL") or "mimo-v2-omni").strip() GOOGLE_API_KEY = (os.environ.get("GOOGLE_API_KEY") or "").strip() GOOGLE_API_BASE = (os.environ.get("GOOGLE_API_BASE_URL") or "https://generativelanguage.googleapis.com/v1beta").strip() GOOGLE_OCR_MODEL = (os.environ.get("GOOGLE_OCR_MODEL") or "gemini-2.5-flash").strip() # Max images per batch API call BATCH_SIZE_LIMIT = 20 # Downscale images to this max dimension before LLM OCR LLM_IMAGE_MAX_DIM = 1600 # OCR prompts DEFAULT_OCR_PROMPT = ( "Read ALL text and numbers visible in this photo. " "Return the exact text shown, nothing else." ) STICKER_OCR_PROMPT = ( "This photo shows a colored equipment sticker (green, orange, or yellow background) " "with a 2D barcode and a machine ID number printed below the barcode. " "Read ONLY the machine ID number that appears below the barcode. " "It is typically a 5-digit number followed by a dash and 6 more digits " "(e.g., 12345-678901). Return ONLY the machine ID number, nothing else." ) DEFAULT_BATCH_PROMPT = ( "I have {n} photos. For EACH photo, read ALL visible text and numbers.\n" 'Respond with a JSON array of objects, one per photo in order:\n' '[{{"i":0,"text":"all text and digits found","digits":"e.g. 12345-678901 or null if none"}}, ...]\n' 'Return ONLY the JSON array, no markdown, no explanation.' ) STICKER_BATCH_PROMPT = ( "I have {n} photos of colored equipment stickers (green, orange, or yellow). " "Each sticker has a 2D barcode and a machine ID printed below it.\n" 'Respond with a JSON array of objects, one per photo in order:\n' '[{{"i":0,"sticker_color":"green/orange/yellow/unknown","machine_id":"12345-678901 or null if not found"}}, ...]\n' 'Return ONLY the JSON array, no markdown, no explanation.' ) # ─── Router ────────────────────────────────────────────────────────────────── router = APIRouter(prefix="/api/admin/exif", tags=["exif"]) # Ensure upload dir exists EXIF_UPLOADS_DIR.mkdir(parents=True, exist_ok=True) # ─── DB init (called from admin_server lifespan) ──────────────────────────── def create_exif_tables(): """Create photos and sessions tables if they don't exist.""" conn = sqlite3.connect(str(EXIF_PHOTOS_DB)) try: conn.execute("""CREATE TABLE IF NOT EXISTS photos ( id INTEGER PRIMARY KEY AUTOINCREMENT, orig_filename TEXT NOT NULL, file_hash TEXT NOT NULL UNIQUE, saved_as TEXT NOT NULL, file_size INTEGER, exif_json TEXT, gps_lat REAL, gps_lng REAL, ocr_engine TEXT, ocr_model TEXT, ocr_raw_text TEXT, ocr_match_5dash6 TEXT, ocr_match_5plus TEXT, machine_id TEXT, sticker_color TEXT, has_barcode INTEGER DEFAULT 0, session_id INTEGER, created_at TEXT DEFAULT (datetime('now')) )""") conn.execute("""CREATE TABLE IF NOT EXISTS sessions ( id INTEGER PRIMARY KEY AUTOINCREMENT, name TEXT NOT NULL DEFAULT '', building TEXT DEFAULT '', floor TEXT DEFAULT '', photo_count INTEGER DEFAULT 0, matched_count INTEGER DEFAULT 0, needs_gps_count INTEGER DEFAULT 0, closed_at TEXT, created_at TEXT DEFAULT (datetime('now')) )""") # Session column migration cols = [r[1] for r in conn.execute("PRAGMA table_info(photos)").fetchall()] if "session_id" not in cols: conn.execute("ALTER TABLE photos ADD COLUMN session_id INTEGER REFERENCES sessions(id)") conn.commit() except Exception: with sqlite3.connect(str(EXIF_PHOTOS_DB)) as c2: c2.execute("""CREATE TABLE IF NOT EXISTS photos ( id INTEGER PRIMARY KEY AUTOINCREMENT, orig_filename TEXT NOT NULL, file_hash TEXT NOT NULL UNIQUE, saved_as TEXT NOT NULL, file_size INTEGER DEFAULT NULL, exif_json TEXT DEFAULT NULL, gps_lat REAL DEFAULT NULL, gps_lng REAL DEFAULT NULL, ocr_engine TEXT DEFAULT NULL, ocr_model TEXT DEFAULT NULL, ocr_raw_text TEXT DEFAULT NULL, ocr_match_5dash6 TEXT DEFAULT NULL, ocr_match_5plus TEXT DEFAULT NULL, machine_id TEXT DEFAULT NULL, sticker_color TEXT DEFAULT NULL, has_barcode INTEGER DEFAULT 0, session_id INTEGER DEFAULT NULL, created_at TEXT DEFAULT (datetime('now')) )""") c2.execute("""CREATE TABLE IF NOT EXISTS sessions ( id INTEGER PRIMARY KEY AUTOINCREMENT, name TEXT NOT NULL DEFAULT '', building TEXT DEFAULT '', floor TEXT DEFAULT '', photo_count INTEGER DEFAULT 0, matched_count INTEGER DEFAULT 0, needs_gps_count INTEGER DEFAULT 0, closed_at TEXT, created_at TEXT DEFAULT (datetime('now')) )""") finally: conn.close() # ─── DB helpers ────────────────────────────────────────────────────────────── def _get_photos_db() -> sqlite3.Connection: conn = sqlite3.connect(str(EXIF_PHOTOS_DB)) conn.row_factory = sqlite3.Row return conn def _get_canteen_db(): """Get a read/write connection to the canteen assets database.""" path = Path(CANTEEN_DB_PATH) if not path.exists(): return None conn = sqlite3.connect(str(path)) conn.row_factory = sqlite3.Row return conn def _file_hash(data: bytes) -> str: return hashlib.sha256(data).hexdigest() def _row_to_dict(row: sqlite3.Row) -> dict: d = dict(row) d["exif_data"] = json.loads(d.pop("exif_json", "{}") or "{}") return d def _save_photo_to_db( orig_filename: str, file_hash: str, saved_as: str, file_size: int, exif_result: dict, ocr_result: dict, machine_id: str | None, session_id: int | None = None, ) -> int: conn = _get_photos_db() try: cur = conn.execute( """INSERT OR IGNORE INTO photos (orig_filename, file_hash, saved_as, file_size, exif_json, gps_lat, gps_lng, ocr_engine, ocr_model, ocr_raw_text, ocr_match_5dash6, ocr_match_5plus, machine_id, sticker_color, has_barcode, session_id) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)""", ( orig_filename, file_hash, saved_as, file_size, json.dumps(exif_result) if exif_result else None, exif_result.get("gps", {}).get("lat") if exif_result and exif_result.get("gps") else None, exif_result.get("gps", {}).get("lng") if exif_result and exif_result.get("gps") else None, ocr_result.get("engine") if ocr_result else None, ocr_result.get("llm_model") if ocr_result else None, ocr_result.get("raw_text") if ocr_result else None, ocr_result.get("match_5dash6") if ocr_result else None, ocr_result.get("match_5plus") if ocr_result else None, machine_id, ocr_result.get("sticker_color") if ocr_result else None, 1 if ocr_result and ocr_result.get("has_barcode") else 0, session_id, ), ) conn.commit() return cur.lastrowid or 0 except sqlite3.IntegrityError: return 0 finally: conn.close() 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 # ─── EXIF extraction ───────────────────────────────────────────────────────── def _dms_to_decimal(dms, ref): 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: 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 # ─── Tesseract OCR ─────────────────────────────────────────────────────────── def run_ocr(image_bytes: bytes) -> dict: if not HAS_TESSERACT: return {"available": False, "text": "", "error": "pytesseract not installed"} tmp_path = EXIF_UPLOADS_DIR / 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) # ─── LLM OCR helpers ───────────────────────────────────────────────────────── def _resize_for_llm(image_bytes: bytes, max_dim: int = LLM_IMAGE_MAX_DIM) -> bytes: img = PILImage.open(io.BytesIO(image_bytes)) w, h = img.size if max(w, h) <= max_dim: return image_bytes ratio = max_dim / max(w, h) new_size = (int(w * ratio), int(h * ratio)) img_resized = img.resize(new_size, PILImage.LANCZOS) buf = io.BytesIO() ext = img.format or "JPEG" if ext.upper() in ("PNG", "WEBP", "TIFF", "BMP"): img_resized = img_resized.convert("RGB") ext = "JPEG" img_resized.save(buf, format=ext, quality=85) return buf.getvalue() def run_ocr_llm( image_bytes: bytes, model: str | None = None, sticker_mode: bool = False, ) -> dict: if not OPENCODE_GO_KEY: result = run_ocr(image_bytes) result["engine"] = "tesseract" result["llm_fallback_reason"] = "no_api_key" return result model = model or LLM_OCR_MODEL image_bytes = _resize_for_llm(image_bytes) b64_img = base64.b64encode(image_bytes).decode() prompt = STICKER_OCR_PROMPT if sticker_mode else DEFAULT_OCR_PROMPT body = json.dumps({ "model": model, "messages": [{ "role": "user", "content": [ {"type": "text", "text": prompt}, {"type": "image_url", "image_url": {"url": f"data:image/jpeg;base64,{b64_img}"}} ] }], "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: 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) out = { "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, } if sticker_mode: color_match = re.search(r"\b(green|orange|yellow)\b", text, re.I) out["sticker_color"] = color_match.group(1).lower() if color_match else "unknown" return out def run_ocr_llm_batch( images: list[tuple[str, bytes]], model: str | None = None, max_per_batch: int = BATCH_SIZE_LIMIT, sticker_mode: bool = False, ) -> list[dict]: if not OPENCODE_GO_KEY: return [run_ocr(b) for _, b in images] model = model or LLM_OCR_MODEL all_results: list[dict] = [] for batch_start in range(0, len(images), max_per_batch): batch = images[batch_start:batch_start + max_per_batch] batch_results = _run_ocr_llm_batch_inner(batch, model, sticker_mode) all_results.extend(batch_results) return all_results def _run_ocr_llm_batch_inner( batch: list[tuple[str, bytes]], model: str, sticker_mode: bool = False, ) -> list[dict]: resized = [(_resize_for_llm(b), n) for n, b in batch] batch_prompt = (STICKER_BATCH_PROMPT if sticker_mode else DEFAULT_BATCH_PROMPT).format(n=len(batch)) content: list[dict] = [{"type": "text", "text": batch_prompt}] for idx, (img_bytes, _) in enumerate(resized): b64_img = base64.b64encode(img_bytes).decode() content.append({ "type": "image_url", "image_url": {"url": f"data:image/jpeg;base64,{b64_img}"} }) body = json.dumps({ "model": model, "messages": [{"role": "user", "content": content}], "max_tokens": min(300 * len(batch), 8000), "temperature": 0.1, }).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=120) result = json.loads(resp.read()) raw = result["choices"][0]["message"]["content"].strip() except Exception: return [run_ocr_llm(b, model, sticker_mode=sticker_mode) for n, b in batch] raw_clean = raw if raw_clean.startswith("```"): raw_clean = raw_clean.split("\n", 1)[-1] raw_clean = raw_clean.rsplit("```", 1)[0].strip() try: parsed = json.loads(raw_clean) results: list[dict] = [] for item in parsed: if sticker_mode: raw_text = str(item.get("machine_id", "") or "") else: raw_text = str(item.get("text", "") or "") digit_str = str(item.get("digits") or "") raw_text = raw_text + " " + digit_str match_5dash = re.search(r"(\d{5})[-\s]*(\d{6,})", raw_text) match_5plus = re.search(r"(\d{5,})", raw_text) entry: dict = { "available": True, "engine": "llm_batch", "llm_model": model, "raw_text": raw_text[:500], "match_5dash6": match_5dash.group(0) if match_5dash else None, "match_5plus": match_5plus.group(0) if match_5plus else None, } if sticker_mode: entry["sticker_color"] = str(item.get("sticker_color", "unknown")) results.append(entry) return results except (json.JSONDecodeError, KeyError, TypeError): return [run_ocr_llm(b, model, sticker_mode=sticker_mode) for n, b in batch] # ─── Google Gemini OCR ─────────────────────────────────────────────────────── def run_ocr_google(image_bytes: bytes, model: str | None = None, sticker_mode: bool = False) -> dict: if not GOOGLE_API_KEY: result = run_ocr(image_bytes) result["engine"] = "tesseract" result["llm_fallback_reason"] = "no_google_api_key" return result model = model or GOOGLE_OCR_MODEL image_bytes = _resize_for_llm(image_bytes) b64_img = base64.b64encode(image_bytes).decode() prompt = STICKER_OCR_PROMPT if sticker_mode else DEFAULT_OCR_PROMPT body = json.dumps({ "contents": [{ "parts": [ {"text": prompt}, {"inline_data": {"mime_type": "image/jpeg", "data": b64_img}} ] }], "generationConfig": {"maxOutputTokens": 200, "temperature": 0.1}, }).encode() req = urllib.request.Request( f"{GOOGLE_API_BASE}/models/{model}:generateContent?key={GOOGLE_API_KEY}", data=body, headers={"Content-Type": "application/json"}, ) try: resp = urllib.request.urlopen(req, timeout=60) result = json.loads(resp.read()) text = result["candidates"][0]["content"]["parts"][0]["text"].strip() except Exception as exc: 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) out: dict = { "available": True, "engine": "google", "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, } if sticker_mode: cm = re.search(r"\b(green|orange|yellow)\b", text, re.I) out["sticker_color"] = cm.group(1).lower() if cm else "unknown" return out # ─── Process helpers ───────────────────────────────────────────────────────── def _extract_machine_id(ocr_result: dict) -> str | None: match_5dash6 = ocr_result.get("match_5dash6") match_5plus = ocr_result.get("match_5plus") if match_5dash6: clean = re.sub(r"\D", "", match_5dash6) if len(clean) >= 5: return clean[:5] if match_5plus: clean = re.sub(r"\D", "", match_5plus) if len(clean) >= 5: return clean[:5] return None def _process_one(orig_filename: str, contents: bytes, ocr_engine: str, ocr_model: str | None, sticker_mode: bool) -> dict: file_size = len(contents) fhash = _file_hash(contents) dup_row = None db_conn = _get_photos_db() if db_conn: try: dup_row = db_conn.execute( "SELECT id, saved_as FROM photos WHERE file_hash = ?", (fhash,) ).fetchone() finally: db_conn.close() if dup_row: saved_name = dup_row["saved_as"] is_dup = True photo_id = dup_row["id"] else: ext = Path(orig_filename or "photo.jpg").suffix.lower() if ext not in {".jpg", ".jpeg", ".png", ".webp", ".bmp", ".tiff", ".tif", ".dng", ".heic", ".heif"}: ext = ".jpg" saved_name = f"{uuid.uuid4().hex}{ext}" (EXIF_UPLOADS_DIR / saved_name).write_bytes(contents) is_dup = False photo_id = None exif_result = extract_exif(contents) if ocr_engine == "llm": ocr_result = run_ocr_llm(contents, ocr_model, sticker_mode=sticker_mode) elif ocr_engine == "google": ocr_result = run_ocr_google(contents, ocr_model, sticker_mode=sticker_mode) 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 mid = _extract_machine_id(ocr_result) if mid: machine_id = mid asset = lookup_machine_id(machine_id) if not is_dup and not dup_row: photo_id = _save_photo_to_db( orig_filename, fhash, saved_name, file_size, exif_result, ocr_result, machine_id, ) return { "filename": orig_filename, "saved_as": saved_as if is_dup and not dup_row else saved_name, "photo_id": photo_id or (dup_row["id"] if dup_row else None), "file_size": file_size, "file_size_kb": round(file_size / 1024, 1), "duplicate": is_dup, "exif": exif_result, "ocr": ocr_result, "machine_id": machine_id, "asset": asset, } # ───────────────────────────────────────────────────────────────────────────── # API Endpoints # ───────────────────────────────────────────────────────────────────────────── @router.post("/analyze") async def analyze_photo( file: UploadFile = File(...), ocr_engine: str = Query(default="tesseract"), ocr_model: str = Query(default=""), sticker_mode: bool = Query(default=False), ): """Upload a photo, get back EXIF + OCR results.""" contents = await file.read() result = _process_one( file.filename or "photo.jpg", contents, ocr_engine, ocr_model or None, sticker_mode, ) return result @router.post("/bulk-process") async def bulk_process( files: list[UploadFile] = File(...), ocr_engine: str = Query(default="tesseract"), ocr_model: str = Query(default=""), sticker_mode: bool = Query(default=False), session_id: int | None = Query(default=None), ): """Process multiple photos: OCR each, extract EXIF GPS, look up matching assets.""" if not files: return {"results": [], "summary": {"total": 0, "has_gps": 0, "matched": 0, "needs_gps": 0}} all_files: list[tuple[str, bytes]] = [] for file in files: contents = await file.read() all_files.append((file.filename or "photo.jpg", contents)) ocr_use_llm = ocr_engine == "llm" ocr_use_google = ocr_engine == "google" if ocr_use_llm: llm_ocr_results = run_ocr_llm_batch( [(f, b) for f, b in all_files], ocr_model or None, sticker_mode=sticker_mode, ) else: llm_ocr_results = None results = [] summary = {"total": len(all_files), "has_gps": 0, "matched": 0, "needs_gps": 0, "duplicates": 0} for i, (orig_fname, contents) in enumerate(all_files): file_size = len(contents) fhash = _file_hash(contents) dup_row = None db_conn = _get_photos_db() if db_conn: try: dup_row = db_conn.execute( "SELECT id, saved_as FROM photos WHERE file_hash = ?", (fhash,) ).fetchone() finally: db_conn.close() if dup_row: saved_name = dup_row["saved_as"] is_dup = True photo_id = dup_row["id"] else: ext = Path(orig_fname or "photo.jpg").suffix.lower() if ext not in {".jpg", ".jpeg", ".png", ".webp", ".bmp", ".tiff", ".tif", ".dng", ".heic", ".heif"}: ext = ".jpg" saved_name = f"{uuid.uuid4().hex}{ext}" (EXIF_UPLOADS_DIR / saved_name).write_bytes(contents) is_dup = False photo_id = None exif_result = extract_exif(contents) if ocr_use_llm: ocr_result = llm_ocr_results[i] if i < len(llm_ocr_results) else {"available": False, "engine": "none", "error": "missing batch result"} elif ocr_use_google: ocr_result = run_ocr_google(contents, ocr_model or None, sticker_mode=sticker_mode) 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 mid = _extract_machine_id(ocr_result) if mid: machine_id = mid asset = lookup_machine_id(machine_id) needs_gps = False if asset: summary["matched"] += 1 has_photo_gps = exif_result.get("gps") is not None needs_gps = has_photo_gps and (asset.get("latitude") is None or asset.get("longitude") is None) if needs_gps: summary["needs_gps"] += 1 if exif_result.get("gps"): summary["has_gps"] += 1 if is_dup: summary["duplicates"] += 1 if not is_dup and not dup_row: photo_id = _save_photo_to_db( orig_fname, fhash, saved_name, file_size, exif_result, ocr_result, machine_id, session_id=session_id, ) results.append({ "filename": orig_fname, "saved_as": saved_name, "photo_id": photo_id or (dup_row["id"] if dup_row else None), "file_size": file_size, "file_size_kb": round(file_size / 1024, 1), "duplicate": is_dup, "exif": exif_result, "ocr": ocr_result, "machine_id": machine_id, "asset": asset, "needs_gps": needs_gps, }) return {"results": results, "summary": summary} @router.get("/photos") async def list_photos(limit: int = Query(default=50, le=200)): """List previously processed photos from DB (newest first).""" conn = _get_photos_db() try: rows = conn.execute( "SELECT * FROM photos ORDER BY created_at DESC LIMIT ?", (limit,) ).fetchall() return {"photos": [_row_to_dict(r) for r in rows]} finally: conn.close() @router.get("/photos/{photo_id}") async def get_photo(photo_id: int): """Get a single photo record from DB.""" conn = _get_photos_db() try: row = conn.execute("SELECT * FROM photos WHERE id = ?", (photo_id,)).fetchone() if not row: raise HTTPException(404, "Photo not found") return _row_to_dict(row) finally: conn.close() @router.get("/photos/{photo_id}/file") async def get_photo_file(photo_id: int): """Serve the saved image file for a photo record.""" conn = _get_photos_db() try: row = conn.execute("SELECT saved_as FROM photos WHERE id = ?", (photo_id,)).fetchone() if not row: raise HTTPException(404, "Photo not found") finally: conn.close() filepath = EXIF_UPLOADS_DIR / row["saved_as"] if not filepath.exists(): raise HTTPException(404, "File not found on disk") return FileResponse(str(filepath)) @router.post("/photos/{photo_id}/reprocess") async def reprocess_photo( photo_id: int, ocr_engine: str = Query(default="tesseract"), ocr_model: str = Query(default=""), sticker_mode: bool = Query(default=False), ): """Re-run OCR on a previously saved photo with different engine/model.""" conn = _get_photos_db() try: row = conn.execute( "SELECT saved_as, orig_filename FROM photos WHERE id = ?", (photo_id,) ).fetchone() if not row: raise HTTPException(404, "Photo not found") finally: conn.close() filepath = EXIF_UPLOADS_DIR / row["saved_as"] if not filepath.exists(): raise HTTPException(404, "Uploaded file not found on disk") contents = filepath.read_bytes() if ocr_engine == "llm": ocr_result = run_ocr_llm(contents, ocr_model or None, sticker_mode=sticker_mode) elif ocr_engine == "google": ocr_result = run_ocr_google(contents, ocr_model or None, sticker_mode=sticker_mode) 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 mid = _extract_machine_id(ocr_result) if mid: machine_id = mid asset = lookup_machine_id(machine_id) db2 = _get_photos_db() try: db2.execute( """UPDATE photos SET ocr_engine=?, ocr_model=?, ocr_raw_text=?, ocr_match_5dash6=?, ocr_match_5plus=?, machine_id=?, sticker_color=? WHERE id=?""", ( ocr_result.get("engine"), ocr_result.get("llm_model"), ocr_result.get("raw_text"), ocr_result.get("match_5dash6"), ocr_result.get("match_5plus"), machine_id, ocr_result.get("sticker_color"), photo_id, ), ) db2.commit() finally: db2.close() return { "photo_id": photo_id, "ocr_engine": ocr_result.get("engine"), "llm_model": ocr_result.get("llm_model"), "ocr": ocr_result, "machine_id": machine_id, "asset": asset, } @router.post("/photos/{photo_id}/reset") async def reset_photo(photo_id: int): """Delete a photo record and its file, allowing re-upload as new.""" conn = _get_photos_db() try: row = conn.execute("SELECT saved_as FROM photos WHERE id = ?", (photo_id,)).fetchone() if not row: raise HTTPException(404, "Photo not found") filepath = EXIF_UPLOADS_DIR / row["saved_as"] if filepath.exists(): filepath.unlink() conn.execute("DELETE FROM photos WHERE id = ?", (photo_id,)) conn.commit() finally: conn.close() return {"ok": True, "reset": photo_id, "message": "Photo entry deleted. Re-upload to process as new."} @router.delete("/photos/{photo_id}") async def delete_photo(photo_id: int): """Delete a photo record and its file from disk.""" conn = _get_photos_db() try: row = conn.execute("SELECT saved_as FROM photos WHERE id = ?", (photo_id,)).fetchone() if not row: raise HTTPException(404, "Photo not found") filepath = EXIF_UPLOADS_DIR / row["saved_as"] if filepath.exists(): filepath.unlink() conn.execute("DELETE FROM photos WHERE id = ?", (photo_id,)) conn.commit() finally: conn.close() return {"ok": True, "deleted": photo_id} @router.get("/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}'"} @router.post("/push-gps") async def push_gps(request: dict): """Update an asset's GPS coordinates from photo EXIF data.""" 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: row = conn.execute( "SELECT latitude, longitude FROM assets WHERE id = ?", (int(asset_id),) ).fetchone() if not row: raise HTTPException(404, f"Asset {asset_id} not found") if row["latitude"] is not None and row["longitude"] is not None: 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() return {"updated": True, "asset_id": asset_id, "latitude": float(latitude), "longitude": float(longitude)} except Exception as e: raise HTTPException(500, str(e)) finally: conn.close() @router.get("/uploads") async def list_uploads(): """List previously uploaded files.""" files = sorted(EXIF_UPLOADS_DIR.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] ] @router.get("/export") async def export_photos( format: str = Query(default="csv", pattern="^(csv|kml|clipboard)$"), session_id: int | None = Query(default=None), limit: int = Query(default=500, le=5000), ): """Export photos as CSV, KML, or clipboard-ready text.""" conn = _get_photos_db() try: if session_id: rows = conn.execute( "SELECT * FROM photos WHERE session_id = ? ORDER BY created_at DESC LIMIT ?", (session_id, limit), ).fetchall() else: rows = conn.execute( "SELECT * FROM photos ORDER BY created_at DESC LIMIT ?", (limit,) ).fetchall() finally: conn.close() records = [] for r in rows: d = _row_to_dict(r) rec = { "filename": d.get("orig_filename", ""), "lat": d.get("gps_lat"), "lng": d.get("gps_lng"), "machine_id": d.get("machine_id", ""), "ocr_engine": d.get("ocr_engine", ""), "sticker_color": d.get("sticker_color", ""), "timestamp": d.get("created_at", ""), } if d.get("machine_id"): asset = lookup_machine_id(d["machine_id"]) if asset: rec.update({ "asset_name": asset.get("name", ""), "building": asset.get("building_name", ""), "floor": asset.get("floor", ""), "room": asset.get("room", ""), "make": asset.get("make", ""), "model": asset.get("model", ""), }) records.append(rec) if format == "csv": output = io.StringIO() writer = csv.writer(output) header = ["filename", "lat", "lng", "machine_id", "asset_name", "building", "floor", "room", "make", "model", "ocr_engine", "sticker_color", "timestamp"] bom = "\ufeff" output.write(bom) writer.writerow(header) for rec in records: writer.writerow([rec.get(h.replace("-", "_"), "") for h in header]) csv_content = output.getvalue() return StreamingResponse( iter([csv_content]), media_type="text/csv", headers={"Content-Disposition": f"attachment; filename=exif-export.csv"}, ) elif format == "kml": kml_parts = [ '', '', " ", f" EXIF Export ({len(records)} photos)", ] for rec in records: if rec["lat"] is None or rec["lng"] is None: continue name = rec.get("asset_name") or rec.get("machine_id") or rec.get("filename", "Photo") desc_lines = [ f"Filename: {rec['filename']}", f"Machine ID: {rec.get('machine_id', 'N/A')}", f"OCR Engine: {rec.get('ocr_engine', 'N/A')}", f"Timestamp: {rec.get('timestamp', 'N/A')}", ] kml_parts.append(" ") kml_parts.append(f" {name}") kml_parts.append(f" {chr(10).join(desc_lines)}") kml_parts.append(" ") kml_parts.append(f" {rec['lng']},{rec['lat']},0") kml_parts.append(" ") kml_parts.append(" ") kml_parts.append(" ") kml_parts.append("") kml_content = "\n".join(kml_parts) return StreamingResponse( iter([kml_content]), media_type="application/vnd.google-earth.kml+xml", headers={"Content-Disposition": f"attachment; filename=exif-export.kml"}, ) else: # clipboard lines = [] for rec in records: if rec["lat"] is not None and rec["lng"] is not None: label = rec.get("asset_name") or rec.get("machine_id") or rec.get("filename", "?") lines.append(f"{rec['lat']:.6f},{rec['lng']:.6f} # {label}") return {"count": len(lines), "text": "\n".join(lines)} @router.post("/assign-machine-id") async def assign_machine_id(request: dict): """Manually assign a machine_id to a photo record.""" photo_id = request.get("photo_id") machine_id = (request.get("machine_id") or "").strip() if not photo_id or not machine_id: raise HTTPException(400, "photo_id and machine_id are required") conn = _get_photos_db() try: row = conn.execute("SELECT id, gps_lat, gps_lng FROM photos WHERE id = ?", (photo_id,)).fetchone() if not row: raise HTTPException(404, f"Photo {photo_id} not found") conn.execute("UPDATE photos SET machine_id = ? WHERE id = ?", (machine_id, photo_id)) conn.commit() finally: conn.close() asset = lookup_machine_id(machine_id) has_photo_gps = row["gps_lat"] is not None and row["gps_lng"] is not None needs_gps = bool(asset and (asset["latitude"] is None or asset["longitude"] is None) and has_photo_gps) return { "photo_id": photo_id, "machine_id": machine_id, "asset": asset, "needs_gps": needs_gps, } @router.get("/nearby") async def nearby_assets( lat: float = Query(...), lng: float = Query(...), radius: float = Query(default=10.0, ge=1, le=1000), exclude_photo_id: int | None = Query(default=None), ): """Find canteen assets near a GPS point.""" conn = _get_canteen_db() if not conn: return {"nearby": [], "count": 0, "radius_m": radius} try: lat_rad = lat * 3.14159265 / 180.0 deg_per_m_lat = 1.0 / 111320.0 deg_per_m_lng = 1.0 / (111320.0 * math.cos(lat_rad)) rad_deg = radius * deg_per_m_lat rows = conn.execute( """SELECT id, machine_id, name, latitude, longitude, building_name, floor, room, category, status FROM assets WHERE latitude IS NOT NULL AND longitude IS NOT NULL AND (latitude - ?) * (latitude - ?) + (longitude - ?) * (longitude - ?) < ? ORDER BY (latitude - ?) * (latitude - ?) + (longitude - ?) * (longitude - ?) LIMIT 50""", (lat, lat, lng, lng, rad_deg * rad_deg, lat, lat, lng, lng), ).fetchall() nearby = [] for row in rows: dlat = row["latitude"] - lat dlng = (row["longitude"] - lng) * math.cos(lat_rad) distance_m = (dlat * dlat + dlng * dlng) ** 0.5 * 111320.0 if distance_m >= radius: continue nearby.append({ "asset_id": row["id"], "machine_id": row["machine_id"], "name": row["name"], "distance_m": round(distance_m, 1), "latitude": row["latitude"], "longitude": row["longitude"], "has_gps": True, "building": row.get("building_name"), "floor": row.get("floor"), "room": row.get("room"), "category": row.get("category"), "status": row.get("status"), }) nearby.sort(key=lambda x: x["distance_m"]) return {"nearby": nearby, "count": len(nearby), "radius_m": radius} finally: conn.close() @router.get("/sessions") async def list_sessions(): """List all sessions, newest first.""" conn = _get_photos_db() try: rows = conn.execute( "SELECT * FROM sessions ORDER BY created_at DESC LIMIT 100" ).fetchall() return {"sessions": [_row_to_dict(r) for r in rows]} finally: conn.close() @router.post("/sessions") async def create_session(request: dict): """Create a new session.""" name = (request.get("name") or "").strip() or f"Session {datetime.datetime.now().strftime('%Y-%m-%d %H:%M')}" building = (request.get("building") or "").strip() floor = (request.get("floor") or "").strip() conn = _get_photos_db() try: cur = conn.execute( "INSERT INTO sessions (name, building, floor) VALUES (?, ?, ?)", (name, building, floor), ) conn.commit() session_id = cur.lastrowid row = conn.execute("SELECT * FROM sessions WHERE id = ?", (session_id,)).fetchone() return _row_to_dict(row) finally: conn.close() @router.get("/sessions/{session_id}") async def get_session(session_id: int): """Get a session with all its photos.""" conn = _get_photos_db() try: srow = conn.execute("SELECT * FROM sessions WHERE id = ?", (session_id,)).fetchone() if not srow: raise HTTPException(404, "Session not found") session = _row_to_dict(srow) photos = conn.execute( "SELECT * FROM photos WHERE session_id = ? ORDER BY created_at ASC", (session_id,), ).fetchall() session["photos"] = [_row_to_dict(r) for r in photos] total = len(session["photos"]) matched = sum(1 for p in session["photos"] if p.get("machine_id")) needs_gps = sum(1 for p in session["photos"] if p.get("machine_id") and (p.get("gps_lat") is None)) conn.execute( "UPDATE sessions SET photo_count=?, matched_count=?, needs_gps_count=? WHERE id=?", (total, matched, needs_gps, session_id), ) conn.commit() session["photo_count"] = total session["matched_count"] = matched session["needs_gps_count"] = needs_gps return session finally: conn.close() @router.post("/sessions/{session_id}/close") async def close_session(session_id: int): """Finalize a session.""" conn = _get_photos_db() try: row = conn.execute("SELECT id FROM sessions WHERE id = ?", (session_id,)).fetchone() if not row: raise HTTPException(404, "Session not found") conn.execute( "UPDATE sessions SET closed_at = datetime('now') WHERE id = ?", (session_id,), ) conn.commit() return {"ok": True, "session_id": session_id, "closed_at": "now"} finally: conn.close() @router.post("/bulk-assign") async def bulk_assign_machine_id(request: dict): """Assign the same machine_id to multiple photos at once.""" photo_ids = request.get("photo_ids", []) machine_id = (request.get("machine_id") or "").strip() if not photo_ids or not isinstance(photo_ids, list): raise HTTPException(400, "photo_ids must be a non-empty list") if not machine_id: raise HTTPException(400, "machine_id is required") asset = lookup_machine_id(machine_id) conn = _get_photos_db() no_gps_files = [] gps_pushed = 0 try: for pid in photo_ids: row = conn.execute( "SELECT id, orig_filename, gps_lat, gps_lng, machine_id FROM photos WHERE id = ?", (pid,), ).fetchone() if not row: continue conn.execute( "UPDATE photos SET machine_id = ? WHERE id = ?", (machine_id, pid), ) if asset and (asset["latitude"] is None or asset["longitude"] is None): gps_lat = row["gps_lat"] gps_lng = row["gps_lng"] if gps_lat is not None and gps_lng is not None: canteen = _get_canteen_db() if canteen: try: canteen.execute( "UPDATE assets SET latitude=?, longitude=?, updated_at=datetime('now') WHERE id=?", (float(gps_lat), float(gps_lng), asset["id"]), ) canteen.commit() gps_pushed += 1 finally: canteen.close() else: no_gps_files.append(row.get("orig_filename", f"photo_{pid}")) conn.commit() finally: conn.close() return { "updated": len(photo_ids), "gps_pushed": gps_pushed, "no_gps": no_gps_files, }